Web-based Intensive Monitoring. a patient based pharmacovigilance tool

Transcription

1 Web-based Intensive Monitoring a patient based pharmacovigilance tool

2 ISBN: The work presented in this thesis was performed at the Netherlands Pharmacovigilance Centre Lareb and the Department of Pharmacotherapy and Pharmaceutical Care, Rijksuniversiteit Groningen. Cover design: Beekhuis&Holthuis, Asten Lay-out inside work: Optima Grafische Communicatie, Rotterdam Printed by: Optima Grafische Communicatie, Rotterdam Financial support by the Nederlands Bijwerkingen Fonds for publication of this thesis is gratefully acknowledged. Linda Härmark, 2012

3 RIJKSUNIVERSITEIT GRONINGEN Web-based Intensive Monitoring a patient based pharmacovigilance tool Proefschrift ter verkrijging van het doctoraat in de Wiskunde en Natuurwetenschappen aan de Rijksuniversiteit Groningen op gezag van de Rector Magnificus, dr. E. Sterken, in het openbaar te verdedigen op maandag 4 juni 2012 om uur door Linda Veronica Dae-Hee Härmark geboren op 25 januari 1978 te Seoul, Zuid-Korea

4 Promotores: Prof. dr. A.C. van Grootheest Prof. dr. J.J. de Gier Copromotor: Dr. E.P. van Puijenbroek Beoordelingscommissie: Prof. dr. H.G.M. Leufkens Prof. dr. S.A. Shakir Prof. dr. B. Wilffert

5 Table of contents Chapter 1 Introduction 7 Chapter 2 Pharmacovigilance and intensive monitoring Pharmacovigilance: methods, recent developments and future perspectives 19 Chapter 3 Patients as a source of information in web-based intensive monitoring Patients motives for participating in active post-marketing surveillance Non-response in a pharmacy and patient based intensive monitoring system, a 55 quantitative study on non-response bias and reasons for non-response Chapter 4 Representativeness of patients participating in a web-based intensive monitoring system 4.1 Representativeness of diabetes patients participating in a web-based adverse drug reaction monitoring system Chapter 5 Description of the Lareb Intensive Monitoring system using pregabalin and duloxetine as examples 5.1 Intensive monitoring of pregabalin: results from an observational, web-based, prospective cohort study in the Netherlands using the patient as a source of information 5.2 Intensive monitoring of duloxetine, results from a web-based intensive monitoring study 5.3 Longitudinal monitoring of the safety of drugs by using a web-based system: the case of pregabalin Chapter 6 Application of web-based intensive monitoring Monitoring the safety of influenza A (H1N1) vaccine using web-based intensive 133 monitoring 6.2 Web-based intensive monitoring: from passive to active drug surveillance 153 Chapter 7 General discussion 167 Summary Samenvatting Sammanfattning Dankwoord List of publications About the author

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7 Chapter 1 Introduction

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9 Introduction 9 1. Introduction Pharmacovigilance 4. During the twentieth century drug development as an industry started to take off. With the 5. discovery of insulin, penicillin and sulphonamides it was possible to treat diseases which 6. had previously been deadly, saving millions of lives. In the early days of drug development 7. there were no regulations regarding a drug s quality, efficacy and safety [1]. In the late 1950 s 8. and beginning of the 1960 s it became evident that drugs were not only saving lives, they 9. could also have a negative impact on it [2]. Even though adverse drug reactions (ADRs) were 10. acknowledged as a problem related to drug use, it was the congenital abnormalities seen 11. in children whose mothers had used thalidomide during pregnancy that acted as a wake 12. up call to start to look more intensively at the negative effects of drugs [3]. Following the 13. thalidomide disaster, authorities all over the world began to set up systems in order to monitor the safety of drugs. These spontaneous reporting systems were based on the collection of reports of ADRs from healthcare professionals. The World Health Organisation (WHO) 16. recognised the need for global drug monitoring, since drugs are seldom registered in one 17. country only, and in 1968 the WHO Pilot Research Project for International Drug Monitoring 18. started its operation with 10 participating countries, with the purpose to develop a system 19. for the detection of previously unknown or poorly understood adverse effects of drugs [4,5]. 20. From there, the practice as well as the science of pharmacovigilance has been developed and 21. today pharmacovigilance is defined by the WHO as the science and activities relating to the 22. detection, assessment, understanding and prevention of adverse effects or any other drug 23. related problem [5] Pharmacovigilance in the 21st century 26. In the last few years there has been renewed interest in pharmacovigilance. It started with the 27. withdrawal of rofecoxib in 2004 [6] followed by the debate about the cardiovascular safety 28. of rosiglitazone [7,8], which ultimately lead to the suspension of the marketing authorisation 29. of the drug in the European Union (EU). These high profile cases lead to a debate about the 30. ability of the current pharmacovigilance system to identify harm [9-12] and forced the pharmacovigilance community to critically evaluate the existing pharmacovigilance systems in place [13,14]. In the European Union the evaluation of the pharmacovigilance system in [14] lead to legislative changes, which were endorsed in September 2010 and will come into 34. force in July 2012 [15,16]. To support the implementation of the new EU pharmacovigilance 35. legislation, the European Medicines Agency (EMA) is developing a new set of guidelines for 36. the conduct of pharmacovigilance. This new guidance on good pharmacovigilance practices 37. (GVP) is organised in 16 different modules [17]. 1

10 10 Chapter 1 1. With the new legislation a strengthening of post-authorisation regulation of medicines will 2. be implemented, which has two key elements: one related to the process, where it is important that there are clear roles, responsibilities and obligations for the key responsible parties and the other related to the collection of high-quality data relevant to the safety of medicines 5. and patient safety, which is a requirement for the prompt identification of potential risks Spontaneous reporting of ADRs by physicians and pharmacists has been the backbone of 8. data collection in pharmacovigilance and has proven its value in detecting relatively rare and 9. serious ADRs [18]. Within the new legislation, spontaneous reporting will continue to play an 10. important role and the range of possible reporters will be expanded by including patients. 11. Research in the last few years has shown that patients reports are a valuable addition to a 12. spontaneous reporting system [19-23]. Besides spontaneous reporting by healthcare professionals and patients, there is also a need for a different kind of information about ADRs than spontaneous reporting can provide. Spontaneous reporting systems focus on detecting 15. signals of new ADRs and it has proven its strength in detecting previously unknown harm. It 16. has also met criticism; under-reporting and its inability to quantify adverse drug reactions are 17. most often mentioned [18] Waller and Evans [24] have suggested that pharmacovigilance should be less focused on finding harm and more focused on extending knowledge of safety. Increased information about the safety of a drug, e.g. information about the time course of ADRs such as time to onset and 22. duration can help patients to be adherent to their medication. This can be achieved through 23. active, systematic collection of information about adverse drug reactions Intensive Monitoring 26. In an effort to come to terms with some of the shortcomings of spontaneous reporting i.e. 27. under-reporting and the inability to quantify ADRs, a new form of active surveillance was 28. developed. In the late 1970 s the Intensive Monitoring Medicines Programme (IMMP) was 29. established in New Zealand [25] and since the beginning of the 1980 s the Prescription Event 30. Monitoring programme (PEM) has been running in the UK [26]. The basis of these intensive 31. monitoring systems is a non-interventional observational cohort where users of certain drugs 32. are identified on basis of prescription data. The prescriber of the drug is sent a questionnaire 33. and is asked about any adverse events that may occur during the use of the drug being 34. monitored. These data are collected and analysed for new signals [25,26] Intensive monitoring distinguishes itself from spontaneous reporting because the former 37. only monitors selected drugs during a certain period of time. Through its non-interventional character, intensive monitoring provides real-world clinical data involving neither inclusion nor exclusion criteria throughout the collection period. Since it is based on event monitoring

11 Introduction it can identify signals for events that were not necessarily suspected as being ADRs of the 2. drug under study. Since it is a cohort study, it enables the incidence of adverse events to be 3. estimated, thus enabling quantification of ADRs Intensive monitoring also has limitations. As in spontaneous reporting, the proportion of 6. adverse effects that go unreported to doctors is unknown; the studies therefore produce 7. reported event rates rather than true incident rates. This is the same for all studies based on 8. medical record data, including computer databases and record linkage. There is no control 9. group in standard intensive monitoring studies, and the true background incidence for 10. events is therefore not known [25,26] Intensive Monitoring in the Netherlands 13. The Lareb Foundation started in the eighties as a local initiative of pharmacists and general 14. practitioners to collect adverse drug reaction reports with the aim to improve pharmacotherapy [27]. What started as a local initiative grew, and in 1995 the Netherlands Pharmaco vigilance Centre Lareb became responsible for the collection and analysis of adverse drug 17. reaction reports in the Netherlands. In order to be able to do this on a high scientific level, 18. research concerning the core business has always been part of its activities [28]. In recent 19. years, research in the areas of statistical signal detection [29-33] and the contribution of 20. pharmacists [34-38] and patients [39] reports to pharmacovigilance has been conducted in 21. order to develop the spontaneous reporting system further. In the continuous process of 22. trying to further develop its activities, Lareb recognised the need for development of new 23. pharmacovigilance methods that could act as a complement to the spontaneous reporting 24. system In 1996 a study was conducted which investigated if the first prescription signal generated in 27. the pharmacy could be of use in post-marketing surveillance [40]. Patients identified through 28. such a signal were given a questionnaire to complete and it was evaluated if the information provided in the questionnaire could give a clear picture of the patient s experiences with the drug. This study concluded that the first prescription signal in the pharmacy was a 31. good way to identify users of specific drugs in order to follow their experiences with the drug 32. intensively A few years later a second study was conducted in which again the first prescription signal 35. in the pharmacy was used to identify new users of a particular drug, however in this case the 36. questionnaires were not given to the patient but to the prescribing GP. The GP was asked to 37. complete the questionnaire upon the patient s next visit. An evaluation of this study showed that pharmacists and GPs are motivated to participate in an intensive monitoring system [41]. 1

12 12 Chapter 1 1. After these two initial studies it was decided to develop an intensive monitoring system. 2. As Lareb had experiences with patient reports [19] and believed in the patient as an important player in pharmacovigilance, it was decided to use patients as a source of information [19,42,43]. In the same period, Lareb had gained experience in using IT-solutions for data 5. processing, so it was chosen to make the system web-based. In 2006 Lareb Intensive Monitoring (LIM), a web-based intensive monitoring system using patients as a source of information was introduced complementary to the spontaneous reporting system In the majority of studies presented in this thesis patients eligible for inclusion were identified using the first dispensation in the pharmacy. However, inclusion is not limited to the pharmacy and one study presented in this thesis uses the general practitioner s office as 12. point of inclusion. At the inclusion point, the patient is informed about the intensive monitoring study and is asked to participate. When registering online, the patient is asked for an address which will be used for further correspondence. In addition, information about 15. patient characteristics and drug use is collected. After registration, the patient receives questionnaires by at specific points in time, allowing longitudinal data collection. In these questionnaires, questions are asked about drug use and possible ADRs. These data are coded 18. and analysed with the purpose of identifying new signals or obtaining information that will 19. extend the knowledge about the safety of the drug under study Objectives and outline of the thesis Web-based intensive monitoring using patients as a source of information was developed 25. with the aim of gathering data about the safety of drugs that more traditional methods such 26. as clinical trials or spontaneous reporting are not able to do. In order for web-based intensive 27. monitoring to be a useful pharmacovigilance method, it has to provide proof of concept and 28. show what kind of information it can capture. In addition, since the method brings in a few 29. relatively new elements such as patients as the source of information and using web-based 30. questionnaires, the method needs to be further characterised The objective of this thesis is to describe a web-based intensive monitoring system using patients 33. as a source of information and its application as a pharmacovigilance tool Chapter 2 provides a background to the field of pharmacovigilance. In addition, current 36. methods used in pharmacovigilance such as clinical trials, spontaneous reporting and intensive monitoring are described in more detail with their strengths and limitations. 37.

13 Introduction In all studies performed with web-based intensive monitoring so far, the patient has been the 2. source of information. Patient participation is increasing in pharmacovigilance but until now 3. this has been limited to spontaneous reporting. Chapter 3 focuses on patient participation in 4. web-based intensive monitoring. Patient participation is essential for the good functioning of 5. the system and therefore patients motivation for participation was investigated. In addition, 6. reasons for non-response were also identified to see what the barriers for participation are Since not all patients who are eligible for inclusion chose to participate in web-based intensive monitoring, it is important to obtain information about the characteristics of the LIM population compared to the whole population using the drug. In Chapter 4, a web-based 11. intensive monitoring population is compared to a reference population to see how they 12. compare on parameters which may influence a patient s susceptibility to develop adverse 13. drug reactions With the theoretical concept of web-based intensive monitoring, it was believed that the 16. system could generate different types of information than for example spontaneous reporting. Chapter 5 provides proof of the theoretical concept. The results from the first web-based intensive monitoring studies, concerning the drugs pregabalin and duloxetine, illustrate the 19. kind of data that can be obtained through longitudinal web-based intensive monitoring The characteristics of web-based intensive monitoring, using a specific inclusion point, 22. letting the patient be the source of information and collecting data through web-based 23. questionnaires can be used to collect data about the safety of drugs in other settings than 24. through community pharmacy. In Chapter 6 this is further elaborated and an example is 25. given how web-based intensive monitoring was used to gather data about the safety of the 26. Influenza A (H1N1 ) pandemic vaccine Chapter 7 comprises a general discussion where web-based intensive monitoring as a 29. methodology will be summarised and future research will be suggested. In addition, since 30. this thesis only shows one application of web-based intensive monitoring, future perspectives about the application of the method and how it can be used to meet society s need for information about adverse drug reactions will be presented

14 14 Chapter References 1. Heath G, Colburn WA. An evolution of drug development and clinical pharmacology during the 20th century. J Clin Pharmacol 2000; 40: van Grootheest K. The dawn of pharmacovigilance: an historical perspective. Int J Pharm Med 2003; 17: McBride WG. Thalidomide and congenital malformations. Lancet 1961; 2: Venulet J, Helling-Borda M. WHO s international drug monitoring--the formative years, : preparatory, pilot and early operational phases. Drug Saf 2010; 33: e1-e The Importance of Pharmacovigilance. WHO Available via Accessed Jan 20, Merck Announces Voluntary Worldwide Withdrawal of VIOXX. Merck & Co Available via Accessed March 1, Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes. N Engl J Med 2007; 356: Singh S, Loke YK, Furberg CD. Long-term risk of cardiovascular events with rosiglitazone: a metaanalysis. JAMA 2007; 298: Greener M. Drug safety on trial. Last year s withdrawal of the anti-arthritis drug Vioxx triggered a debate about how to better monitor drug safety even after approval. EMBO Rep 2005; 6: Horton R. Vioxx, the implosion of Merck, and aftershocks at the FDA. Lancet 2004; 364: Krumholz HM, Ross JS, Presler AH, et al. What have we learnt from Vioxx? BMJ 2007; 334: Rosen CJ. The rosiglitazone story--lessons from an FDA Advisory Committee meeting. N Engl J Med 2007; 357: Baciu A, Stratton K, Burke SP, editors. Committee on the Assessment of the US Drug Safety System The future of drug safety: promoting and protecting the health of the public. Institute of Medicine Washington DC. 14. Assessment of the European Community System of Pharmacovigilance. European Medicines Agency Available via Accessed March 1, Directive 2010/84/EU. Official Journal of the European Union 2010, Dec 31,L. 348/ Regulation 1235/2010. Official Journal of the European Union 2010, Dec 31,L. 348/ Good Pharmacovigilance Practices. European medicines Agency Available via Accessed March 1, Raine JM. Risk management - a European Regulatory View. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 19. de Langen J, van Hunsel F, Passier A, et al. Adverse drug reaction reporting by patients in the Netherlands: three years of experience. Drug Saf 2008; 31: van Hunsel F, Talsma A, van Puijenbroek E, et al. The proportion of patient reports of suspected ADRs to signal detection in the Netherlands: case-control study. Pharmacoepidemiol Drug Saf 2011; 20: Aagaard L, Nielsen LH, Hansen EH. Consumer reporting of adverse drug reactions: a retrospective analysis of the Danish adverse drug reaction database from 2004 to Drug Saf 2009; 32: Anderson C, Krska J, Murphy E, et al. The importance of direct patient reporting of suspected adverse drug reactions: a patient perspective. Br J Clin Pharmacol 2011; 72:

15 Introduction McLernon DJ, Bond CM, Hannaford PC, et al. Adverse drug reaction reporting in the UK: a retrospective observational comparison of yellow card reports submitted by patients and healthcare professionals. Drug Saf 2010; 33: Waller PC, Evans SJ. A model for the future conduct of pharmacovigilance. Pharmacoepidemiol Drug Saf 2003; 12: Harrison-Woolrych M, Coulter DM. PEM in New Zealand. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 26. Shakir SAW. PEM in the UK. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 27. De Koning, GHP. A Regionalized Spontaneous Surveillance Program for Adverse Drug Reactions as a Tool to Improve Pharmacotherapy, Thesis Utrecht University Meyboom, RHB. Detecting adverse drug reactions, pharmacovigilance in the Netherlands, Thesis Nijmegen University van Puijenbroek EP, Diemont W, van Grootheest K. Application of quantitative signal detection in the Dutch spontaneous reporting system for adverse drug reactions. Drug Saf 2003; 26: van Puijenbroek EP, van Grootheest K, Diemont WL, et al. Determinants of signal selection in a spontaneous reporting system for adverse drug reactions. Br J Clin Pharmacol 2001; 52: van Puijenbroek EP, Bate A, Leufkens HG, et al. A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions. Pharmacoepidemiol Drug Saf 2002; 11: van Puijenbroek EP, Egberts, ACG, Meyboom RHB, et al. Signalling possible drug-drug interactions in a spontaneous reporting system: delay of withdrawal bleeding during concomitant use of oral contraceptives and itraconazol. Br J Clin Pharmacol 1999; 47: van Puijenbroek EP. Quantitive Signal Detection in Pharmacovigilance, Thesis Utrecht University van Grootheest AC, van Puijenbroek EP, de Jong-van den Berg LT. Contribution of pharmacists to the reporting of adverse drug reactions. Pharmacoepidemiol Drug Saf 2002; 11: van Grootheest AC, Mes K, de Jong-van den Berg LTW. Attitudes of community pharmacists in the Netherlands towards adverse drug reaction reporting. Int J Pharm Pract 2002; 10: van Grootheest K, Olsson S, Couper M, et al. Pharmacists role in reporting adverse drug reactions in an international perspective. Pharmacoepidemiol Drug Saf 2004; 13: van Grootheest AC, de Jong-van den Berg LTW. The role of hospital and community pharmacists in pharmacovigilance. Res Social Adm Pharm 2005; 1: van Grootheest AC. Improving pharmacovigilance and the role of the pharmacist, Thesis Groningen University van Hunsel F. The contribution of direct patient reporting to pharmacovigilance, Thesis Groningen University van Puijenbroek EP, van Amerongen CA. [Is the first dispensation signal useful in postmarketing surveillance? Results from a pilot study] Pharm Weekbl 1996; 131: van Grootheest AC, Groote JK, de Jong-van den Berg LT. Intensive monitoring of new drugs based on first prescription signals from pharmacists: a pilot study. Pharmacoepidemiol Drug Saf 2003, 12: van Grootheest K, de Graaf L, de Jong-van den Berg LT. Consumer adverse drug reaction reporting: a new step in pharmacovigilance? Drug Saf 2003; 26: van Grootheest K, de Jong-van den Berg LT. Patients role in reporting adverse drug reactions. Expert Opin Drug Saf 2004; 3:

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17 Chapter 2 Pharmacovigilance and intensive monitoring

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19 Chapter 2.1 Pharmacovigilance: methods, recent developments and future perspectives Härmark L van Grootheest A.C European Journal of Clinical Pharmacology 2008; 64:

20 20 Chapter Abstract Background 4. Pharmacovigilance, defined by the World Health Organisation as the science and activities 5. relating to the detection, assessment, understanding and prevention of adverse effects or 6. any other drug-related problem plays a key role in ensuring that patients receive safe drugs. 7. Our knowledge of a drug s adverse reactions can be increased by various means, including 8. spontaneous reporting, intensive monitoring and database studies. New processes, both 9. at a regulatory and a scientific level, are being developed with the aim of strengthening 10. pharmacovigilance. On a regulatory level, these include conditional approval and risk management plans; on a scientific level, transparency and increased patient involvement are two important elements Objective 15. To review and discuss various aspects of pharmacovigilance, including new methodological 16. developments

21 Pharmacovigilance and intensive monitoring Introduction The field of drug safety has been receiving a great deal of attention lately. Almost weekly, 4. tabloids as well as scientific journals publish articles on drugs that cause unexpected adverse 5. drug reactions (ADRs). These articles have the unfortunate result of evoking apprehension 6. in both patients and health professionals regarding the use of these drugs. A more serious 7. consequence may be that the patient stops taking the prescribed medication, which may 8. lead to an even more serious situation than the ADR he was initially concerned about. Pharmacovigilance, defined by the World Health Organisation (WHO) as the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or 11. any other drug-related problem [1], plays a vital role in ensuring that doctors, together with 12. the patient, have enough information to make an educated decision when it comes to choosing a drug for treatment. The aim of this review is to provide a summary of the most common methods used in pharmacovigilance to guarantee the safety of a drug. Recent developments 15. in pharmacovigilance as well as future needs are discussed As an introduction to the sort of problems pharmacovigilance has to face, a few examples of 18. recent safety concerns and the action taken are briefly described Safety concerns 21. The withdrawal of rofecoxib directed renewed attention to drug safety. The decision to withdraw rofecoxib was made after the safety monitoring board of the APPROVe trial found an increased risk of cardiovascular (CV) events in patients treated with rofecoxib compared to 24. placebo [2]. The events leading to the withdrawal of rofecoxib, and what have happened since 25. the withdrawal, have been discussed in numerous papers [3-6]. Another association that has 26. been much debated the last year is the association between rosiglitazone and cardiac effects. 27. In June 2007 a meta-analysis was published wherein the use of rosiglitazone was linked to an 28. increased risk of myocardial infarction and death from cardiovascular causes [7]. The results 29. of this one meta-analysis kindled a growing debate on the safety of the drug [8-11], and 30. new studies were rapidly published with the aim of rejecting or confirming the results of 31. the first study [12,13]. Both the US Food and Drug Administration (FDA) and the European 32. Medicines Agency (EMEA) have now concluded that the benefits of rosiglitazone outweigh 33. its risks within the framework of its approved indications [14,15]. However, constant revision/ 34. updating of product information and a continued monitoring of this ADR are necessary A more recent safety concern is the association between aprotinin and increased mortality. In 2006, a study based on observational data was published by Mangano et al. in which 37. these authors questioned the safety of aprotinin [16]. On November 21, 2007, aprotinin was withdrawn from the market in the European Union based on data from the BART clinical 2

22 22 Chapter trial showing increased mortality for patients receiving aprotinin [17]. Table 1 provides an overview of recent major drug safety issues and the evidence that led to their discovery Table 1. Drug safety issues and their evidence in Europe since Drug Trovofloxacin Tolcapone Cisapride Safety concern Hepatoxicity Hepatoxicity QT prolongation Key evidence Spontaneous ADRs Spontaneous ADRs Spontaneous ADRs Regulatory action Withdrawn Suspended Patient registration 11. cardiac arrhythmias licences subsequently cancelled Bupropion Cerivastatin Hormone replace therapy Seizures Drug interaction Rhabdomyolysis CVS risk and cancer long term Spontaneous ADRs Spontaneous ADRs Epidemiological studies Posology change, Warnings Withdrawn Warnings and restriction of indication SSRIs Suicidal behaviour in Clinical trials Warnings accompanied by 20. children clinical guidance COX IIs CVS risk Clinical trials Warnings and clinical guidance Topical macrolide Risk of cancer Spontaneous reports Restriction of use, 25. immunosuppressants Risk management plan SSRI, selective serotonin reuptake inhibitors, CVS, cardiovascular safety, ADR, adverse drug reaction. From Pharmacovigilance; Risk Management- a European Regulatory View. J.M Raine. Copyright Copyright John Wiley & Sons Limited. Reproduced with permission Whenever a drug safety issue occurs, the first reaction is to search for a reason of why such a thing could happen. In the case of rofecoxib, this led to a critical evaluation of the current methods and mechanisms available for safeguarding the safe use of a drug Regulatory action after rofecoxib withdrawal In the aftermath of the withdrawal of rofecoxib, the FDA and the current system of postmarketing surveillance was heavily criticised on a number of points [18-23]. Firstly, the FDA uses only a limited number of data sources (clinical trials, spontaneous reporting) when it comes to assembling information on the safety of a drug. Secondly, the FDA has no control

23 Pharmacovigilance and intensive monitoring over the performance of post-marketing safety studies. The majority of post-marketing study 2. commitments are never initiated, and the proportion of post-marketing safety studies (phase 3. 4 studies) that were completed declined from 62% between 1970 and 1984 to 24% between and Thirdly, the FDA has no authority to take direct legal action against companies that do not fulfill their post-marketing commitments [24]. Some critics also claim that the FDA has become too close to the industry that they are supposed to regulate and that a 7. separation between regulatory duties and the post-marketing surveillance activities is desirable [21]. In response to the criticism, the Centre for Drug Administration (CDER) at the FDA asked the Institute of Medicine (IOM) to assess the US drug safety system. In September 2006, 10. the IOM released the committee s findings and recommendations in a report The future of 11. drug safety: promoting and protecting the health of the public [25]. The main message in 12. this report is that the FDA needs to follow the safety of a drug during its whole life cycle. This 13. life-cycle approach includes identifying safety signals, designing studies to confirm them, 14. evaluating benefits as well as risks, using risk-benefit assessments to integrate study results 15. and communicating key findings to patients and physicians [24,26] In Europe the withdrawal of rofecoxib led to an assessment of the pharmacovigilance system 18. in the different European Union member states, which was published in March The 19. report Assessment of the European Community System of Pharmacovigilance highlighted 20. the strengths and weaknesses of the European pharmacovigilance system. The report s 21. recommendations focused on the breadth and variety of data sources, the pro-active use 22. of registration, the speed of decision-making, the impact of regulatory action and communication, compliance by marketing authorisation holders and general principles of quality management and continuous quality improvement [27,28] Methods used in pharmacovigilance The activities undertaken in the name of pharmacovigilance can be roughly divided into 30. three groups: regulatory, industry, and academia. Regulatory pharmacovigilance is driven 31. by the aim to provide drugs with a positive benefit-harm profile to the public. Some of the 32. problems related to regulatory post-marketing surveillance will be discussed in this context, 33. followed by a description of the methods used to detect new ADRs and a discussion of the 34. pros and cons of each method Clinical trial data insufficient to evaluate drug risk 37. The main method currently used to gather information on a drug in the pre-marketing phase is to conduct a clinical trial. Pre-marketing clinical trials can be divided into three phases. Phase III studies are often double-blind randomised controlled trials; these are considered 2

24 24 Chapter to be the most rigorous approach to determining whether a cause-effect relationship exists 2. between a treatment and an outcome. However, when it comes to monitoring the safety of a 3. drug, this study design is not optimal. Due to the limited number of patients participating, it 4. is generally not possible to identify ADRs that occur only rarely. The relatively short duration 5. of clinical trials makes it difficult to detect ADRs with a long latency. Another limitation of 6. clinical trials is the population in which a drug is tested. The characteristics of the participants 7. do not always correspond to the characteristics of the population in which it will later be 8. used; consequently, it may be difficult to extrapolate the results obtained from clinical trials 9. to the population at large [29]. This is especially true for the elderly, for women or for people 10. belonging to a minority ethnic group [30,31]. In order to study rare ADRs, ADRs with a long latency and ADRs in specific populations, careful monitoring of the drug in the post-marketing phase is essential Post-marketing studies can be descriptive or analytical. Descriptive studies generate hypotheses and attempt to describe the occurrence of events related to drug toxicity and efficacy Analytical studies test hypotheses and seek to determine associations or causal connections 17. between observed effects and particular drugs, and to measure the size of these effects. 18. Descriptive studies are widely used in post-marketing surveillance because they are able to 19. generate hypotheses that will become starting points for analytical studies [32]. Two forms of 20. descriptive studies, spontaneous reporting and intensive monitoring, will be discussed here. 21. Analytical studies can be conducted using a variety of approaches, including case-control 22. studies, cohort studies and clinical trials. In order to be able to conduct retrospective cohort 23. and case-control studies, data which have been collected in a reliable and routine manner 24. needs to be available. To provide an example of such studies, we describe here two European 25. databases frequently used for analytical studies, the General Practitioners Research Database 26. (GPRD) in the UK and the PHARMO Record Linkage System in the Netherlands Spontaneous reporting 29. In 1961, a letter from the Australian physician WG McBride was published in Lancet. In this 30. letter, he shared his observation that babies whose mothers had used thalidomide during 31. pregnancy were born with congenital abnormalities more often than babies who had not 32. been exposed to thalidomide in utero [33]. In the years to come it became evident that 33. thousands of babies had been born with limb malformations due to the maternal use of 34. thalidomide. In order to prevent a similar disaster from occurring, systems were set up all over 35. the world with the aim of regulating and monitoring the safety of drugs Spontaneous reporting systems (SRS) were created, and these have become the primary method of collecting post-marketing information on the safety of drugs. The main function of SRS is the early detection of signals of new, rare and serious ADRs. A spontaneous reporting

25 Pharmacovigilance and intensive monitoring system enables physicians and, increasingly more often, pharmacists and patients to report 2. suspected ADRs to a pharmacovigilance centre [34-36]. The task of the pharmacovigilance 3. centre is to collect and analyse the reports and to inform stakeholders of the potential risk 4. when signals of new ADRs arise. Spontaneous reporting is also used by the pharmaceutical 5. industry to collect information about their drugs. By means of a SRS it is possible to monitor 6. all drugs on the market throughout their entire life cycle at a relatively low cost. The main 7. criticism of this approach is the potential for selective reporting and underreporting [37]. In a 8. review article, Hazell and Shakir investigated the magnitude of underreporting in SRS and determined that more than 94% of all ADRs remain unreported [38]. Underreporting can lead to the false conclusion that a real risk is absent, while selected reporting of suspected risks may 11. give a false impression of a risk that does not exist. However, underreporting and selective 12. reporting can also been seen as advantages. Because only the most severe and unexpected 13. cases are reported, it is easier to detect new signals of ADRs because the person reporting the 14. reaction has already pinpointed what may be a new safety issue. Against this background, 15. the system should perhaps be called concerned reporting instead of spontaneous reporting, 16. seeing as those reporting the issues are highly selective of what they are reporting [39]. With 17. a SRS, it is not possible to establish cause-effect relationships or accurate incidence rates; it 18. is also not possible to understand risk factors or elucidate patterns of use. Although critics 19. say that spontaneous reporting is not the ideal method for monitoring the safety of drugs, 20. it has proven its value throughout the years. Eleven products were withdrawn from the UK 21. and U.S. markets between 1999 and Randomised trial evidence was cited for two products (18%) and comparative observational studies for two products (18%). Evidence from spontaneous reports supported the withdrawal of eight products (73%), with four products 24. (36%) apparently withdrawn on the basis of spontaneous reports only. For two products, 25. the evidence used to support their withdrawal could not be found in any of the identified 26. documentation [40]. Of nine recent significant drug safety issues handled in the European 27. Union since 1995, six were detected by spontaneous reports, Table 1, which demonstrates 28. the strength of spontaneous reporting in detecting new safety issues [28] Data mining in spontaneous reporting 31. In the past, signal detection in spontaneous reporting has mainly occurred on the basis of 32. case-by-case analyses of reports. In recent years, however, data mining techniques have 33. become more important. The term data mining refers to the principle of analysing data 34. from different perspectives and extracting the relevant information. Algorithms are often 35. used to determine hidden patterns of associations or unexpected occurrences, i.e. signals, 36. in large databases. Although the methodology of the various data mining methods applied 37. in pharmacovigilance differ, they all share the characteristic that they express to what extent the number of observed cases differs from the number of expected cases [41]. 2

26 26 Chapter Several approaches of data mining are currently in use. Proportional reporting ratios (PPRs), 2. compare the proportion of reports for a specific ADR reported for a drug with the proportion 3. for that ADR in all other drugs. The calculation is analogous to that of relative risk. Using the 4. same information, it is also possible to calculate a reporting odds ratio [42] The Bayesian confidence propagation neural network (BCPNN) method is used to highlight 7. dependencies in a data set. This approach uses Bayesian statistics implemented in a neural 8. network architecture to analyse all reported ADR combinations. Quantitatively unexpectedly 9. strong relationships in the data are highlighted relative to general reporting of suspected 10. adverse effects. The WHO Collaborating Centre for International Drug Monitoring uses this 11. method for data mining [43]. A related approach is the Multi-Item Gamma Poisson Shrinker 12. (MGPS) used by the FDA for data mining of their spontaneous report s database. The MGPS 13. algorithm computes signal scores for pairs, and for higher-order (e.g. triplet, quadruplet) 14. combinations of drugs and events that are significantly more frequent than their pair-wise 15. associations would predict [44]. All data-mining approaches currently cannot distinguish 16. between associations that are already known and new associations. Moreover, clinical information described in the case reports is not taken into account; consequently, there is still the need for a reviewer to analyse these events Intensive monitoring 21. In the late 1970s and early 1980s a new form of active surveillance was developed in New 22. Zealand (Intensive Medicines Monitoring Programme) and the UK (Prescription Event 23. Monitoring). These intensive monitoring systems use prescription data to identify users of a 24. certain drug. The prescriber of the drug is asked about any adverse event occurring during 25. the use of the drug being monitored. These data are collected and analysed for new signals. 26. The methodology of these intensive monitoring systems have been described in depth 27. elsewhere [45-48] The basis of intensive monitoring is a non-interventional observational cohort, which distinguishes it from spontaneous reporting because the former only monitors selected drugs dur ing a certain period of time. Through its non-interventional character, intensive monitoring 32. provides real world clinical data involving neither inclusion nor exclusion criteria throughout 33. the collection period. It is unaffected by the kind of selection and exclusion criteria that characterise clinical trials, thereby eliminating selection bias. Another strength of the methodol ogy is that it is based upon event monitoring and is therefore capable of identifying signals 36. for events that were not necessarily suspected as being ADRs of the drug being studied. 37. Intensive monitoring programmes also enable the incidence of adverse events to be estimated, thus enabling quantification of the risk of certain ADRs. This approach, however, also has recognised limitations. The proportion of adverse effects that go unreported to doctors is

27 Pharmacovigilance and intensive monitoring unknown. The studies also produce reported event rates rather than true incident rates. This 2. is the same for all studies based on medical record data, including computer databases and 3. record linkage. There is no control group in standard intensive monitoring studies, and the 4. true background incidence for events is therefore not known [49] Although the intensive monitoring methodology was developed more than 20 years ago, 7. this methodology has received renewed interest in the last years. In the European Commission consultation Strategy to better protect public health by strengthening and rationalising EU pharmacovigilance intensive monitoring is mentioned as one tool that can improve the 10. pharmacovigilance system [50] Database studies 13. In order to test a hypothesis, a study has to be performed. The study can be conducted using a variety of methods, including case-control studies and cohort studies. The limitations of these methods include power considerations and study design. In order to be able to 16. conduct retrospective cohort and case-control studies, data which have been collected in a 17. reliable and routine fashion needs to be available. The General Practice Research Database 18. (GPRD) and the PHARMO Record Linkage System, which will be described in further detail 19. in the following sections, were chosen here because they represent two different types of 20. European databases. Other database and record linkage systems are available for research 21. purposes in both Europe and in North America [51] General Practice Research Database 24. Virtually all patient care in the UK is coordinated by the general practitioner (GP), and data 25. from this source provide an almost complete picture of a patient, his illnesses and treatment. 26. In any given year, GPs, who are members of the GPRD, collect data from about 3 million 27. patients (about 5% of the UK population). These patients are broadly representative of the 28. general UK population in terms of age, sex and geographic distribution. The data collected 29. include demographics (age and sex), medical diagnoses that are part of routine care or 30. resulting from hospitalisations, consultations or emergency care, along with the date and 31. location of the event. There is also an option of adding free text, referral to hospitals and 32. specialists, all prescriptions, including date of prescription, formulation strength, quantity 33. and dosing instructions, indication for treatment for all new prescriptions and events leading 34. to withdrawal of a drug or a treatment. Data on vaccinations and miscellaneous information, 35. such as smoking, height, weight, immunisations, pregnancy, birth, death, date entering the 36. practice, date leaving the practice and laboratory results, are also collected. 37. A recent review of protocols using GPRD data showed that the database is used for pharmacoepidemiology (56%), disease epidemiology (30%) and, to a lesser degree, drug utilisation, 2

28 28 Chapter pharmacoeconomics and environmental hazards. There have been over 250 publications in peer-reviewed journals using the GPRD [52-54]. PHARMO In the early 1990s, the PHARMO system of record linkage was developed in The Netherlands. PHARMO links community pharmacy and hospital data within a specific region on the basis of patient birth date, gender and GP code. The system now includes drug-dispensing records from community pharmacies and hospital discharge records of about 2 million people in the Netherlands. The data collection is longitudinal and goes back to More recently, PHARMO has also been linked to other data, such as primary care data, population surveys, laboratory and genetic data, cancer and accident registries, mortality data and economic outcomes. The system has well-defined denominator information that allows incidence and prevalence estimates and is relatively cheap because existing databases are used and linked. The PHARMO database is used for follow-up studies, case-control studies and other analytical epidemiological studies for evaluating drug-induced effects. In the past the database has been used for studies on drug utilisation, persistence with treatment, economic impact and ADRs [55,56]. Developments Pharmacovigilance and the methods used need to continue to develop in order to keep up with the demands of society. In recent years, three publications have been of utmost importance in terms of providing guidance on the future of pharmacovigilance. The first is the Erice Declaration on transparency, which was published in 1997 [57]. In this declaration, pharmacovigilance experts from all over the world, representing different sectors, emphasise the role of communication in drug safety with the following statements: Drug safety information must serve the health of the public Education in the appropriate use of drugs, including interpretation of safety information, is essential for the public at large, as well as for health care providers All the evidence needed to assess and understand risks and benefits must be openly available Every country needs a system with independent expertise to ensure that safety information on all available drugs is adequately collected, impartially evaluated and made accessible to all Innovation in drug safety monitoring needs to ensure that emerging problems are promptly recognised and efficiently dealt with, and that information and solutions are effectively communicated

29 Pharmacovigilance and intensive monitoring It is believed that these factors will help risks and benefits to be assessed, explained and acted upon openly and in a spirit that promotes general confidence and trust. This declaration was followed in 2007 by the Erice Manifesto for global reform of the safety of medicines in patient care [58]. The Erice Manifesto specifies the challenges which must be addressed to ensure the continuing development and usefulness of the science, in particular: The active involvement of patients and the public in the core debate about the risks and benefits of medicines, and in decisions about their own treatment and health The development of new ways of collecting, analyzing and communicating information about the safety and effectiveness of medicines; open discussion about it and the decisions which arise from it The pursuit of learning from other disciplines about how phamacovigilance methods can be improved, alongside wide-ranging professional, official and public collaboration The creation of purposeful, coordinated, worldwide support amongst politicians, officials, scientists, clinicians, patients and the general public, based on the demonstrable benefits of pharmacovigilance to public The third article that has had a profound impact on how pharmacovigilance should work in the future is the article published in 2002 by Waller and Evans in which they give their view on the future conduct of pharmacovigilance. The key values that should underpin pharmacovigilance are excellence (defined as the best possible result), the scientific method and transparency. The paper defines five elements that are considered to be essential for achieving excellence. Three of these are: process-oriented best evidence, robust scientific decision-making and effective tools to deliver protection of public health. The other two elements, scientific development and audit, underpin these processes, recognising that excellence cannot be achieved merely by process [59] International developments In the past, pharmacovigilance has been most concerned with finding new ADRs, but Waller and Evans suggest that pharmacovigilance should be less focused on finding harm and more focused on extending knowledge of safety [59]. In recent years, regulatory agencies have been reforming their systems in order to keep pace with the developments in pharmacovigilance, with the focus on being more pro-active Europe In 2005, a document was drafted by the Heads of the Medicines Agencies called Implementation of the Action Plan to Further Progress the European Risk Management Strategy. In July 2007, the EMEA published a document in which they discussed the achievements booked 2

30 30 Chapter to date. These achievements included the implementation of legal tools for monitoring the safety of medicines and for regulatory actions. Particular emphasis was placed on: Systematic implementation of risk management plans Strengthening the spontaneous reporting scheme through improvements of the Eudra- Vigilance database Launching the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP) project to strengthen the monitoring of medicinal products The conduct of multi-centre post authorisation safety studies Strengthening the organisation and the operation of the EU Pharmacovigilance system In the course of the next 2 years, two main areas will be covered by the European Risk Management Strategy: further improving of the operation of the EU Pharmacovigilance system and strengthening the science that underpins the safety monitoring for medicines for human use [60,61] In December 2007, a public consultation Strategy to Better Protect Public Health by Strengthening and Rationalising EU Pharmacovigilance was published on behalf of the European Commission. This document contains legislative strategy and key proposals for legislative changes within the European Union. Areas where legislative changes are needed include: fast and robust decision-making on safety issues, clarification of roles and responsibilities for industry and regulators, strengthening of the role of risk-management planning, improvement of the quality of non-interventional safety studies, simplification of ADR reporting, including introducing patient reporting, strengthening of medicine safety, transparency and communication, including clearer safety warnings in the product information to improve the safe use of medicines [50] The USA In the USA, the FDA has had a difficult time since the withdrawal of rofecoxib. The main concern is that the FDA is not able to protect the public from drug risks as efficiently as it might. In February 2007, on the basis of the IOM report, the FDA announced several initiatives designed to improve the safety of prescription drugs [26]. These initiatives fall into four main categories. The first is increasing the resources for drug safety activities. Perceiving the agency as being overly dependent on industry funding, some observers propose eliminating user fees. The second category of proposed reform is new authority for the FDA; the agency needs regulatory tools to help assure drug safety. This authority would be exercised through a required risk evaluation and mitigation strategy, including measures such as prescribing restrictions, limits on direct consumer marketing and requirements for post-marketing studies. The FDA could impose monetary penalties for non-compliance. A third aspect of the reform

31 Pharmacovigilance and intensive monitoring is the improvement of post-marketing surveillance. A routine systematic approach to active population-based drug surveillance that could identify potential safety problems is needed. Finally, changes in the FDA management practices and safety supervision are necessary [62] In May 2007, the U.S. senate passed its version of reform for the FDA. The senate proposed that the Prescription Drug User Fee Act, which allows the pharmaceutical industry to pay money directly to the FDA, should increase their payments to the FDA by close to U.S. 400 million dollars. Furthermore, this reform would give the FDA new authority to order companies to undertake formal safety studies of drugs that are being marketed and to fine those who do not honour their post-marketing commitments, however when it came to changing the structure of the FDA, the proposal to create an independent office for the monitoring of the safety of drugs was rejected by a majority of one vote [63-65] Methodological developments Transparency The Erice Declaration [57], as well as Waller and Evans [59], stated that transparency is important for the future of pharmacovigilance. In the last few years transparency around ADRs has increased. The registration of clinical trials will allow the necessary tracking of trials to ensure full and unbiased reporting for public benefit [66]. A number of countries, including Canada ( the Netherlands ( and the UK ( have made their databases containing the data from the spontaneous reporting system freely available to the public Conditional approval Both the FDA report and the report from the European Union described earlier emphasise that compliance by marketing authorisation holders needs to be improved when it comes to additional post-marketing studies. A possible solution to this problem would be a time-limited conditional approval, which would place pressure on the manufacturers to conduct and report additional safety studies [67]. Within the European Union, the EMEA has introduced a conditional marketing authorisation. The Committee for Medicinal Products for Human Use (CHMP) delivers a conditional marketing authorisation for products where there is a specific patient need. Examples include products for seriously debilitating or life-threatening diseases, medicinal products to be used in emergency situations in response to public threats and products designated as orphan medicinal products. A conditional marketing authorisation is granted in the absence of comprehensive clinical data referring to the safety and efficacy of the medicinal product. However, a number of criteria have to be met including: 1. A positive risk-benefit balance of the product 2

32 32 Chapter Likeliness that the applicant will be in a position to provide the comprehensive clinical data Unmet medical needs being fulfilled The benefit of the immediate availability of the medicinal product to public health outweighing the risk inherent in the absence of additional data Conditional marketing authorisations are valid for 1 year, on a renewable basis. The holder is required to complete ongoing studies or to conduct new studies with the objective of confirming that the risk-benefit balance is positive. In addition, specific obligations may be imposed in relation to the collection of pharmacovigilance data. The authorisation is not intended to remain conditional indefinitely. Rather, once the missing data are provided, it should be possible to replace it with a formal marketing authorisation. The granting of a conditional marketing authorisation will allow medicines to reach patients with unmet medical needs earlier than might otherwise be the case and will ensure that additional data on a product are generated, submitted, assessed and acted upon Risk management plans Another step in a more pro-active post-marketing surveillance is the introduction of risk management plans (RMPs) [68]. Such RMPs are being set up in order to identify, characterise, prevent or minimise risk relating to medicinal products, including the assessment of the effectiveness of those interventions. A RMP may need to be submitted at any time in a product s life cycle, for example, during both the pre-authorisation and post-authorisation phases. A RMP is required for all new active substances, significant changes in established products (e.g. new form/route of administration), established products introduced to new populations, significant new indications or when an unexpected hazard is identified The EU Risk Management Plan consists of two parts: the first part contains a safety specification and a pharmacovigilance plan and the second part contains an evaluation of the need for risk minimisation activities and, if necessary, a risk minimisation plan. The safety specification contains a summary of what is known and what is not known about the safety of the product. This specification encompasses the important identified risk and any information and outstanding safety questions which warrant further investigation in order to refine the understanding of benefit-risk during the post-authorisation period A risk minimisation plan is only required in circumstances where the standard information provision, by means of a medicine s summary of product characteristics, is considered inadequate. Insufficient patient information leaflets or inadequate labelling of the medicine are additional reasons for drawing up a risk minimisation plan. Where a risk minimisation plan is considered necessary, both routine and additional activities are to be included. Some

33 Pharmacovigilance and intensive monitoring safety concerns may have more than one risk minimisation activity, each of which should be 2. evaluated for effectiveness Many RMPs have already been established; however, to date, no quantitative or qualitative 5. reports have been released by the EMEA. Information to the public about RMPs has also been 6. scarce. If RMPs are to take an important place in pharmacovigilance, they need to be made 7. public and easily accessible to scientists, professionals and patients Involvement of patients 10. Another important development is the recognition of the patient as an important player 11. in pharmacovigilance. Patients are the users of drugs, and it is their use of a drug in a safe 12. manner that is the ultimate goal of pharmacovigilance activities. In an increasing number of 13. countries patients are now allowed to report ADRs to the spontaneous reporting system. The 14. European Commission acknowledges the role of the patient in spontaneous reporting [50]. 15. Patients and patient organisations are becoming increasingly more involved in pharmacovigilance, especially when it comes to risk communication [57,69] After introducing patient reporting in the spontaneous reporting scheme in 2004 [70], the 19. Netherlands Pharmacovigilance Centre Lareb took patient reporting one step further and 20. introduced, in 2006, an intensive monitoring programme using patients as a source of information. The Lareb Intensive Monitoring programme (LIM), follows the prescription-event monitoring methodology in that patients are identified on the basis of prescriptions. Eligible 23. patients are identified in their pharmacies when they come and pick up for the first time the 24. drug under study. Patients can register at the LIM website, and during a certain period of 25. time they will receive questionnaires asking them about adverse events. The system is totally 26. web-based; consequently, questionnaires can be sent via to participating patients at 27. different points, allowing the collection of longitudinal data. The high level of automation 28. also allows a rapid collection and analysis of data [71] Future perspectives On a regulatory level, progress has been made during the past few years. However, the results 34. of these changes have yet to become apparent and, therefore, it has not yet been proven 35. if these developments have contributed to better pharmacovigilance conduct. In order to 36. further prove pharmacovigilance as a science, it is essential that academia develops new 37. methods which can strengthen the current system. 2

34 34 Chapter Pharmacovigilance as we know it today has been about detecting new ADRs and, if necessary, taking regulatory actions needed to protect public health, for example, by changing the summary of product characteristics (SPCs) or withdrawing the drug from the market. Little 4. emphasis has been put into generating information that can assist a healthcare professional 5. or a patient in the decision-making process of whether of not to use a drug. The gathering 6. and communication of this information is an important goal of pharmacovigilance Active surveillance is necessary to receive information about the safety of a drug at an early 9. stage. When developing new methods for active post-marketing surveillance, one has to bear 10. in mind the importance of being able to gather information in a timely manner. Spontaneous 11. reporting has indeed been shown to be a useful tool in generating signals, but the relatively 12. low number of reports received for a specific association makes it less useful in identifying 13. patient characteristics and risk factors that will contribute to the occurrence of an ADR in a 14. certain person. This information is essential when it comes to a healthcare provider recommending whether or not a particular patient should use the drug in question. Furthermore, when facing an ADR, questions that patients as well as the treating physician can ask are: will 17. this ADR disappear?; how long will it take before it does?; what treatment is needed? None of the main methods used today in post-marketing surveillance can provide an answer 20. to these questions. It is therefore important to develop methods that can follow a patient using a particular drug over time, as the information gathered using such methods will enable such questions to be answered. Pharmacogenetics could play a role in identifying individual 23. risk factors for the occurrence of certain ADRs [72] The role of the patient is gradually changing. From being a person with little knowledge and 26. little power, the presentday patient is highly informed about his disease and wants to participate actively in his treatment. As mentioned earlier, in some countries the importance of patients as a source of information about ADRs has been acknowledged. In these countries, 29. patients have the option of reporting ADRs via the spontaneous reporting system. This patient empowerment will continue and, in the future, pharmacovigilance has to concentrate on this group as a source of information in addition to the more traditional groups, such as 32. the healthcare professionals The field of pharmacovigilance has made a tremendous journey since it was recognised in 35. the early 1960s after the thalidomide disaster. Recent events, such as the withdrawal of aprotinin and the questioning of the safety of rosiglitazone, show that it is a topic that lies close to people s hearts. In the past few years there has been a major push in trying to change the existing pharmacovigilance systems in order to meet the demands of the future. Scientific underpinning of pharmacovigilance is needed to ensure that it will develop as a scientific

35 Pharmacovigilance and intensive monitoring discipline and thereby contribute to the innovation needed in this field. The pharmacovigilance of tomorrow must be able to identify new safety issues without delay. If we succeed herein, patient s confidence in drugs will return. Furthermore, pharmacovigilance methods 4. must also be able to describe which patients are at risk of developing an ADR and what the 5. course of the ADR is. One approach to doing this would be to use patients, more than has 6. been done up to now, as a source of information; this approach would be consistent with the 7. growing patient involvement in drug safety

36 36 Chapter References 1. The Importance of Pharmacovigilance. WHO Available via Accessed Dec Bresalier RS, Sandler RS, Quan H, et al. Cardiovascular events associated with rofecoxib in a colorectal adenoma chemoprevention trial. N Engl J Med 2005; 352: Topol EJ. Failing the public health--rofecoxib, Merck, and the FDA. N Engl J Med 2004; 351: Horton R. Vioxx, the implosion of Merck, and aftershocks at the FDA. Lancet 2004; 364: Hampton T. Experts point to lessons learned from controversy over rofecoxib safety. JAMA 2005; 293: Krumholz HM, Ross JS, Presler AH, et al. What have we learnt from Vioxx? BMJ 2007; 334: Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes. N Engl J Med 2007; 356: Solomon DH, Winkelmayer WC. Cardiovascular risk and the thiazolidinediones: deja vu all over again? JAMA 2007; 298: Hampton T. MI risks linked to rosiglitazone. JAMA 2007; 298: Rosen CJ. The rosiglitazone story--lessons from an FDA Advisory Committee meeting. N Engl J Med 2007; 357: Krall RL. Cardiovascular safety of rosiglitazone. Lancet 2007; 369: Singh S, Loke YK, Furberg CD. Long-term risk of cardiovascular events with rosiglitazone: a metaanalysis. JAMA 2007; 298: Home PD, Pocock SJ, Beck-Nielsen H, et al. Rosiglitazone evaluated for cardiovascular outcomes- -an interim analysis. N Engl J Med 2007; 357: European Medicines Agency confirms positive benefit-risk balance for rosiglitazone and pioglitazone. European Medicines Agency Available via human/press/pr/ en.pdf Accessed Oct Information for Healthcare Professionals Rosiglitazone maleate (marketed as Avandia, Avandamet, and Avandaryl). FDA Available via rosiglitazone200707hcp.htm. Accessed Nov Mangano DT, Tudor IC, Dietzel C. The risk associated with aprotinin in cardiac surgery. N Engl J Med 2006; 354: European Medicines Agency recommends suspension for marketing authorisation of aprotinincontaining medicines for systemic use. European Medicines Agency Available via Accessed Feb Mitka M. Report criticizes lack of FDA oversight. JAMA 2006; 296: Lenzer J. FDA is incapable of protecting US against another Vioxx. BMJ 2004; 329: Ray WA, Stein CM. Reform of drug regulation--beyond an independent drug-safety board. N Engl J Med 2006; 354: Furberg CD, Levin AA, Gross PA, et al. The FDA and drug safety: a proposal for sweeping changes. Arch Intern Med 2006; 166: Avorn J. Paying for drug approvals--who s using whom? N Engl J Med 2007; 356: Strom BL. How the US drug safety system should be changed. JAMA 2006; 295: Psaty BM, Charo RA. FDA responds to institute of medicine drug safety recommendations--in part. JAMA 2007; 297: Baciu A, Stratton K, Burke SP, editors. Committee on the Assessment of the US Drug Safety System The future of drug safety: promoting and protecting the health of the public. Institute of Medicine Washington DC.

37 Pharmacovigilance and intensive monitoring Psaty BM, Burke SP. Protecting the health of the public--institute of Medicine recommendations on drug safety. N Engl J Med 2006; 355: Assessment of the European Community System of Pharmacovigilance. European Medicines Agency Available via Accessed Dec Raine JM. Risk management - a European Regulatory View. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 29. Gross CP, Mallory R, Heiat A, et al. Reporting the recruitment process in clinical trials: who are these patients and how did they get there? Ann Intern Med 2002; 137: Heiat A, Gross CP, Krumholz HM. Representation of the elderly, women, and minorities in heart failure clinical trials. Arch Intern Med 2002; 162: Zarin DA, Young JL, West JC. Challenges to evidence-based medicine: a comparison of patients and treatments in randomized controlled trials with patients and treatments in a practice research network. Soc Psychiatry Psychiatr Epidemiol 2005; 40: Wardell WM, Tsianco MC, Anavekar SN, et al. Postmarketing surveillance of new drugs: I. Review of objectives and methodology. J Clin Pharmacol 1979; 19: McBride WG. Thalidomide and congenital malformations. Lancet 1961; 2: van Grootheest K, Olsson S, Couper M, et al. Pharmacists role in reporting adverse drug reactions in an international perspective. Pharmacoepidemiol Drug Saf 2004; 13: van Grootheest K, de Jong-van den Berg L. Patients role in reporting adverse drug reactions. Expert Opin Drug Saf 2004; 3: van Grootheest AC, Passier JL, van Puijenbroek EP. [Direct reporting of side effects by the patient: favourable experience in the first year]. Ned Tijdschr Geneeskd 2005; 149: Eland IA, Belton KJ, van Grootheest AC, et al. Attitudinal survey of voluntary reporting of adverse drug reactions. Br J Clin Pharmacol 1999; 48: Hazell L, Shakir SA. Under-reporting of adverse drug reactions : a systematic review. Drug Saf 2006; 29: Edwards IR. Spontaneous reporting--of what? Clinical concerns about drugs. Br J Clin Pharmacol 1999; 48: Clarke A, Deeks JJ, Shakir SA. An assessment of the publicly disseminated evidence of safety used in decisions to withdraw medicinal products from the UK and US markets. Drug Saf 2006; 29: Hauben M, Madigan D, Gerrits CM, et al. The role of data mining in pharmacovigilance. Expert Opin Drug Saf 2005; 4: van Puijenbroek E, Diemont W, van Grootheest K. Application of quantitative signal detection in the Dutch spontaneous reporting system for adverse drug reactions. Drug Saf 2003; 26: Bate A, Lindquist M, Edwards IR, et al. A data mining approach for signal detection and analysis. Drug Saf 2002; 25: Szarfman A, Machado SG, O Neill RT. Use of screening algorithms and computer systems to efficiently signal higher-than-expected combinations of drugs and events in the US FDA s spontaneous reports database. Drug Saf 2002; 25: Mackay FJ. Post-marketing studies: the work of the Drug Safety Research Unit. Drug Saf 1998; 19: Mann RD. Prescription-event monitoring--recent progress and future horizons. Br J Clin Pharmacol 1998; 46: Coulter DM. The New Zealand Intensive Medicines Monitoring Programme. Pharmacoepidemiol Drug Saf 1998; 7: Coulter DM. The New Zealand Intensive Medicines Monitoring Programme in Pro-active Safety Surveillance. Pharmacoepidemiology and Drug Safety 2000; 9:

38 38 Chapter Shakir SAW. PEM in the UK. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 50. Strategy to better protect public health by strengthening and rationalising EU pharmacovigilance. European Commission Enterprise and Industry Directorate-general Brussels. 51. Strom BL (ed). Pharmacoepidemiology. 4th edn Wiley, Chichester. 52. Gelfand JM, Margolis DJ, Dattani H. The UK General Practice Research Database. In: Strom BL (ed) Pharmacoepidemiology. 4th edn Wiley, Chichester. 53. Parkinson J, Davies S, van Staa T. The General Practice Research Database: Now and the Future. In: Mann R, Andrews E (eds) Pharmacovigilance nd edn. Wiley, Chichester. 54. Wood L, Martinez C. The general practice research database: role in pharmacovigilance. Drug Saf 2004; 27: Leufkens HG, Urquhart J. Automated Pharmacy Record Linkage in the Netherlands. In: Strom BL (ed) Pharmacoepidemiology. 4th edn Wiley, Chichester. 56. Sturkenboom MCJM. Other databases in Europe for the Analytic Evaluation of Drug Effects. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 57. Hugman B. The Erice declaration : the critical role of communication in drug safety. Drug Saf 2006; 29: Adis International. The Erice Manifesto: for global reform of the safety of medicines in patient care. Drug Saf 2007; 30: Waller PC, Evans SJ. A model for the future conduct of pharmacovigilance. Pharmacoepidemiol Drug Saf 2003; 12: European Risk management Strategy: Achievements to date. European Medicines Agency Available via Accessed Dec Status Report on the Implementation of the European Risk management Strategy. European Medicines Agency Available via Accessed Dec 18, McClellan M. Drug safety reform at the FDA-pendulum swing or systematic improvement? N Engl J Med 2007; 356: Coombes R. FDA tightens its grip on drug regulation. BMJ 2007; 334: Zwillich T. US lawmakers tackle safety reforms at the FDA. Lancet 2007; 369: Hennessy S, Strom BL. PDUFA reauthorization-drug safety s golden moment of opportunity? N Engl J Med 2007; 356: Sim I, Chan AW, Gulmezoglu AM, et al. Clinical trial registration: transparency is the watchword. Lancet 2006; 367: Human Medicines - EMEA Pre-Submission Guidance. European Medicines Agency Available via Accessed Dec 18, Guideline on Risk management Systems for Medicinal Products for Human Use. European Medicines Agency Available via pdf Accessed Dec 18, van Grootheest K, de Graaf L, de Jong-van den Berg LT Consumer adverse drug reaction reporting: a new step in pharmacovigilance? Drug Saf 2003; 26: de Langen J, van Hunsel F, Passier A, et al. Three Years of Experience with ADR Reporting by Patients in the Netherlands. [In Press] Drug Saf Härmark L, Kabel JS, van Puijenbroek EP, et al. Web-Based Intensive Monitoring, a New Patient Based Tool for Early signal Detection. [Abstract] Drug Saf 2006; 29: Pirmohamed M, Park BK. Genetic susceptibility to adverse drug reactions. Trends Pharmacol Sci 2001; 22:

39 Chapter 3 Patients as a source of information in web-based intensive monitoring

40

41 Chapter 3.1 Patients motives for participating in active post marketing surveillance Härmark L Lie-Kwie M Berm L de Gier H van Grootheest K Accepted for publication in Pharmacoepidemiology and Drug Safety

42 42 Chapter Abstract Purpose 4. Web-based intensive monitoring is a method used to actively collect information about 5. adverse drug reactions using patients as a source of information. To date little is known 6. about patients motivation to participate in this kind of active post-marketing surveillance, 7. (PMS). Increased insight in this matter can help us to better understand and interpret patient reported information and it can be used for developing and improving patient based pharmacovigilance tools. The aim of this study is to gain insight into patients motives for 10. participating in active PMS and investigate their experiences with such a system Method 13. A mixed model approach combining qualitative and quantitave research methods was used. 14. For both parts, patients participating in a web-based intensive monitoring study about the 15. safety of anti-diabetic drugs (excluding insulines) were used. A questionnaire was developed 16. based on the results from qualitative interviews. The data collected through the questionnaires was analysed with descriptive statistics. Relations between patient characteristics and motives were analysed using a t-test or a Chi-squared test Results (54.6%) patients responded to the questionnaire. The main motive for participation was 22. altruism. Often experiencing ADRs or negative experiences with drugs were not important 23. motives. The patient s gender played a role in the different motives for participation, for men 24. having benefit from the results was more important than for women. The overall opinion 25. about the system was positive Conclusion 28. The knowledge that patients participate in this kind of research from an altruistic point of 29. view will strengthen patient involvement in pharmacovigilance

43 Patients as a source of information Introduction Patients have become important players in pharmacovigilance. Some countries have accepted patient reports to their spontaneous reporting systems for a long time and the ex periences so far are favorable [1-3]. Recent studies show that patient reports also contribute 6. significantly to signal detection [4]. In addition, patient reports give a new perspective on 7. adverse drug reactions (ADRs) [5,6]. The new European pharmacovigilance legislation [7,8] 8. which will come into force mid-2012 also accentuates the growing importance of patients in 9. pharmacovigilance. Patients will be represented in the Pharmacovigilance Risk Assessment 10. Committee (PRAC), the highest administrative body concerning pharmacovigilance issues 11. within the European Medicines Agency (EMA). In addition, all countries will be obliged to 12. introduce patient reporting to their spontaneous reporting systems. The reporting will be 13. promoted by including a reference in the patient information leaflet to where patients can 14. report ADRs [9,10] In 2006 the Netherlands Pharmacovigilance Centre Lareb, which is responsible for the spontaneous reporting system in the Netherlands, started its Lareb Intensive Monitoring (LIM) system as a complement to their spontaneous reporting system. LIM is a non-interventional 19. observational cohort study, using patients as a source of information. Patients are identified 20. in their pharmacy when a drug under study is dispensed for the first time. Patients are asked 21. by the pharmacist to participate with LIM. After online registration, the patient will receive 22. electronic questionnaires by , containing questions about patient characteristics, drug 23. use and ADRs. The LIM methodology has been described more in depth earlier [11-13] Patients motivation to report to a spontaneous reporting system has been previously investigated [14]. However, to date little is known about patients motivation to participate in active post-marketing surveillance (PMS) systems such as LIM. Increased insight into patients 28. motives for participating can help us to better understand and interpret patient reported 29. information. Increased knowledge about patients motives for participation can also be used 30. for developing and improving patient-based pharmacovigilance tools. The aim of this study 31. is to gain insight into patients motives for participating in active post-marketing surveillance 32. and investigate their experiences with the system using a mixed model approach [15]

44 44 Chapter Method Mixed model design A mixed model approach combining qualitative and quantitave research methods was used. Qualitative interviews were used as a basis for the questionnaire to assure the internal validity Patients, aged 18 years and older, who participated in the LIM diabetes study and had completed the first questionnaire were eligible for inclusion. Participant recruitment was continued until an informational saturation point was reached [16], which lead to an inclusion period of 3 months (between September 1 and December ). Eligible patients were sent an invitation letter and if they were willing to participate, they were contacted via telephone by one of the researchers (ML) and an appointment for the interview was made. Written informed consent was obtained from all participants prior to the interview. No form of compensation was provided. The research plan was submitted to the Medical Ethics Committee (METC) for approval. No approval was needed In total 21 patients were interviewed, 62% of the interviewees were male and the average age was 61 years. The interviews, except one, were carried out by two researchers. During the interviews one researcher acted as main inquirer, the other as observer. The interviews were structured by using an interview guide. The interview guide was specifically constructed for this study. In developing the interview guide the main research questions were divided into themes and subthemes. The themes subsequently formed the interview topics, see Table 1. The themes and subthemes were consequently translated to truly open questions Table 1. Topics covered by the interview guide. The topics are placed in order of appearance in the interview guide Number 1 2 Topic Introduction personal information Patient s explanation / perception of LIM 3 Contact with pharmacy staff during the request to participate with LIM Other information sources for/on LIM Attitudes towards (other) commercial and non-commercial research Motives for participating with LIM Experience with the LIM study Experience of LIM with PC (pros and cons) How to motivate other patients to participate with LIM Advice to other patients who consider participating with LIM

45 Patients as a source of information The guide was reviewed between interviews, ensuring that topics that were not included but were relevant for the aim of the study, were also discussed during the following interview. All interviews were held at the patient s home in their mother tongue Dutch and lasted between twenty-five and forty-five minutes. The interviews were recorded and notes were taken concurrently. The interviews were transcribed verbatim and Nvivo SP3 software for qualitative research (QSR international, Melbourne Australia) was used to assist with the coding, sorting and retrieval of the data In the interview transcripts, continuous portions of text with some apparent coherence about one clear subject were identified and given a code. Eight interviews were open coded by two researchers independently (ML and LH or EB). Coding was compared and discussed to resolve any differences. The codes were organised into three coding schemes and the codes where thereafter categorised/grouped into a coding set. Coding of all data according to the coding set was performed by one of the researchers (ML). In order to ensure a uniform analysis of the data four interviews were randomly selected for duplo coding by another researcher (LH) and the coded interviews were compared and discussed by the two researchers. From the interviews patients motives for participation and patients experiences with LIM were identified. The reported motives for participating, together with illustrative patient quotes, are described in Table Table 2. Quotations from interviewees concerning motives for participating. 21. Motives Quotations 22. Altruistic Others Help knowledge Pharmacy s request Fear about negative effects of drugs It s always good for other people too. If you can help with it. You should do it. To pass on my knowledge, the science to you. I think it is important to pass things on, and again, for the sake of new drug. Just because the pharmacist handed over the folder. To know if the new drug will cooperate with my other medicines, because I use so many other drugs I think it is important admission. You do get shocked from something like that and you than wonder, about how important it is that lots of information is available on specific drugs. Personal experience/ Because I think this is pretty important. I once had penicillin, and all of a sudden discomfort I had a anaphylactic shock, that was a very intense, which resulted in a hospital Egoistic motives They cannot do enough research and it s me that will benefit, on the first place it s a bit egoistic The results from the interviews were used to design a questionnaire in Dutch. In the questionnaire, statements were formulated concerning Motives and Experiences. The Motives part consisted of possible reasons which might have influenced a patient s decision to participate in LIM. The Experiences part contained statements relating to the LIM questionnaire and its user-friendliness. A five point Likert scale with the options: strongly disagree, disagree, 3

46 46 Chapter neutral, agree and strongly agree were used as answer options. To ensure that no important 2. motive was missed, an open question was added to the questionnaire. The questionnaire also 3. contained questions relating to the patient demographics (gender and birth date), level of 4. education and questions relating to their LIM participation such as when they registered for 5. LIM (year), the number of questionnaires filled in the LIM study and if they had experienced 6. any adverse drug reactions while participating in the LIM study The web-based questionnaire was designed using the software Survey Monkey [17], adding 9. logic to the questions. A person was only asked questions relevant to his or her situation, 10. for example, if the patient had not filled in any LIM questionnaires, the questions regarding 11. experiences with the questionnaires were not asked. All questions were made mandatory, 12. except for the open question, to enhance data completeness. Before sending, the questionnaire was tested by a panel consisting of 10 persons of different age and education level The comments made resulted in adjustments of the final questionnaire. The letter type was 15. increased for more easy reading, explanatory text was highlighted and made red so it would 16. be more visible and the questionnaire was divided into more pages so that each page would 17. contain less information and be easier to read Study population 20. All patients who registered for the LIM diabetes study between February 1, 2008 and October , 2010 were eligible for participating in the quantitative study. The questionnaire was sent 22. on October 28, 2010 by . The link in the invitation was uniquely tied to the 23. survey and the respondent s address, making sure each questionnaire could only be 24. filled in once. After 10 days a reminder was sent to the patients who had not yet responded. 25. Four weeks after sending the initial questionnaire, the collection of responses was finished Data analysis 28. Descriptive statistic was used to get an overview of the patient characteristics, the additional 29. information asked about their LIM participation and the experiences and motives. The age 30. was categorised in age categories used by the Dutch National Institute for Public Health 31. and the Environment for categorising type 2 diabetes mellitus patients [18]. A Pearson s Chisquared test was performed to detect statistical significant differences in patient motives for participating in LIM between men and women and between motives and the year in which 34. the participants signed up for LIM. If a statistically significant difference was found, the frequencies of the distribution were calculated to give an understanding of the difference. Dif ferences between responders and non-responders to this questionnaire were investigated. 37. Differences in patient characteristics such as age, gender and having experienced an ADR, were addressed using additional data from the LIM database. To test if there was a statistically significant difference between continuous variables, a t-test was performed, for differences

47 Patients as a source of information between nominal variables a Chi-squared test was used. The responses to the open question were independently categorised by two researchers (LB and LH) independently and later combined and compared to see if new motives were mentioned. MS Access 2000 was used for data retrieval. Statistical analyses were performed using SPSS for Windows version P-values equal or below 0.05 were considered statistically significant. Results Response For the study a list of 2688 eligible patients was derived from the LIM database. The response rate was 54.6%, for further details see Figure 1. Figure 1. Response rate questionnaire Filtering out duplicates and test addresses 12 adresses blocked in software 169 bounced/undelivered 7 unable to answer 2688 patients addresses in LIM database 2625 unique addresses s sent 2437 potential responders 1332 responders 1105 non-responders 3

48 48 Chapter Descriptive statistics 2. The patient characteristics are listed in Table 3. An overview of the responses on the motives for participating in LIM are given in Table 4. The main motives for participating with LIM ( agree or strongly agree are presented together) were: Other patients can be treated better 5. (89%) and I want to help healthcare workers (84%) Table 3. Patient characteristics and information about their LIM participation, the most frequently given 8. answer is bold. 9. Variable Percentage % (n) 10. Gender 11. Women 40.5 (545) Man 59.5 (787) 12. Education level 13. Primary school 6.8 (90) 14. Secondary school 23.7 (316) 15. Vocational education 6 (527) Higher professional education 23.8 (317) 16. Academic 6. 2 (82) 17. Start year LIM* (285) (392) (423) 20. Unknown 16.7 (221) 21. * 1321 responses, 11 missing 22. Number of questionnaires completed (40) (114) (208) (263) (155) (74) (81) 28. Unknown 29.8 (397) 29. Reported an ADR* 30. Yes 37.6 (486) No 62.4 (807) 31. *1293 responses, 39 skipped 32. Age* (2) (1) (101) (804) (373) (50) *1331 responses, 1 invalid

49 Patients as a source of information 49 Table 4. Motives for participating with LIM, the most frequently given answer is bold. 1. Strongly Disagree Neutral % (n) Agree % (n) Strongly 2. Motive disagree % (n) agree % (n) I want to help healthcare workers. I often experience adverse drug reactions. There is not enough knowledge about adverse drug reactions. The pharmacist (assistant) asked me to participate. I am worried about the safety of new drugs. I find it interesting to learn more about adverse drug reactions. Other patients can be treated better. I am worried about drug interactions. I will benefit from it myself later. % (n) 1.1 (15) 8.9 (119) 1.8 (24) 5.2 (69) 2.9 (39) 1.0 (13) 0.7 (9) 2.1 (28) 0.6 (8) 1.5 (20) 47.7 (635) 11.3 (150) 17.0 (227) 25.4 (338) 5.6 (75) 0.8 (10) 21.2 (283) 2.3 (30) 13.0 (173) 23.3 (310) 44.4 (591) 12.5 (166) 42.1 (561) 23.9 (318) 9.2 (122) 4 (511) 22.1 (295) 70.8 (943) 17.9 (238) 0 (506) 54.4 (725) 26.2 (349) 58.6 (780) 68.2 (908) 32.8 (437) 63.5 (846) 13.6 (181) 2.3 (30) 4.6 (61) 10.9 (145) 3.4 (45) 11.0 (146) 21.2 (283) 5.5 (73) 11.5 (153) 22. I have had bad experiences with previous 10.5 (140) 44.6 (594) 22.5 (300) 17.5 (233) 4.9 (65) drug use I want to learn more about the drug I am using. 1.1 (15) 5.6 (75) 33.4 (445) 51.1 (680) 8.8 (117) 26. Lareb Monitor directly contributes to the 27. safety of the drugs I use (8) 2.0 (26) 32.5 (443) 54.7 (728) 10.3 (137) patients responded to the open question. The motive for participating which was most frequently mentioned (18 times) was To help gain more (scientific) information about ADRs. Apparently this subject was not completely covered by the statement There is not enough knowledge about adverse drug reactions, which was in the questionnaire. New motives/statements mentioned were I have become diabetic (4 times), I am using a medicine which is new on the market (4 times) and I am a health care worker (3 times). Motives which were already in the questionnaire or modification thereof where also mentioned. Patients also used the open text field to give comments on the questionnaire or healthcare in general (17 times). 3

50 50 Chapter An overview of the experiences with LIM are given in Table 5. The questions which are asked are understandable (83%), the majority (78%), thinks it is easy to participate. Only 10.5% of the patients finds it time consuming to complete the questionnaires and less than 5% of the participants is concerned about the confidentiality after providing their information Table 5. Experiences with LIM, the most frequently given answer is bold. Experience disagree Strongly % (n) Disagree agree % (n) Neutral % (n) Agree % (n) Strongly % (n) Completing the questionnaires takes too much time. The questions asked are understandable. I had trouble finding the drug s RVG number. The questions could be formulated better. 9.5 (123) 2.2 (29) 6.7 (86) 4.8 (62) 46.3 (599) 2.6 (33) 37.4 (484) 40.8 (528) 33.6 (435) 12.3 (159) 22.6 (292) 44.7 (578) 9.0 (117) 70.8 (915) 26.8 (346) 8.6 (111) 1.5 (19) 12.1 (157) 6.6 (85) 1.1 (14) After completing a LIM questionnaire I 6.7 (86) 25.2 (326) 26.6 (344) 33.1 (428) 8.4 (109) 17. would like to receive a copy I am convinced that the privacy of the information I send is guaranteed. 2.1 (27) 2.6 (34) 30.5 (395) 55.1 (712) 9.7 (125) I find it difficult to fill in online 19.5 (252) 58.7 (759) 15.2 (197) 5.2 (67) 1.4 (18) 22. questionnaires LIM participation is easy. Differences in motives 2.0 (26) 2.3 (30) 17.7 (229) 66.2 (856) 11.8 (152) In seven of the motives for participating in LIM, there are differences between men and women. The motives I often experience adverse drug reactions, I am worried about drug interactions, The pharmacist (assistant) asked me to participate and Other patients can be treated better were more important motives for participation for women than men. For men, having benefit from the results was more important than to women. On two items There is not enough knowledge about adverse drug reactions and I am worried about the safety of new drugs there were significant differences between men and women, but the data did not give a clear picture if women were more concerned about these items compared to men or vice versa. There were no statistically significant differences in motives between patients who signed up for the LIM study in different years, except for The pharmacist (assistant) asked me to participate (p < 0.001). For patients who recently started with LIM, this was a more important motive than for patients who started with LIM a long time ago.

51 Patients as a source of information Non-response 2. In total there were 1105 non-responders (including 135 partial responders). Twelve 3. addresses which were blocked in Survey Monkey were unknown and could not be excluded 4. from the non-responders and these had to be counted as non-responders, resulting in non-responders Differences between responders and non-responders to this questionnaire were investigated 8. using data from the LIM database. There were no statistical significant difference in gender 9. distribution (Chi-squared test p= 0.393) or age (t-test p= 0.402). There was a statistically 10. significant difference in reporting an ADR between responders and non-responders (Chisquared test p < 0.001). Responders to the questionnaire reported more ADRs compared to non-responders Discussion In this study patients motives for participating in a web-based intensive monitoring system 18. as well as their experiences with this system were investigated, using a mixed model research 19. approach. The main motives for participation can be classified as altruistic reasons and 20. because the pharmacist asked them to register. Often experiencing ADRs or other negative 21. experiences with drugs are not important as motivation; however among the responders 22. to the questionnaire a bigger proportion of the patients had experienced an adverse drug 23. reaction as compared to the non-responders (38% vs 27%). The patient s gender plays a role 24. in the motivation for participation. The overall opinion about the LIM system is very positive; 25. completing the surveys with the computer seems to be easy. The only negative feedback 26. about LIM was the question about the drug identification number (RVG-number). Patients 27. found it difficult to identify this number on the medicine boxes The statements in the questionnaire were based on the results from the qualitative interviews 30. in order to increase the internal validity of the questionnaire [15]. The open question at the 31. end identified three new motives/statements, however these were only mentioned by less 32. than 5 patients per motive/statement and are probably no main motives, indicating a high 33. internal validity On three of the statements relating to the motives for participation, the highest frequency 36. was in the neutral group. These motives might not have been relevant for patients, or the formulation of the motive was too abstract to make a distinction between agree and disagree. 37. Statement formulated in a negative way also yielded a high proportion of neutral responses. 3

52 52 Chapter The questionnaire was sent to all patients who had signed up for the LIM study during the 2. inclusion period. This means that some patients had already finished their LIM participation 3. at the moment they received the questionnaire and other patients had just started. Patients 4. who took the decision to participate years ago might not remember their motives for participation, leading to recall bias. Analysis showed that the only motive that was influenced by the start year was The pharmacist (assistant) asked me to participate The characteristics of the patients who responded to the questionnaire do not differ from 9. the non-responders. In addition they are similar to the Dutch diabetes population concerning gender and age [18] and similar to the Dutch population concerning education level [19]. There was a difference in reporting an ADR between responders and non-responders. 12. Patients who reported an ADR are probably more willing to complete an additional questionnaire, because they might feel more involved in LIM. This might have influenced the results of the motive I often experience ADR s, however this was not a main motive. Even though the 15. responders and the non-responders did not differ in age and gender, it is possible that they 16. differ in their experiences and opinions about LIM. Non-responders might for example find 17. it difficult to answer web-based questionnaires or have a more negative attitude to LIM, and 18. therefore not answer it. This might have led to more positive results concerning the experience about LIM The main limitation of this study is that patients motives for participation have only been 22. investigated in a cohort of patients who have registered for a study about anti-diabetic 23. medication. However, it is not to be expected that the motives would be different for patients 24. participating in studies where other drugs are investigated. For all drugs the information 25. about the study, the aim and possible gain from the study, is identical In the past there has been a debate in pharmacovigilance whether patients can provide reliable information about their drug use and possible adverse drug reactions. Critical voices issued their concerns that patient would use their role in pharmacovigilance to represent the 30. views of special interest groups and become strong lobbies easily manipulated by interested 31. parties [20,21]. If this would be the case, one would get a very biased view of drugs and 32. its adverse drug reactions when using patients as a source of information. This study has 33. shown that patients do not participate in an active pharmacovigilance system because of 34. these reasons. Patients have an honest interest in participating in this kind of research, where 35. the feeling of doing something good for others (altruism) is the most important motive. This 36. study shows that patients are prepared to give their time in order to contribute to additional 37. information about the safety of drugs.

53 Patients as a source of information Conclusion Active and independent post-marketing surveillance is important and patients will play 4. an even bigger role herein in the near future. The knowledge that patients participate in 5. this kind of research from an altruistic point of view will strengthen patient involvement in 6. pharmacovigilance

54 54 Chapter Reference list 1. de Langen J, van Hunsel F, Passier A, et al. Adverse drug reaction reporting by patients in the Netherlands: three years of experience. Drug Saf 2008; 31: Aagaard L, Nielsen LH, Hansen EH. Consumer reporting of adverse drug reactions: a retrospective analysis of the Danish adverse drug reaction database from 2004 to Drug Saf 2009; 32: McLernon DJ, Bond CM, Hannaford PC, et al. Adverse drug reaction reporting in the UK: a retrospective observational comparison of yellow card reports submitted by patients and healthcare professionals. Drug Saf 2010; 33: van Hunsel F, Talsma A, van Puijenbroek E, et al. The proportion of patient reports of suspected ADRs to signal detection in the Netherlands: case-control study. Pharmacoepidemiol Drug Saf 2011; 20: Basch E. The missing voice of patients in drug-safety reporting. N Engl J Med 2010; 362: Anderson C, Krska J, Murphy E, et al. The importance of direct patient reporting of suspected adverse drug reactions: a patient perspective. Br J Clin Pharmacol 2011; 72: Directive 2010/84/EU. Official Journal of the European Union 2010, Dec 31,L. 348/ Regulation 1235/2010. Official Journal of the European Union 2010, Dec 31,L. 348/ Waller P. Getting to grips with the new European Union pharmacovigilance legislation. Pharmacoepidemiol Drug Saf 2011; 20: Borg JJ, Aislaitner G, Pirozynski M, et al. Strengthening and rationalizing pharmacovigilance in the EU: where is Europe heading to? A review of the new EU legislation on pharmacovigilance. Drug Saf 2011; 34: Härmark L, van Puijenbroek E, Straus S, et al. Intensive Monitoring of Pregabalin Results from an Observational, Web-Based, Prospective Cohort Study Using Patients as a Source of Information. Drug Saf 2011; 34: Härmark L, van Puijenbroek E, van Grootheest K. Longitudinal monitoring of the safety of drugs by using a web-based system: the case of pregabalin. Pharmacoepidemiol Drug Saf 2011; 20: Härmark L, van Grootheest AC. Web-based Intensive Monitoring, from passive to active drug surveillance. Expert Opin Drug Saf 2012; 11: van Hunsel F, van der Welle C, Passier A, et al. Motives for reporting adverse drug reactions by patient-reporters in the Netherlands. Eur J Clin Pharmacol 2010; 66: O Cathain A, Murphy E, Nicholl J. Why, and how, mixed methods research is undertaken in health services research in England: a mixed methods study. BMC Health Serv Res 2007; 7: Kuper A, Lingard L, Levinson W. Critically appraising qualitative research. BMJ 2008; 337:a Survey Monkey. Available via Accessed Jan 5, Hoe vaak komt diabetes mellitus voor en hoeveel mensen sterven eraan? Dutch National Institute of Public Health and the Environment. Available via gezondheid-en-ziekte/ziekten-en-aandoeningen/endocriene-voedings-en-stofwisselingsziekten-en-immuniteitsstoornissen/diabetes-mellitus/omvang/ Accessed Dec 5, Opleidingsniveau van de Nederlandse bevolking. Trends in Beeld. Available via trendsinbeeld.minocw.nl/grafieken/3_1_2_31.php Accessed Dec 5, Liberati A. Consumer participation in research and health care. BMJ 1997; 315: Blenkinsopp A, Wilkie P, Wang M, et al. Patient reporting of suspected adverse drug reactions: a review of published literature and international experience. Br J Clin Pharmacol 2007; 63:

55 Chapter 3.2 Non-response in a pharmacy and patient based intensive monitoring system, a quantitative study on nonresponse bias and reasons for non-response Härmark L Huls H de Gier H van Grootheest K Submitted

56 56 Chapter Abstract Introduction 4. Pharmacists all over the world play an increasingly important role in pharmacovigilance. 5. Web-based intensive monitoring is a new form of active pharmacovigilance where pharmacists play a key role. Patients using drugs which are monitored by web-based intensive monitoring are identified in the pharmacy and invited to participate. Not all patients who are 8. invited will eventually participate. The aim of this study is to investigate non-response bias in 9. web-based intensive monitoring. In addition, reasons for non-response will be investigated 10. in order to identify barriers for participation Method 13. The study population consisted of patients who received a first dispensation of an antidiabetic drug monitored with web-based intensive monitoring between July 1, 2010 and February 28, Possible non-response bias was investigated by comparing age, gender 16. and the number of drugs used as co-medication. Reasons for non-response were investigated 17. using a postal questionnaire Results 20. Responders were on average 4.5 years younger and used less co-medication. There were no 21. differences regarding gender. The main reason for non-response was that information in the 22. pharmacy lacked. Among the patients who received information and had access to internet 23. but chose not to participate, little personal gain was the main reason for non-response Conclusion 26. The differences between responders and non-responders should be taken into account 27. when analysing and generalising data collected through web-based intensive monitoring as it might contribute to non-response bias. The relatively high response to the postal questionnaire, together with the answers about reasons for non-response show that patients 30. are willing to participate in a web-based intensive monitoring system, when informed and 31. invited in the pharmacy

57 Patients as a source of information Introduction Pharmacovigilance is defined by the WHO as the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem [1]. All over the world pharmacists play an increasingly important role in pharmacovigilance, because of their knowledge about drugs, but also because the pharmacy profes sion is evolving from drug dispensing to providing pharmaceutical care to patients [2,3] The Netherlands Pharmacovigilance Centre Lareb is responsible for the collection and analysis of adverse drug reaction (ADR) reports from both healthcare professionals and patients In addition to this spontaneous reporting system (SRS) a web-based intensive monitoring 12. scheme called Lareb Intensive Monitoring (LIM) was introduced in 2006 as a complement to 13. the SRS. SRS has known limitations and intensive monitoring can provide other information 14. about adverse drug reactions than SRS [4] Web-based intensive monitoring is a non-interventional observational cohort study, using 17. patients as a source of information. In this form of active drug surveillance, the pharmacist 18. plays a key role. Eligible patients are identified in their community pharmacy based on the 19. first time dispensing signal which is generated by the pharmacy computer software if the 20. patient has not filled a prescription of that particular drug in the previous 12 months. If the 21. patient agrees to participate in the LIM study, the patient can register for the study online. 22. After online registration, the patient will automatically receive electronic questionnaires by 23. at different points in time, containing questions about patient characteristics, drug 24. use and ADRs. The LIM methodology has been described in more detail earlier [5,6]. With this 25. system the first group of users of a new drug is monitored, which allows for early identification of new ADRs. In addition, information about incidences, latencies and the time course of the ADR can be collected. This kind of information has been difficult to obtain with other 28. pharmacovigilance methods [7] In the first LIM study, the response rate of patients was 6.6% [6], which is rather low. The 31. reasons for the non-response is unclear, however both pharmacies and patients may be 32. contributing factors. The pharmacy, because informing the patient about the study is a 33. prerequisite for participation. The patients, because they are the ones actually providing the 34. information. Non-response leads to a smaller final sample size, where the chance of finding 35. less frequently occurring ADRs decreases and Iess information about the ADR profile can be 36. gathered. By identifying reasons for non-response, measures to increase patient participation can be taken. If the non-response is not random, it can lead to non-response bias. Studies 37. have shown that elderly people, women, individuals from upper social classes and persons with a higher education are more prone to answer questionnaires than other categories of 3

58 58 Chapter people, which can contribute to non-response bias and ultimately influence the generalisability of the results obtained [8] The aim of this study is to investigate if there is a non-response bias in LIM which might 5. influence the generalisability of the results obtained. In addition, reasons for non-response 6. are investigated in order to identify barriers for participation Method To investigate possible non-response bias a database study was performed. Reasons for nonresponse were investigated using a questionnaire. In order to investigate non-response bias and reasons for non-response, data about patients eligible for LIM inclusion in the participating pharmacies was needed. In the Netherlands, the Dutch Foundation for Pharmaceutical Statistics (SFK) has been collecting exhaustive data about the use of pharmaceuticals since and 92.7% of all Dutch pharmacies contribute data to the foundation. For each dispensation, SFK registers information about the drug supplied, the dispensing pharmacy, the health insurance company, the prescribing doctor and the patient for whom the prescription 19. was issued. So as not to put too much burden on the pharmacies, only pharmacies which 20. actively had included patients in LIM between July 1, 2009 and July 1, 2010 were invited to 21. contribute data to this study. If they agreed to participate, data was collected through SFK [9], 22. so the participating pharmacies did not have to do the data retrieval themselves Non-response bias 25. The study population consisted of patients who received a first dispensation of an antidiabetic drug monitored with LIM between July and February A first dis pensation was identified if the patient had not received any anti-diabetic drugs from the 28. group with ATC-code A10B in the previous 12 months. In addition, SFK checked that the 29. pharmacy brought the prescription into account as a first dispensation in its own database. 30. To investigate non-response bias, three patient characteristics were chosen: age, gender and 31. the number of drugs used as co-medication. These parameters are known to play a role in a 32. person s susceptibility to experience an ADR [10-13]. These three parameters were compared 33. between responders and non-responders to LIM. LIM responders were matched between 34. the LIM database and the data provided by SFK using year of birth, gender, name of the 35. drug, date of the first dispensation and dispensing pharmacy. In this study, drugs used as 36. co-medication were defined as: every drug (ATC7-code) the patient used during the period 37. of three months prior to the first dispensation of the study drug until and including the day of the first dispensation. Only prescribed drugs were included. The characteristics of both LIM

59 Patients as a source of information responders and LIM non-responders were described and statistically significant differences 2. between groups were tested Reasons for non-response 5. To investigate the reasons for non-response, a paper questionnaire was designed. The questionnaire consisted of four parts, namely patient characteristics, information about LIM given by the pharmacy, the LIM registration procedure and motives for non-response. At the end of 8. the questionnaire an open-ended question asking about additional reasons for non-response 9. was included. Motives for non-response were measured using a five point Likert scale with 10. the answering options strongly agree, agree, neutral, disagree and strongly disagree. Before 11. sending the questionnaire, it was tested by 18 persons with different educational levels and 12. age and based on their comments the questionnaire was finalised. The research plan was 13. discussed per telephone with the local Medical Ethics Committee (METC). No approval was 14. needed The paper questionnaire was posted to all non-responders who received a first dispensation 17. between January 1 and February 28, Since it was difficult to estimate the response rate 18. among a group of non-responders, pharmacies were asked to phone at least two patients 19. who did not respond to the postal questionnaire in order to increase the response rate. 20. For the analysis, questionnaires filled in directly by patients and questionnaires filled in by 21. patients after the pharmacy contacted them were analysed together. Only completely filled 22. questionnaires were used. For data entry and descriptive analysis Survey Monkey was used. 23. Certain patient characteristics, such as age and gender might be of influence if the patient 24. receives information about the LIM study in the pharmacy. Age and gender might also be 25. of influence if a patient has access to internet. These associations were further analysed, for 26. the analysis involving age, age was converted into a categorical variable with four equally 27. sized groups. For continuous variables, a t-test was performed and for categorical variables a 28. Chi-squared test. The significance level of all the tests was set at p < The analyses were 29. performed in SPSS for Windows Results Of the 310 pharmacies that were contacted for participation, 82 pharmacies contributed data 35. about 2954 patients, 10 patients were excluded because essential data was missing. From the patients, 2854 were non-responders and 90 were responders in LIM. Age, gender and 37. the number of drugs used as co-medication was compared between non-responders and responders see Table 1. 3

60 60 Chapter 3.2 Table 1. Analysis of characteristics between non-responders and responders Age Number of comedication Gender Non-responders (n=2854) Mean with SD or n with % 63.9 (±14.1) 5.0 (±3.8) Male: 1457 (51.1%) Female: 1397 (48.9%) Responders (n=90) Mean with SD or n with % 59.3 (±11.9) 4.2 (±2.7) Male: 52 (57.8%) Female: 38 (42.2%) P Of the 82 pharmacies who delivered data, 66 agreed to send the questionnaire about reasons for non-response. In these pharmacies, 573 LIM non-responders were identified. To 58 of these, the pharmacy did not send the questionnaire because the patients were temporary visitors to the pharmacy, or too ill to be burdened with a questionnaire. In total, 547 patients were sent a questionnaire. From the 547, 226 patients responded completely, yielding a response rate of 41.3%. From these 197 responded to the postal questionnaire and 29 to the telephone questionnaire The average age of the responders to the questionnaire was 64.8 (SD 13.1) years and 50.9% of the respondents were male. Only 63 patients (27.9%) were informed about the LIM study in the pharmacy, 50.9% was not informed and 21.2% could not remember if they obtained any information. The 63 patients who did receive information continued to the next two questions about the information provided by the pharmacy concerning the LIM study, see Table 2. Most patients agreed that the information they received made it clear what the importance of the study was and what they could expect from the study. To be able to participate in LIM, access to internet is a prerequisite. 47 (74.6%) of the respondents who were asked to participate in the LIM study, had access to internet and could have participated if they wanted to. 11 (23.4%) tried to sign up for the study, but did not succeed. Of the patients that could have signed up but chose not to 36 (76.6%), questions were asked about reasons for non-response, see Table patients filled in the open question at the end. There were only two new reasons for non-response which were not asked in the questionnaire, namely, that patients were too severely ill to participate and that they simply just forgot to register for the study Age and gender did not influence the chance of receiving information about the LIM study (p= 0.88 for both). Older age was associated with less access to internet. Patients without access to internet were on average 10 years older than the patients with access to internet (72.3 (SD ±11.2) versus 62.3 (SD ±10.9)). Gender did not seem to influence a patient s access to internet (p=0.52). 37.

61 Patients as a source of information 61 Table 2. Results from the questions about the quality of the information given to the patients in 1. pharmacy and the reasons for non-response, the most frequently given answer is bold Question The information made Strongly agree %(n) 12.7 (8) Agree %(n) 66.7 (42) Neutral %(n) 14.3 (9) Disagree %(n) 4.8 (3) Strongly disagree %(n) 1.6 (1) the importance of the 5. study clear to me 6. The information made 11.1 (7) 65.1 (41) 17.5 (11) 3.2 (2) 3.2 (2) it clear to me what was to expect from study participation Participation would take 2.8 (1) 19.4 (7) 30.6 (11) 9 (14) 8.3 (3) too much time I was worried about the privacy of my information In my opinion the research was not important enough The research will have little personal yield I have little trust in 2.8 (1) 0 (0) 0 (0) 2.8 (1) 25 (9) 22.8 (8) 36.1 (13) 8.3 (3) 25 (9) 30.6 (11) 22.2 (8) 30.6 (11) 9 (14) 33.3 (12) 33.3 (12) 50.0 (18) 8.3 (3) 13.9 (5) 8.3 (3) 8.3 (3) pharmacovigilance 19. organisations 20. I am too often asked to 5.6 (2) 22.2 (8) 16.7 (6) 44.4 (16) 11.1 (4) 21. participate in research Discussion Non-response bias The analyses of the characteristics showed a significant difference between non-responders and responders in age. Patients who participate in LIM are about 4,5 years younger than patients who do not participate. The analyses also showed a significant difference in amount of drugs used as co-medication. Responders used less co-medication (difference is 0.8) than non-responders. No differences in gender distribution were detected. It is not certain that the age difference between responders and non-responders contributes to non-response bias in the LIM studies, however it should be taken into account when analysing the data from the LIM database. It has not been proven that older patients experience more ADRs than younger patients, but non-response bias can be attributed to the fact that older and younger patients differ physiologically from each other and that older patients often have more co-morbidities and use more co-medication [10,11]. Differences in age might be the reason that LIM participants use less drugs as co-medication than those who do not participate. However, a high number of drugs as co-medication can indicate decreased health status and studies have shown that low health status can be a factor for not participating in research [8,13]. The dif- 3

62 62 Chapter ference in the number of drugs used as co-medication (0.8) is probably not clinically relevant 2. and will not lead to a non-response bias. In order to investigate the clinical relevance one 3. would have to take a look at which type of drugs the non-responders use. Because males 4. and females differ physiologically they can report different ADRs. Research has pointed out 5. that females also have more ADRs than males [12] which makes gender a clinically relevant 6. characteristic. The results showed no significant difference in gender between responders 7. and non-responders, excluding non-response bias Principal results reasons for non-response 10. There are several general reasons why people are reluctant to take part in research. People 11. are more individualistic, where personal gain is more important than contributing to society. 12. People are busy, so time is valuable to people and they choose carefully how to spend it. 13. Because of these reasons, people may be less willing to offer their time to fill in a questionnaire. In addition, people are concerned about the privacy of the data they provide. In the case of patients using drugs, other factors may influence their willingness to participate in 16. research, such as the patient s believes about medicines and the level of adherence to the 17. medication [14] In the questionnaire the major reason for non-response was that the patients were not asked 20. to participate in LIM by the pharmacy. 50.9% of the patients did not receive information 21. about LIM and another 21.2% did not remember if they received information or not. For the 22. patients who received information about LIM, not having access to internet was the reason 23. for non-response for about a quarter of the patients. For those with access to internet, about 24. a quarter stated that they tried to register for the study but failed. Of all possible reasons for 25. non-response not one major reason was identified, except that most patients found that they 26. would gain very little on an individual level by participating. Because about half of all patients 27. were not asked about LIM participation in the pharmacy, it was investigated if receiving information about LIM was influenced by the patients age or gender. Our study shows that age and gender does not influence whether the patient receives information about LIM or not This study was not aimed at investigating the reasons why pharmacies did not provide information to more than half of all patients eligible for the study and therefore the reason for this has to be addressed in another study. The questions about the quality of the information 34. determined that this was not a problem and that the patients who received information were 35. sufficiently informed about the importance of LIM and what they could expect from participation. The second most important reason for non-response was not having access to internet According to Statistics Netherlands (Centraal Bureau voor de Statistiek, CBS) only 9% of the Dutch households lack access to internet. In this study, people older than 75 years were not included [15]. In our study, a higher percentage of patients had no access to internet which is

63 Patients as a source of information possibly due to the fact that the average age is high. Our study showed that patients without 2. access to internet were about 10 years older than patients with access internet. No access to 3. internet might also explain why the LIM responders are younger than the non-responders Strengths and weaknesses 6. Sometimes when non-response bias is investigated, it is not possible to make a direct comparison between responders and non-responders and proxy measures have to be used. One of the strengths of this study is that it investigates non-response bias directly by comparing 9. LIM responders and non-responders instead of using proxy measures A limitation of the research is caused by the definition for the first time dispensation of an 12. anti-diabetic drug to be used. To avoid patients to be included who were not eligible for 13. participating in LIM, the definition for the first time dispensation was conservatively chosen. 14. In order to exclude patients who switched from brand or dose, also patients who switched 15. from one anti-diabetic drug to another anti-diabetic drug were excluded. Therefore, the 16. final group did not represent all patients who were eligible for participating in LIM, because 17. patients who switch from one anti-diabetic drug to another were not included. It is possible 18. that patients who switch from one anti-diabetic drug to another had different reasons for 19. non-response than patients who for the first time received a drug. For example, patients who 20. already use drugs for treating diabetes are more familiar with these types of drugs and could 21. therefore be less worried about ADRs. The number of drugs used as co-medication can give 22. an indication of the amount of drugs a patient uses and thereby give an indication of the 23. patient s health status. However the amount of co-medication used only reflects the number 24. of drugs and not the types of drugs, which might be important to know when deciding if 25. possible differences in the number of drugs used as co-medication would contribute to nonresponse bias. The number of drugs used as co-medication only included prescribed drugs and not OTC drugs In this study the non-responders in LIM were identified and approached with a questionnaire about reasons for non-response. Research to non-response is often done indirectly by comparing characteristics between two groups, but not with a questionnaire particularly 32. focussed on finding reasons for non-response, which makes this study extra valuable. The 33. response rate of the questionnaire was 41.3%. Questionnaires sent in medical settings usually have a response rate of about 60% [16] but this reflects the response rate in a whole study population and not only the non-responders in the study population. For a non-responder 36. study, this percentage can be considered quite high. Since almost 60% of the patients did 37. not respond to the questionnaire, additional analyses were done to determine if there were differences between responders and non-responders to the questionnaire. No difference in 3

64 64 Chapter gender was found, but the average age differed significantly, responders were younger than 2. non-responders By using a postal questionnaire, the possibility for the researcher to control the context of the 5. response diminishes. When people do not understand certain questions, or need clarification 6. about some topics, it is difficult to provide them with an answer, increasing the chance that 7. the questions are misinterpreted or not well understood. In the questions about the motives 8. for non-response, the neutral option was quite often chosen, showing that people may have 9. found it difficult to answer the question. Another problem is that patients give socially desirable answers. In the questionnaires filled in by the pharmacist this might be an even bigger problem. However the number of questionnaires filled in by the pharmacists was relatively 12. low compared to the total number of questionnaires received, making it impossible to make 13. a stratified analysis Conclusion In our study, we compared the characteristics of non-responders with those of responders to 19. a patient- and web-based intensive monitoring system. The responders and non-responders 20. in LIM differ in age. LIM responders are on average 4.5 years younger. The differences found 21. in use of co-medication will probably not be clinically relevant and therefore not contribute 22. to non-response bias. There were no differences in gender, which eliminates non-response 23. bias for this parameter. The differences between responders and non-responders should be 24. taken into account when analysing and generalising data collected through an intensive 25. monitoring system The results of the questionnaire show that general reasons for non-response do not apply to 28. LIM participation, except for personal gain. The main reason for non-response was that patients were not informed in the pharmacy about the study, had no access to internet and that participation would have little gain for the individual patient. The relatively high response to 31. the postal questionnaire, together with the answers about reasons for non-response, show 32. that patients are willing to participate in a web-based intensive monitoring system when 33. informed and invited in the pharmacy

65 Patients as a source of information References 1. The Importance of Pharmacovigilance. WHO Available via Accessed Jan 20, van Grootheest AC, van Puijenbroek EP, de Jong-van den Berg LT. Contribution of pharmacists to the reporting of adverse drug reactions. Pharmacoepidemiol Drug Saf 2002; 11: van Grootheest K, Olsson S, Couper M. Pharmacists role in reporting adverse drug reactions in an international perspective. Pharmacoepidemiol Drug Saf 2004; 13: Härmark L, van Grootheest AC. Pharmacovigilance: methods, recent developments and future perspectives. Eur J Clin Pharmacol 2008; 64: Härmark L, van Grootheest AC. Web-based Intensive Monitoring, from passive to active drug surveillance. Expert Opin Drug Saf 2012; 11: Härmark L, van Puijenbroek E, Straus S, et al. Intensive Monitoring of Pregabalin, Results from an Observational, Web-Based, Prospective Cohort Study Using Patients as a Source of Information. Drug Saf 2011; 34: Härmark L, van Puijenbroek E, van Grootheest K. Longitudinal monitoring of the safety of drugs by using a web-based system: the case of pregabalin. Pharmacoepidemiol Drug Saf 2011; 20: Etter JF, Perneger TV. Analysis of non-response bias in a mailed health survey. J Clin Epidemiol 1997; 50: Dutch Foundation for Pharmaceutical Statistics. Available via Accessed Jan 20, Begaud B, Martin K, Fourrier A, et al. Does age increase the risk of adverse drug reactions? Br J Clin Pharmacol 2002, 54: Gurwitz JH, Avorn J. The ambiguous relation between aging and adverse drug reactions. Ann Intern Med 1991; 114: Tran C, Knowles SR, Liu, BA, et al. Gender differences in adverse drug reactions. J Clin Pharmacol 1998; 38: Paganini-Hill A, Hsu G, Chao A, et al. Comparison of early and late respondents to a postal health survey questionnaire. Epidemiology 1993; 4: Clifford S, Barber N, Horne R. Understanding different beliefs held by adherers, unintentional nonadherers, and intentional nonadherers: application of the Necessity-Concerns Framework. J Psychosom Res 2008; 64: Mediaproducten steed meer via internet. Centraal Bureau voor de Statistiek Available via Accessed Jan 20, Asch DA, Jedrziekwski MK, Christakis, NA. Response rates to mail surveys published in medical journals. J Clin Epidemiol 1997; 50:

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67 Chapter 4 Representativeness of patients participating in a web-based intensive monitoring system

68

69 Chapter 4.1 Representativeness of diabetes patients participating in a webbased adverse drug reaction monitoring system Härmark L Alberts S Denig P van Puijenbroek E van Grootheest K Submitted

70 70 Chapter Abstract Purpose 4. Lareb Intensive Monitoring (LIM) is a non-interventional observational cohort method which 5. follows first-time users of certain drugs during a certain period of time and collects information about adverse drug reactions (ADRs). In order for LIM to be a useful pharmacovigilance tool, it is important to know whether the LIM population is comparable to the whole population using the drug. The aim of this study is to compare the LIM diabetes population with an external diabetes reference population on characteristics that may influence the patient s 10. susceptibility for ADRs Methods 13. In this study, a LIM diabetes population was compared to a reference diabetes population derived from The Groningen Initiative to ANalyse Type 2 diabetes Treatment project (GIANTT) Comparisons were made regarding age, gender, BMI and polypharmacy, as well as diabetes 16. medication used and disease/treatment duration Results 20. LIM patients were more often men (58.5% vs 50.8%) and in general younger (59.1 vs years) and healthier, by that meaning that this population had a higher percentage of de 22. novo treated patients (55.5% vs 53.2%), a shorter diabetes treatment duration (3.7 vs years) and used less co-medication than patients in the reference population Conclusions 26. This study shows that diabetes patients participating in a web-based monitoring system differ from a reference population. The observed differences might lead to an underestimation of ADRs but it is not clear whether this would also influence the type or time-course of the 29. ADRs reported. When interpreting results from LIM studies, one should take these differences 30. into account

71 Representativeness of the population Introduction After the withdrawal of rofecoxib in 2004 [1] it became evident that pharmacovigilance 4. needed improvement to meet society s needs regarding information about adverse drug 5. reactions (ADRs). In the following years pharmacovigilance systems in the US as well as in 6. Europe underwent close scrutiny [2,3], and recently the European regulatory framework 7. for pharmacovigilance underwent legislative changes as described in a new Directive and 8. Regulation [4,5]. The new legislation will, among others, give regulators the legal power to 9. request Post Authorisation Safety Studies (PASS). Hopefully these new measures will lead to 10. better pharmacovigilance, including development of new methods which can capture other 11. types of information, for example regarding the time course of ADRs, than retrieved from 12. clinical trials and spontaneous reporting In the Netherlands, the national pharmacovigilance centre Lareb, which is responsible for 15. maintaining the spontaneous reporting system, developed a web-based intensive monitoring 16. system called Lareb Intensive Monitoring (LIM), which can capture more detailed information 17. on the time course of ADRs and enables estimation of the incidence of reported ADRs. LIM is 18. a monitoring system which prospectively follows cohorts of first time users of specific drugs 19. for a certain period of time. In LIM, patients eligible for inclusion are identified in community 20. pharmacies through a first dispensation signal. The patient receives information about the 21. study and when willing to participate, registers online. After registration, questionnaires are 22. sent by at specific points in time. Questions are asked about patient characteristics, 23. drug use and possible adverse drug reactions. The LIM methodology has been described in 24. more detail elsewhere [6,7] For a new pharmacovigilance system such as LIM to be a useful tool, it is important to know 27. whether the population who chooses to participate with LIM is comparable to the whole 28. population using the drug. Otherwise it might be difficult to extrapolate the results to the 29. population at large. The participation rate in previous studies has been around 5% of all the 30. patients receiving a first dispensation for a specific drug [7,8]. It is not known whether all 31. patients who received the drug for the first time were actually informed about the study in 32. the pharmacy. Selection bias could thus be introduced at the level of the pharmacy and at 33. patient level In 2008, a LIM cohort study was started monitoring the safety of all anti-diabetic drugs except 36. insulins. The aim of this study is to compare the LIM diabetes population with an external 37. diabetes reference population on characteristics that may influence the patient s susceptibility for adverse drug reactions. 4

72 72 Chapter Method The LIM diabetes population was compared to a reference population consisting of patients 4. with type 2 diabetes mellitus. The two populations were compared on parameters which 5. might influence a patient s susceptibility to develop an adverse drug reaction, such as age 6. [9,10], gender [11], BMI [12,13] and polypharmacy at the time of new anti-diabetic drug 7. start [14]. Comparisons were also made between the two populations regarding clinical 8. parameters related to their diabetes status, such as diabetes medication used and diabetes 9. treatment duration. The anti-diabetic drugs on which the patient entered the study were 10. divided into four groups: biguanides, sulphonamide urea derivates, GLP-1 analogues or DPP inhibitors, and the remaining group of other oral anti-diabetic drugs. If the patient started 12. on a combination drug, the patient was registered in the group as described above to which 13. the newest substance in the combination belonged. In the following paragraphs the two 14. populations and the data extraction will be described in more detail LIM diabetes population 17. A LIM diabetes patient was defined as a person who received a first dispensation for an oral 18. anti-diabetic drug or a GLP-1 analogue between February 1, 2008 and November 1, 2011 and 19. registered for the LIM study. Only anti-diabetic drugs which were registered before February 20. 1, 2008 were included during the study period. A first dispensation was defined as an oral 21. anti-diabetic drug prescription or a GLP-analogue without a prescription for the same drug 22. in 12 months prior to the date of prescription. In the LIM population, demographic information (gender, birth date, length, weight), information relating to the study including date of entering the study, study drug use and concomitant drug use (type of drugs as well as start 25. date and if applicable stop date) were asked. In addition, information about adverse drug 26. reactions and an open question about previous use of anti-diabetic drugs were collected 27. through structured questionnaires. The questionnaires were filled in at registration, and at and 6 weeks and 3, 6, 9 and 12 months after starting the anti-diabetic drug. All data, except 29. for previous use of anti-diabetic drugs, were collected in the registration questionnaire Reference population 32. The Groningen Initiative to ANalyse Type 2 diabetes Treatment (GIANTT) database is a registry of ambulant patients with type 2 diabetes mellitus in the northern part of the Netherlands [15]. It contains demographic information (birth date, gender, date of first registration and 35. end of registration, date of death), prescriptions, symptoms and diagnoses as recorded in text 36. or with International Classification of Primary Care (ICPC), medical history, results of physical examination expressed as numerical data and laboratory results of patients with type diabetes as documented in electronic primary care medical records [16]. A GIANTT reference patient was defined as a person who received a first prescription of an oral anti-diabetic drug

73 Representativeness of the population or a GLP-1 analogue in the period between January 1, 2008 and November 1, A first prescription was defined as an oral anti-diabetic drug prescription or a GLP-analogue without a prescription for the same drug in 12 months prior to the date of prescription Data definitions in LIM population 6. The age of the LIM patients was calculated in years from the date of birth to the start date of 7. the first prescription in the study period. The BMI was calculated, values smaller than 10 and 8. greater than 50 were considered to be invalid and were excluded from further analysis. Patients were considered to be de novo anti-diabetic drug users when they did not report any co-medication belonging to the group of anti-diabetic drugs (ATC code A10) and reported 11. that they had not used any anti-diabetic drugs in the past. The patients who reported an antidiabetic drug as co-medication provided information about the start year which was then used to calculate the diabetes treatment duration in days. If more anti-diabetic drugs were 14. used, the oldest start date was used. The start date of any previously used and stopped antidiabetic drugs, however, was not available. For patients who did not provide a start date for their anti-diabetic drugs no duration could be calculated, and these patients were omitted 17. from the analysis about treatment duration. The number of concomitantly used drugs was 18. restricted to drugs commonly used for chronic diseases, i.e. belonging to the ATC chapters 19. A (Alimentary tract and metabolism), B (Blood and blood forming organs), C (Cardiovascular 20. system), H (Systemic hormonal preparations), L (Anti-neoplastic and Immunomodulated 21. agents), M (Musculo-skeletal system), N (Nervous system) and R (Respiratory system) [17] as 22. reported by the patients Data definitions in reference population 25. The age of patients in the reference population was also calculated from the date of birth to 26. the date of the first prescription in the study period. The BMI value available from the medical 27. records which was closest in time to the first prescription was used. To calculate the diabetes 28. treatment duration, the date of the first prescription of an anti-diabetic drug ever and the 29. date of first prescription in the inclusion period for this cohort were used. In the reference 30. population, the patient would be seen as de novo if the date of the first prescription of any 31. anti-diabetic drug was the same as the date of the first prescription for inclusion in this cohort. The number of concomitantly used drugs, using the same ATC restrictions as above, was based on the drugs prescribed in a period up to 120 days prior to the first prescription of the 34. oral anti-diabetic drug. This period was chosen since chronic drugs are commonly prescribed 35. for a period of 3 months in the Netherlands Analysis In the LIM population as well as in the reference population a patient could be included more than once depending on how many first prescriptions of an anti-diabetic drug the patient 4

74 74 Chapter received during the study period. For the comparison between the drugs of the first prescription, all first prescriptions were included. For comparing the populations at first prescrip tion regarding gender and age distribution, Body Mass Index, disease treatment duration, 4. de novo anti-diabetic drug use and number of drugs used as co-medication, a patient was 5. included only once, using the values from the first prescription during the study period. 6. Differences in demographic and clinical characteristics between the two populations were 7. tested with Chi-squared and Fisher exact tests for categorical data and with two-tailed t-tests 8. for normally distributed data and Mann-Whitney U-tests for non-parametric data. Gender 9. and co-medication were stratified for age in 5 year intervals, since age could be a confounder 10. in the results of gender and the number of co-medication. For gender stratified by age, an 11. odds ratio was calculated using logistic regression MS Access 2000 was used for LIM data retrieval. Statistical analyses were performed using 14. SPSS for Windows version P-values equal or below 0.05 were considered statistically 15. significant Results In the study period patients were included in the LIM population and patients 21. were included in the reference population. The LIM population included more males, was on 22. average more than 5 years younger, and used on average less co-medication in comparison 23. to the reference population, see Table 1. Furthermore, it included around 55% de novo 24. diabetes treatment patients, which was slightly higher than the 53% observed in the reference population. The treatment duration of those already on treatment was almost 4 years, which was more than a year shorter as compared to the reference population. The frequency 27. order of the drugs included as a first prescription was similar between LIM and the reference 28. population with biguanides being the most frequently initiated drug (almost 60%) followed 29. by sulphonamide urea derivates (around 25%). In the LIM population, the GLP-1 analogues 30. and DPP-4 inhibitors were slightly more included, see Table As age might be a confounder for gender, stratified analysis was made calculating the female/male ratio in LIM compared to the reference population. The analysis between age and gender shows that in the younger age categories (under 45) there were more females in LIM 35. compared to the reference population, between the ages of 45 to 59 the gender distribution 36. was almost equal and in the age categories above 60, the reference population contained 37. more females, see Figure 1.

75 Representativeness of the population Table 1. The comparison of the LIM diabetes population with a reference population. The number of patients or the mean with standard deviation or the median with the Inter Quartile Range are presented. 2. LIM GIANTT n n with % or mean with SD or median with IQR n n with % or mean with SD or median with IQR P 6. First prescription < Biguanides 1721 (59.6%) 8744 (57.1%) Sulphonamide urea derivatives 707 (24.5%) 149 (15.0%) 4492 (29.3%) 142 (7.4%) -DPP-4 inhibitors and GLP- 329 (11.4%) 1257 (8.2%) 9. 1 analogues Remaining group 133 (4.6%) 827 (5.4%) 11. Gender < Men Women 1653 (58.5%) 1175 (41.5%) 6020 (50.8%) 5832 (49.2%) Age (years) (± 10.7) (± 12.7) < BMI (kg/m2) (± 5.3) (± 5.6) < De novo anti-diabetic % % < drug users Unclassified % 18. Duration diabetes < treatment 1343 ( ) 1997 ( ) (days) 20. Number of co medication (1-4) (2-7) < Age might also be a confounder for the number of co-medication used, therefore the number of co-medication was stratified for age, see Figure 2. In LIM the number of co-medication commonly used for chronic conditions was relative stable around 2-3 drugs, regardless of age. In the reference population, the number of co-medication increased by age. In all age categories, except for the group under 35 years statistically significant differences were present Discussion Principal findings The comparison of the LIM diabetes population with a reference population showed differences in patient s characteristics, diabetes characteristics and number of co-medication. LIM patients were in general younger and healthier, by that meaning that they were more often de novo anti-diabetic drug users, had a shorter treatment duration and used less co-medication than patients in the reference population. In contrast to the reference 4

76 76 Chapter 4.1 Figure 1. Gender stratified by age-class (in years) shown as odds ratios, where the odds ratio was calculated as female/male ratio in LIM compared to the reference population , , , , Figure 2. Mean number of co-medication per age category age categories (in years) Number of co-medication < >85 LIM GIANTT

77 Representativeness of the population population, co-medication did not increase for patients in the LIM population with increasing 2. age. Furthermore, the LIM population included relatively more females in the youngest age 3. category and more males in the elderly categories as compared to the reference population The age difference between the two groups of more than 5 years could be attributed to 6. internet access and computer skills. Older patients may have less access to and knowledge 7. or trust about internet. These patients would therefore not register with the LIM diabetes 8. study. In addition, older patients may have an impaired cognitive function, which might 9. not make LIM participation possible. It has been found that higher age or other factors 10. closely linked to age, for example comorbidity and co-medication, are associated with an 11. increased susceptibility for adverse drug reactions [10,18]. This would imply that LIM is likely 12. to underestimate adverse drug reactions. It is not clear, however, whether the type of ADRs 13. experienced or reported will be affected by age, but it has been suggested that type A ADRs 14. are more common in the elderly and the unpredictable type B ( bizarre or idiosyncratic reactions) less common [19] The LIM database contains slightly more men than women. When gender is corrected for 18. age, there are no differences in distribution between the ages of Above 65 years, the 19. reference population contained more females which might be due to the fact that older men 20. are more familiar with using computers and internet compared to older women. Studies have 21. shown that women are more prone to develop ADRs than men [11]. However, the mechanism 22. behind these differences is not known. There are several factors that have been suggested to 23. play a role, including pharmacokinetic and pharmacodynamic factors, hormonal influences, 24. healthcare utilisation, reporting bias, and increased use of medications in women. The pharmacokinetic differences such as higher plasma drug levels and a higher percentage of body fat in women may result in females experiencing more dose related effects [11]. A LIM study 27. where more men are participating than women, would probably lead to an underestimation 28. of adverse drug reactions The diabetes treatment duration in LIM is shorter than in the reference population. Because 31. the LIM population is younger than the reference population, this might influence the diabetes treatment duration if one assumes that the age of diabetes onset is the same in the two populations The number of co-medication in the reference population was higher than in the LIM population. In the reference population the number of co-medication increases with age and this trend is not seen in LIM where the number of co-medication stays quite constant between the different age groups. As we know, the number of co-medication increases with age [20,21] and this could be due to a healthier LIM population with respect to age and diabetes. 4

78 78 Chapter The number of de novo patients is also slightly higher in LIM than the reference population, 2. and one can assume that these are healthier than chronic patients and will thus use less 3. co-medication The pattern of the drugs used for the first prescription is similar between LIM and the reference population and mirrors the guideline for diabetes treatment in the Netherlands [22] However in LIM the GLP-1 analogues and DPP-4 inhibitors were slightly more included. 8. Maybe pharmacists are more active in recruiting patients who use these drugs because they 9. are new chemical entities and knowledge about their ADRs is scarce Strengths and weaknesses 12. In this study we compare a web-based intensive monitoring population with a reference 13. population to see whether these two populations are comparable. Ideally, one would like 14. to compare the LIM diabetes population with the patients who are LIM non-responders, but 15. since this information is not readily available, it was chosen to compare the LIM population 16. with a reference population consisting of patients with diabetes By comparing the LIM diabetes population with a reference population, data of different 19. origin and kind are used. In both systems, data can be missing. For example, BMI data were 20. very incomplete, limiting the value of its comparison. The reference population is based on 21. medical records and LIM is based on direct information from the patients, and the data in 22. both data-sets were not collected with the aim of comparing the two data sets with each 23. other. Therefore not all the parameters that were needed for the comparison were readily 24. available, some parameters could only be obtained by proxy or when certain assumptions 25. were made Some of the differences found in this study could partly be due to the way the data were 28. collected or extracted. Specifically, this might have played a role regarding the diabetes 29. treatment duration and co-medication data. In the reference population the duration was 30. calculated using the date of the first prescription ever of an anti-diabetic drug. In LIM, the 31. date of the first dispensation ever was not known and the date of the first dispensation of 32. any anti-diabetic drug which the patient was using at the time of LIM registration was used to 33. calculate the diabetes duration. If the patient had used other anti-diabetic drugs in the past 34. but stopped using them before entering the study, these would not be taken into account 35. when calculating the diabetes duration, yielding a shorter diabetes treatment duration than 36. the actual diabetes treatment duration for the LIM population. On the other hand, also in 37. the reference population incomplete documentation of previously used drugs may occur. The number of co-medication in the reference population is based on the prescribed drugs instead of the used drugs, which means that an overestimation is possible in the reference

79 Representativeness of the population population. In LIM, patients reported the drugs which they actually used, however it is possible that the LIM participants forgot or did not feel like to report all co-medication, giving an under-estimation of the number of co-medications Finally, the differences found in this comparison are applicable to a cohort consisting of 6. diabetes patients. LIM as a system is developed to monitor all kind of drugs, and it is not 7. known to what extent the results of this study would be applicable for other populations. For 8. example, limitations related to age, treatment duration or co-medication are likely to depend 9. on the type of drug one is monitoring Conclusion The aim of this study was to test whether a web-based intensive monitoring population 15. differs from a reference population concerning parameters that might influence a patient s 16. susceptibility to develop an adverse drug reaction. This study shows that diabetes patients 17. participating in a web-based monitoring system are more often men and in general younger 18. and possibly healthier than the reference population. Such differences might lead to an underestimation of adverse drug reactions but it is not clear whether this would also influence the type or time-course information of ADRs reported. Differences found in this study have 21. to be taken into account when interpreting results from web-based intensive monitoring 22. studies

80 80 Chapter References 1. Merck Announces Voluntary Worldwide Withdrawal of VIOXX. Merck & Co Available via Accessed March 1, Baciu A, Stratton K, Burke SP, editors. Committee on the Assessment of the US Drug Safety System The future of drug safety: promoting and protecting the health of the public. Institute of Medicine Washington DC. 3. Assessment of the European Community System of Pharmacovigilance. Fraunhofer Available via 0/ rappfraunhofer.pdf Accessed March 1, Regulation 1235/2010. Official Journal of the European Union 10 A.D L. 348/1-16. Available via 6:EN:PDF Accessed June 23, Directive 2010/84/EU. Official Journal of the European Union 2010, L. 348/ Available via 9:EN:PDF Accessed June 24, Härmark L, van Puijenbroek E, van Grootheest K. Longitudinal monitoring of the safety of drugs by using a web-based system: the case of pregabalin. Pharmacoepidemiol Drug Saf 2011; 20: Härmark L, van Puijenbroek E, Straus S, et al. Intensive monitoring of pregabalin: results from an observational, web-based, prospective cohort study in the Netherlands using patients as a source of information. Drug Saf 2011; 34: Härmark L, van Puijenbroek E, van Grootheest K. Intensive Monitoring of Duloxetine, Results from a web-based intensive monitoring study. Submitted. 9. Begaud B, Martin K, Fourrier A, et al. Does age increase the risk of adverse drug reactions? Br J Clin Pharmacol 2002; 54: Gurwitz JH, Avorn J. The ambiguous relation between aging and adverse drug reactions. Ann Intern Med 1991; 114: Tran C, Knowles SR, Liu BA, et al. Gender differences in adverse drug reactions. J Clin Pharmacol 1998; 38: Chung-Delgado K, Revilla-Montag A, Guillen-Bravo S, et al. Factors associated with anti-tuberculosis medication adverse effects: a case-control study in Lima, Peru. PLoS One 2011; 6:e Campos-Fernandez MM, Ponce-De-Leon-Rosales S, Archer-Dubon C, et al. Incidence and risk factors for cutaneous adverse drug reactions in an intensive care unit. Rev Invest Clin 2005; 57: Leendertse AJ, Egberts AC, Stoker LJ, et al. Frequency of and risk factors for preventable medication-related hospital admissions in the Netherlands. Arch Intern Med 2008; 22: Voorham J, Haaijer-Ruskamp FM, van der Meer K, et al. Identifying targets to improve treatment in type 2 diabetes; the Groningen Initiative to analyse Type 2 diabetes Treatment (GIANTT) observational study. Pharmacoepidemiol Drug Saf 2010; 19: Voorham J, Denig P. Computerized extraction of information on the quality of diabetes care from free text in electronic patient records of general practitioners. J Am Med Inform Assoc 2007; 14: ATC classification. WHO Collaborating Centre for Drug Statistics Methodology. ATC classification. Available via Accessed March 7, Routledge PA, O Mahony MS, Woodhouse KW. Adverse drug reactions in elderly patients. Br J Clin Pharmacol 2004; 57: Bowman L, Carlstedt BC, Hancock EF, et al. Adverse drug reaction (ADR) occurrence and evaluation in elderly inpatients. Pharmacoepidemiol Drug Saf 1996; 5:9-18.

81 Representativeness of the population Jyrkka J, Vartiainen L, Hartikainen S, et al. Increasing use of medicines in elderly persons: a fiveyear follow-up of the Kuopio 75+Study. Eur J Clin Pharmacol 2006; 62: Linjakumpu T, Hartikainen S, Klaukka T, et al. Use of medications and polypharmacy are increasing among the elderly. J Clin Epidemiol 2002; 55: NHG standaard Diabetes mellitus type 2. Nederlands Huisartsen Genootschap Available via artsennet nl/kenniscentrum/k_richtlijnen/k_nhgstandaarden/samenvattingskaartje- NHGStandaard/M01_svk htm Accessed Feb 16,

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83 Chapter 5 Description of the Lareb Intensive Monitoring system using pregabalin and duloxetine as examples

84

85 Chapter 5.1 Intensive monitoring of pregabalin: results from an observational, web-based, prospective cohort study in the Netherlands using the patient as a source of information Härmark L van Puijenbroek E Straus S van Grootheest K Drug Safety 2011; 34:

86 86 Chapter Abstract Background 4. Pregabalin is one of the first drugs registered for the treatment of neuropathic pain. It is 5. also indicated as adjuvant therapy in the treatment of epilepsy and for generalised anxiety 6. disorder. Pregabalin is a GABA analogue and exerts its effect by binding to the α 2 -δ subunit 7. of voltage-gated calcium channels, leading to a decreased synaptic release of neurotransmitters Objective 11. To gain insight into the safety and user profile of pregabalin in daily practice, reported by 12. patients via a web-based intensive monitoring system based at the Netherlands Pharmacovigilance Centre Lareb Methods 16. Lareb Intensive Monitoring is an observational prospective cohort study with no limiting inclusion or exclusion criteria compared with clinical trials. First-time users of pregabalin were identified through the first prescription signal in intensive monitoring participating pharmacies between August 1, 2006 and January 31, Eligible patients received information about the pregabalin study in the pharmacy. When registering online, patient characteristics 21. and information about pregabalin and other concomitant drug use were collected. After 22. registration, the patient received questionnaires by 2 weeks, 6 weeks, 3 months and months after the start of pregabalin. In these questionnaires, possible adverse drug reactions 24. (ADRs) were addressed. Reactions not labelled in the Summary of Product Characteristics 25. of pregabalin, and reactions that were labelled but were interesting for other reasons, were 26. analysed on a case-by-case basis Results 29. In total, 1373 patients filled in the online registration form. The average age of participants 30. was 54.5 years (range 11-89), with 58.0% being female. The indication for pregabalin use was 31. neuropathic pain in 85.9% of participants. The average daily dose was 201 mg, and 80.5% 32. of all users used pregabalin capsule 75 mg. All patients who registered for the study were 33. sent a questionnaire, 1051 (76.5%) patients filled in at least one questionnaire. There were 34. no statistically significant differences found regarding sex, age or daily dosage between 35. this latter group compared with the patients who registered for the study but did not fill in 36. a questionnaire. At least one possible ADR was reported by 69.3% of patients and serious 37. ADRs were reported by 11 patients. The five most frequently reported possible ADRs were dizziness, somnolence, feeling drunk, fatigue and increased weight. Four associations were further analysed. Headache was analysed because of its high frequency. The time to onset

87 Description of the Lareb Intensive Monitoring system ranged from a few hours to 5 months, with a median time to onset of 2 days. In 15 reports the 2. headache passed without withdrawing the drug, and in ten cases the headache disappeared 3. after drug withdrawal. Upper abdominal pain, a possible drug interaction between pregabalin and blood glucose-lowering agents, and suicidal ideation were considered to be signals Conclusions 7. Web-based intensive monitoring is an observational prospective cohort study. It will therefore provide a picture of the use of pregabalin and its ADRs in daily practice. This study indi cates that pregabalin is a relatively safe drug. Eleven patients (<1.0%) experienced a serious 10. ADR while using the drug. The most frequently reported possible ADRs correspond with the 11. reactions most frequently reported during clinical trials. The study demonstrates that a webbased intensive monitoring system can contribute to greater knowledge about a reaction, such as headache, with quantification and information about latencies and time course of 14. the reaction. It can also detect signals worth further investigation, such as abdominal pain 15. and possible interaction with oral antidiabetics Background Neuropathic pain is pain associated with disease or injury of the peripheral or central nervous system [1]. This type of pain is considered to be particularly difficult to treat [2]. In the Netherlands, the incidence rate of neuropathic pain has been estimated to be 8.2 per person-years, translating to 0.8% of the population per year, or more than new cases 24. yearly. Neuropathic pain is more common in women than in men (63% of all patients with 25. neuropathic pain are female) and peaks between the ages of 70 and 79 years [3] Antiepileptics (such as gabapentin and carbamazepine) and antidepressants (such as nortriptyline and amitriptyline) have been shown to be effective in treating neuropathic pain [4]. In 2004, pregabalin was introduced in Europe for the treatment of neuropathic pain. In 30. addition to neuropathic pain, pregabalin is also indicated as adjuvant therapy in the treatment of epilepsy and for generalised anxiety disorder [5]. It is a GABA analogue and exerts it effects by binding to the α 2 δ subunit of voltage-gated calcium channels, leading to a 33. decreased synaptic release of neurotransmitters [6]. Before pregabalin approval, its efficacy 34. had been investigated in more than ten controlled clinical trials, none of which lasted longer 35. than 13 weeks [5]. Because of the well known limitation of premarketing studies [7], the full 36. benefit-risk balance and user profile of pregabalin could not be considered to be complete at 37. the time of marketing. Monitoring of the drug in daily practice is therefore necessary. 5

88 88 Chapter The main method of gathering data in the post-marketing phase is through a spontaneous 2. reporting system [8], whereby healthcare professionals and, increasingly, patients can submit 3. reports of adverse drug reactions (ADRs). These reports can lead to the detection of a new 4. signal, an association between a drug and an ADR, previously not known. Even though spontaneous reporting has shown its strengths throughout the years [9], it also has limitations One of the most frequently mentioned is underreporting [10] and the inability to assess the 7. incidence of the reported ADRs Spontaneous reporting systems focus on detecting new signals. The detection of a new 10. signal is not always sufficient for a well informed decision to be made as to whether to use 11. that drug or not. Information on who is at risk of developing the ADR, the latency, duration, 12. seriousness and severity of the ADR, and what action is necessary to cope with the ADR, is 13. information that can help in the decision-making process. Traditionally, pharmacovigilance 14. has been focused on finding unrecognised potential harm that has not yet been demonstrated. Waller and Evans [11] have suggested that pharmacovigilance should be less focused on finding harm and more focused on extending knowledge of safety. Extending knowledge 17. on safety is difficult since safety can only be demonstrated to a finite degree [11]. In terms 18. of demonstrating safety, new forms of post-marketing research are needed to gather information that aims to provide information on safety instead of focusing on finding harm, for example observational cohort studies In the Netherlands, the Netherlands Pharmacovigilance Centre Lareb has been responsible 23. for the collection and analysis of spontaneous reports since To meet the increasing 24. needs of extending the knowledge about the use and safety of a drug in daily practice, a new 25. method has been developed. In spontaneous reporting a report is only submitted when the 26. patient has experienced an ADR. This new method is focused on gathering information on 27. safety from the patient s first day of use of a specific drug. Some patients might experience a 28. possible ADR and some might not, and by monitoring all first-time users of a drug it will be 29. possible to gather information from daily practice. In 2006, a web-based intensive monitoring system, called Lareb Intensive Monitoring (LIM), was introduced. This system is based on patients filling in questionnaires sent by during the first period of time that they use 32. the drug [12-14] The aim of this study is to gain insight into the user profile and safety of pregabalin in daily 35. practice, reported by patients via a web-based intensive monitoring system during the first months of use. 37.

89 Description of the Lareb Intensive Monitoring system Method Study population 4. The included population consisted of first-time users of pregabalin, identified through the 5. first prescription signal in the intensive monitoring participating pharmacies between August 6. 1, 2006 and January 31, Data were collected between August 1, 2006 and July 31, Community pharmacists were invited to participate in the intensive monitoring system, and 9. more than 1000 pharmacies (more than 50% of all Dutch pharmacies) decided to participate. 10. Patients in the Netherlands are linked to one pharmacy only, which makes it possible to 11. monitor a patient s drug use. The computer can signal if a patient is receiving a drug for the 12. first time, i.e. the patient has not filled a prescription for the drug, in that particular pharmacy, 13. in the previous 12 months. The pharmacist receives a special LIM signal when a drug studied 14. with the LIM system is dispensed for the first time. If receiving pregabalin for the first time, 15. patients receive information in the pharmacy about the pregabalin study and are given a 16. pharmacy-specific code with which they can sign up for the study online Data collection 19. Upon registration, patients were asked for an address, which was used for further 20. correspondence. Patient characteristics such as sex, birth date, height and weight were 21. collected. Information about pregabalin use, including start date, strength, product code, 22. dosage, administration form and indication were collected. This information was also gathered for all concomitant medication. Patients received questionnaires by 2 weeks, weeks, 3 months and 6 months after starting to take the drug. These questionnaires collected 25. information on possible ADRs: seriousness of the reaction according to the criteria developed 26. by CIOMS, which include (prolongation of ) hospitalisation, life-threatening events, reactions 27. leading to death, disabling events, congenital abnormalities and other medically important 28. conditions, start date of reaction, action taken with pregabalin (stopping/dose reduction/no 29. dose change), and outcome of the reaction. For an overview of the questionnaires see tables 30. SI and SII. If the patient did not fill in the questionnaire immediately, a reminder was sent days later. If a questionnaire was not completed 4 weeks after the reminder, the patient was 32. considered lost to follow-up for that questionnaire If the patient stopped the use of pregabalin, or in the event of death of the patient or if the 35. patient actively chose to stop his participation in the study, the patient did not receive any 36. more questionnaires. The participation in the study was then considered to be completed. 37. All data were stored in an Oracle database. The indication and reported ADRs were coded using the Medical Dictionary for Regulatory Activities (MedDRA) on a Lower Level Term, by a qualified assessor. Study drug and co-medication were coded using the Dutch drug diction- 5

90 90 Chapter ary (Z-index) [15]. If a report was reported as serious according to the CIOMS criteria, and also assessed as serious by the assessor, a copy of the report was exported to the national database containing all spontaneous reports, where it was handled according to the regulations regarding serious ADR reports. See Figure 1 for a schematic description of the workflow. Analysis Descriptive analysis was performed on patient characteristics, drug use and indication for use. The number of patients reporting a possible ADR, the percentage of serious ADRs and the incidence of different ADRs were calculated. Even though a patient could report the same ADRs in all four questionnaires, one specific reaction was only counted once for each individual when calculating incidences. The possible ADRs were divided into labelled or not labelled according to the European Public Assessment Report [5]. Reactions that were not labelled and reactions that were labelled but for other reasons were considered to be of potential interest (selection was undertaken by one pharmacist (LH) and one general practitioner (EvP)) were analysed on a case-by-case basis. Labelled reactions were considered to be of interest if differences were found between the cohort and the Summary of Product Characteristics (SPC). Reactions with serious complications, even though they were labelled, were further analysed. Figure 1. Flow diagram for Lareb Intensive Monitoring. Pharmacy Patient Lareb 1 st prescription signal Registration Questionnaire 2 weeks Questionnaire 6 weeks Questionnaire 3 months Questionnaire 6 months Coding Analysis

91 Description of the Lareb Intensive Monitoring system In the case-by-case analysis, causality was assessed by looking at the temporal relationship between the drug and the reaction, and to exclude other causes for the reaction (for example confounding by indication, concomitant medication). Only reactions where the causality was assessed as at least possible were included A comparison between patients who only filled in the registration form and patients who provided data on whether or not they had experienced any possible ADRs was made on the basis of age, sex and daily dosage. Age and daily doses were tested with a t-test, sex was tested with a chi-squared test and significance was declared at the p < 0.05 a level. Data were retrieved using Microsoft Access. Statistical analysis was performed using SPSS version 17 (SPSS Inc., Chicago, IL, USA) Results Between August 1, 2006 and January 31, 2008, 1373 patients registered for the pregabalin study. 796 (58.0%) of these were female. The average age was 54.5 (SD 13) years, ranging from years. Neuropathic pain was the indication in 85.9% of cases. For an overview of reported indications see Table 1. Pregabalin capsule 75 mg was used by 80.5% of the population cohort, 150 mg was used 21. Table 1. Top 5 indications for pregabalin use. 22. Indication Number of patients 23. Neuropathic pain 1.179* Pain Fibromyalgia Epilepsy Back pain *including indications specifically reported as herpes zoster, complex regional pain syndrome, trigeminal neuralgia and peripheral neuropathy by 17.0%, 300 mg by 1.2% and the capsule strength used was not specified in 1.8%. The average daily dose was 201 mg. Of all included patients, 1051 (76.5%) filled in at least one questionnaire, providing data on whether or not they had experienced any possible ADRs. For an overview of the response rate see Figure There were no statistical significant differences found regarding sex, age and daily dosage between patients filling in a questionnaire compared with patients who only registered for the study. At least one possible ADR was reported by 728 (69.3%) patients. The reported ADRs, in absolute number, as well as percentages, are presented in Table 2. 5

92 92 Chapter 5.1 Figure 2. Response rate per questionnaire. Since patients were allowed to fill in a questionnaire even 1. if they had not completed the previous one, the number of collected questionnaires can exceed the 2. number of the patients filling in the previous questionnaire minus the patients who were reported to 3. have stopped the use of pregabalin in that questionnaire st questionnaire 896 patients patients stopped the use of pregabaline nd questionnaire patients patients stopped the use of 14. pregabaline rd questionnaire patients patients stopped the use of 20. pregabaline th questionnaire 400 patients Serious ADRs were reported by 11 patients (1.0%). One ADR was categorised as disabling, 26. three as life-threatening, two required hospitalisation and five were categorised as other. 27. For an overview of these reactions see Table 3. Of the patients reporting an ADR, 401 (55.1%) 28. stopped using pregabalin Signals 31. Events not labelled in the SPC and events already labelled but for other reasons were considered to be of interest (e.g. incidence differences) were analysed on a case-by-case basis Headache 35. Headache was reported 43 times during the study, giving an overall incidence of 4.1%. Sixteen of the reports concerned men and 27 concerned women. In all patients the indication was neuropathic pain or other pain-related symptoms (in one case it was for trigeminal neuralgia, which might be a confounding factor). No patients used pregabalin to treat headache or fibromyalgia. Median time to onset was 2 days, ranging from a few hours to 5 months.

93 Description of the Lareb Intensive Monitoring system 93 Table 2. The reported adverse drug reactions, in absolute number as well as percentages if n> ADR Dizziness Somnolence Feeling drunk Fatigue Weight increased Constipation Headache Dry mouth Disturbance in attention Memory impairment Feeling abnormal Number of patients (%) 265 (25.2) 146 (13.9) 72 (6.9) 68 (6.5) 57 (5.4) 47 (4.5) 43 (4.1) 43 (4.1) 41 (3.9) 33 (3.1) 32 (3.0) Nausea 32 (3.0) 13. Vision blurred 21 (2.1) 14. Increased appetite 20 (1.9) 15. Balance disorder 17 (1.6) Libido decreased Aphasia Oedema Oedema peripheral Confusional state Palpitations Insomnia Abdominal pain upper Paraesthesia 17 (1.6) 16 (.,5) 15 (1.4) 13 (1.2) 12 (1.1) 11 (1.0) 10, (1.0) 10 (1.0) 10 (1.0) In 15 reports the headache resolved without stopping the drug and in 16 reports the drug was discontinued due to the headache. In ten reports the headache disappeared after drug discontinuation Upper abdominal pain Upper abdominal pain was reported ten times, giving an overall incidence of 1.0%. The reports concerned six women and four men. All patients used pregabalin for neuropathic pain and other pain-related symptoms. Two types of latencies were reported. In four cases the abdominal pain manifested itself immediately (latency <1 week) after the start of pregabalin. In these cases the abdominal pain disappeared after cessation of the drug. The other latency was longer, 3-10 weeks. In this group there is no clear temporal relationship between drug use and the reaction. A positive dechallenge was reported in only two of these cases. 5

94 94 Chapter Table 3. An overview of serious adverse drug reactions. Sex, Age Type of Suspected adverse Concomitant Time to onset, Comment seriousness drug reaction medication Action with drug outcome F, 58 Other somnolence, peripheral oedema, phentanyl, bisoprolol, 2 weeks (hoarseness citalopram, irbesartan, 6 weeks) dose not feeling drunk, paracetamol, changed, not recovered dyspnoea, hoarseness diazepam, F, 33 Other fall, somnolence, nicomorphine, syncope, feeling drunk venlaflaxine, F, 63 Life threatening alopecia, cerebrovascular accident F, 65 Hospitalisation balance disorder, memory impairment, upper abdominal pain, anorexia F, 21 Life threatening increased blood pressure (192/121 mmhg), increased heart rate (145 bpm at rest) F, 40 Hospitalisation decreased alertness, impaired memory, tongue swelling, fatigue, dizziness dalteparin, levothyroxine, temazepam, diazepam, omeprazole, naproxen, loperamide, phentanyl, celecoxib unknown, drug withdrawn, patient recovered prednisolon eye dropsalopecia 1 week, CVA 2 months, drug withdrawn, alopecia unknown, CVA left sided paralysis isosorbide-5- mononitrate, ranitidine, ursodeoxycholic acid, sucralphate, amoxicilline/clavulanic acid, verapamil, esomperazole memory impairment and balance disorder 4 days, upper abdominal pain and anorexia 2.5 months, drug withdrawn, not recovered paracetamol/tramadol15 days, drug withdrawn, not recovered clonazepam, perindopril, diclofenac, paracetamol, levothyroxine, omeprazole all events occurred days before the start of pregabalin, drug was withdrawn, not recovered from fatigue and memory impairment, is recovering from all other events alopecia was confined to areas with herpes zoster, reporter is unsure about relation between CVA and pregabalin since the patient also had hypertension normal blood pressure 130/90mmHg the causality is doubtful in this report

95 Description of the Lareb Intensive Monitoring system Table 3. (continued) Sex, Age Type of seriousness Suspected adverse drug reaction Concomitant medication Time to onset, Action with drug outcome F, 62 Life threatening suicidal tendency none reported 15 days, drug withdrawn, not recovered M, 47 Disabling somnolence, forgetfulness citalopram, esomeprazole, etericoxib, dimethylsulphoxide, ginko biloba extract, tramadol, atenolol F, 58 Other numbness, peripheral none reported oedema, increased appetite, fracture in the foot, hyperactivity F, 43 Other weight increase, dizziness, speech disorder, concentration impairment, confusion diclofenac F, 44 Other feeling drunk, rizatriptan concentration impairment, balance difficulty, dizziness 5 days for somnolence, 5 months for forgetfulness, dose not changed, not recovered Comment this case is also described under Signals peripheral oedema, numbness and fracture 4 months, increased appetite and hyperactivity 5 months, dose not changed, not recovered 3 months, dose not the symptoms changed, not recoveredprohibited the patient from driving and working hours, dose reduced, recovered the symptoms prohibited the patient from driving and therefore also working Drug interaction A possible drug interaction was reported four times during the study. Two of these reports concerned an interaction between pregabalin and blood glucose-lowering agents. In total, 83 patients reported an oral antidiabetic drug or insulin as concomitant medication. A female aged 62 years used pregabalin 150 mg once daily for neuropathic pain. Concomitant medication was glimepiride (dose not specified), which had been used for more than 5 years. The patient reported an increased effect of glimepiride on the same day as pregabalin treatment was started. The patient recovered after pregabalin withdrawal. The second report concerned a male patient aged 56 years. He used pregabalin 150 mg twice daily for neuropathic pain. Concomitant medications were diclofenac, oxycodone, enalapril/hydrochlorothiazide, atorvastatin, glimepiride, metformin, insulin aspart and insulin detemir. Four days after initiation of pregabalin treatment the patient experienced hypoglycaemia (glucose levels not provided), 5

96 96 Chapter which led to an adjustment of his insulin dose. Pregabalin was not withdrawn and the patient 2. recovered because of adjustment of his insulin dose Suicidal ideation 5. Two separate patients reported suicidal ideation in their reports. The first report concerned 6. a male aged 46 years. He used pregabalin 75 mg twice daily for the treatment of neuropathic pain. Concomitant medication was morphine. Five days after initiation of pregabalin treatment the patient reported that he experienced suicidal ideation. Two weeks thereafter, 9. pregabalin was withdrawn and the patient was reported to be recovering. The second report 10. concerned a female aged 62 years who used pregabalin 75 mg for neuropathic pain. No 11. concomitant medication was used. Two weeks after initiation of pregabalin treatment and days after withdrawal of the drug the patient reported suicidal tendency. At the time at which 13. the questionnaire was completed, the patient had not recovered from the suicidal tendency Discussion The results of this web-based intensive monitoring study give an overview of not only the 19. safety profile of the drug in daily practice but also capture the characteristics of its users Use of pregabalin in daily practice 22. In this study, the majority of participants (58.0%) were female, which is consistent with the 23. fact that neuropathic pain is more prevalent in females [3]. Age ranged from 11 to 89 years, 24. with four patients in total being younger than 18 years of age. Pregabalin is licensed for 25. patients aged 18 years and over [5], thus showing that pregabalin, although a relatively new 26. drug, is prescribed off-label to younger patients The majority of patients started with the 75 mg capsule, which is in line with the recommended starting dosage (150 mg daily). This dosage can be titrated to 300 mg daily in the first week. It is remarkable that 17 patients started with the 300 mg capsule, which exceeds 31. the recommended starting dose. In this study, pregabalin was used mostly as a treatment 32. for neuropathic pain and only a minority of people used the drug as an anti-epileptic. This is 33. probably due to the fact that there are few treatment options for neuropathic pain, whereas 34. there are many effective drugs on the market for the treatment of epilepsy. Another possibility is that the prevalence of neuropathic pain is higher than the prevalence of epilepsy. Some indications reported are types of pain that do not necessarily fall under the term neuropathic 37. pain. It seems that pregabalin is used as a medication for pain that does not respond to treatment with conventional analgesics such as NSAIDs and opioids.

97 Description of the Lareb Intensive Monitoring system Adverse drug reactions 2. In the Prescription Event Monitoring and the Intensive Medicines Monitoring Programme 3. methodology [16,17] the reported information is treated as adverse events. Although 4. a causality assessment has not been performed on all the information gathered, we have 5. chosen to use the term ADR for the reactions reported because patients are asked only to 6. report symptoms that they believe are associated with the use of pregabalin. The ADRs most 7. frequently reported in this study correspond to the most frequently reported ADRs in preregistration trials [5], as well as in other trials [18,19]. Of the possible ADRs reported via the web-based intensive monitoring system, four are worth additional attention Headache is mentioned as an ADR in the SPC of pregabalin, with an unknown frequency. 12. The incidence of headache in this LIM study was 4.1%, indicating that headache might be 13. a commonly occurring ADR. In a study where the efficacy of pregabalin in the treatment of 14. generalised anxiety disorder was investigated, headache occurred in 13.5% of participants in 15. an open label phase, in the double-blind phase of the study the incidence of headache did 16. not differ between the pregabalin and placebo groups [19]. Results from our study show that 17. latency seems to be short and in some cases the headache resolves without withdrawing the 18. drug, however in other cases recovery was seen only after drug discontinuation Abdominal pain is not mentioned in the SPC of pregabalin. During this study, ten reports 21. were received describing this association. In four of the ten reports, latency was short (<1 22. week) and a positive dechallenge was reported In this study, there were two reports of suicidal ideation. Antiepileptic drugs have been associated with suicidal behaviour and ideation. A meta-analysis performed by the US FDA shows that the use of antiepileptic drugs increases the risk of suicidal behaviour or ideation 27. (odds ratio 1.8, 95% CI ). The risk is greater in patients with epilepsy than in patients 28. using these drugs for other indications [20]. This possible ADR should be closely monitored, 29. in particular since its primary use seems to be for pain-related symptoms instead of epilepsy, 30. which is the main indication for other antiepileptic drugs In the SPC of pregabalin, hypoglycaemia is mentioned as a rare ADR to pregabalin, however, 33. a possible interaction between pregabalin and blood glucose-lowering drugs is not mentioned [5]. In this study, two reports were found in which hypoglycaemia occurred when pregabalin was added to an already existing treatment with glucose-lowering drugs. In a 36. meta-analysis including 1510 patients in which the efficacy of pregabalin in the treatment 37. of painful neuropathic peripheral neuropathy was investigated, this possible interaction was not found [18]. A literature search via PubMed did not yield any further information concerning a possible interaction between pregabalin and oral blood glucose-lowering drugs. This 5

98 98 Chapter association is worth further investigation, as our study indicates that the main indication for 2. pregabalin use is neuropathic pain. One can assume that in some of these users neuropathic 3. pain has been caused by diabetes mellitus. Since patients with diabetic neuropathy might 4. be prescribed pregabalin, it is important to investigate if pregabalin interacts with blood 5. glucose-lowering drugs in order to prevent hypoglycaemia Strengths and weaknesses 8. Web-based intensive monitoring is an observational prospective cohort study. All patients 9. prescribed pregabalin can be included in the study, there are no limiting inclusion or exclusion criteria compared with clinical trials. A web-based intensive monitoring system will therefore give a picture of the use of pregabalin and its ADRs as it is in daily practice The pharmacy 14. Eligible patients are identified in the community pharmacy, making it possible to monitor 15. pregabalin prescribed by both general practitioners and specialist doctors in outpatient settings. In the Netherlands, pharmacists play an important role in pharmacovigilance [21]. Fifty percent of all Dutch pharmacies are participating in LIM, however not all of them are active 18. participants. With this number it is assumed that patients going to these pharmacies are a 19. representative sample of the Dutch population. Data on pregabalin prescription during the 20. inclusion period were provided by the Dutch Foundation for Pharmaceutical Statistics [22]. 21. During the inclusion period there were first prescriptions of pregabalin in all Dutch 22. pharmacies. Assuming that half of these first prescriptions were filled in a LIM participating 23. pharmacy, approximately 6.6% of the patients given a first pregablin prescription in this time 24. period chose to participate in LIM. Since we have no information about the patients who did 25. not participate, it is not possible to know if the patients eventually participating in the study 26. are representative of all patients using pregabalin. This is a matter that has to be addressed 27. in further research The patient 30. The role of the patient in pharmacovigilance has been strengthened in recent years, and using patients as a source of information in spontaneous reporting has proven to be successful [23,24]. In this study it was chosen to use the patient as a source of information. This has the 33. advantage that ADRs are reported by the person who has actually experienced the reaction In the study, patients were asked to report reactions that they believed were caused by the 36. drug. Thus, it is possible that patients did not report reactions that they did not believe to be 37. attributed to the drug. However, patients do not have any professional filter in what they report, compared with health professionals, therefore underreporting would be less of a problem with patients as reporters. A much given criticism on using patients as a source

99 Description of the Lareb Intensive Monitoring system of information is that it is not medically confirmed and that it can sometimes be difficult to 2. interpret the symptoms reported. However, it is always possible to ask the patient s permission to contact his/her general practitioner for further information By using the patient as the source of information, it is possible that people who are retired, or 6. for other reasons are not pursuing a professional career, are more willing to participate in the 7. study because they have more spare time. Because the system is web-based, patients who do 8. not have access to the Internet or are not familiar with using the Internet will be underrepresented in the sample, this would probably be more prominent in the older age categories Statistics from 2008 show that 86% of Dutch households have access to the Internet at home 11. [25]. It is difficult to draw conclusions to what extent age contributes to the selection bias but 12. because the population using pregabalin has an average age of 54.5 years, one can assume 13. that the impact of older people not being familiar with the Internet would be greater than 14. the number of people having little time to participate in research. It is to be expected that in 15. forthcoming years the elderly will increasingly use the Internet and that this bias will be less 16. important Another factor possibly influencing the willingness for a patient to participate in a study 19. investigating ADRs can be their experiences of ADRs in the past. If a patient has experienced 20. an ADR in the past that had implications for their well-being, they might be more prone to 21. participate in this study. However, susceptibility to ADRs in the past might be a predictor 22. of susceptibility to ADRs in the future. The data collected could therefore give too high an 23. incidence of ADRs because there are more people prone to ADRs participating in the study Of the 1373 patients registering for the study, 1051 filled in at least one questionnaire. Of 26. these patients, 69.3%reported an ADR. This number is quite high and it is possible that patients who did experience an ADR are more inclined to fill in a questionnaire compared with those not experiencing any ADRs. Because the patient is the source of information, patients 29. with severe illness will be underrepresented because they are not able to fill in the questionnaires themselves Conclusions This study indicates that pregabalin is a relatively safe drug, as used by patients in daily practice over a period of 6 months. It is important when interpreting these results to bear in mind that these data were gathered using information from only a small proportion of patients using this drug during their first 6 months of use. 5

100 100 Chapter Eleven patients (<1.0%) out of the total population experienced a serious ADR. Only two patients were hospitalised because of their serious ADR. The most frequently reported reactions in LIM correspond to the reactions that were most frequently reported during clinical trials Our study demonstrated that with a web-based intensive monitoring system it is possible to 6. gather information that can contribute to greater knowledge about the characteristic of the 7. reported reactions, allowing for an estimation of the incidence and information about latencies and time course of the reaction, as was the case with headache. It also has the ability to identify new signals, such as abdominal pain and possible interaction with oral anti-diabetics

101 Description of the Lareb Intensive Monitoring system References 1. Jensen TS, Gottrup H, Sindrup SH, et al. The clinical picture of neuropathic pain. Eur J Pharmacol 2001; 429: Attal N, Cruccu G, Haanpaa M, et al. EFNS guidelines on pharmacological treatment of neuropathic pain. Eur J Neurol 2006; 13: Dieleman JP, Kerklaan J, Huygen FJ, et al. Incidence rates and treatment of neuropathic pain conditions in the general population. Pain 2008; 137: Collins SL, Moore RA, McQuay HJ, et al. Antidepressants and anticonvulsants for diabetic neuropathy and postherpetic neuralgia: a quantitative systematic review. J Pain Symptom Manage 2000; 20: EPAR Lyrica. Committee for Medicinal Products for Human Use (CHMP). Available via ema.europa.eu/docs/en_gb/document_library/epar_-_product_information/human/000546/ WC pdf Accessed Dec 1, Taylor CP, Angelotti T, Fauman E. Pharmacology and mechanism of action of pregabalin: the calcium channel alpha2-delta subunit as a target for antiepileptic drug discovery. Epilepsy Res 2007; 73: Stricker BH, Psaty BM. Detection, verification, and quantification of adverse drug reactions. BMJ 2004; 329: Härmark L, van Grootheest AC. Pharmacovigilance: methods, recent developments and future perspectives. Eur J Clin Pharmacol 2008; 64: Raine JM Risk management - a European Regulatory View. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 10. Hazell L, Shakir SA. Under-reporting of adverse drug reactions: a systematic review. Drug Saf 2006; 29: Waller PC, Evans SJ. A model for the future conduct of pharmacovigilance. Pharmacoepidemiol Drug Saf 2003; 12: Härmark L, Kabel JS, van Puijenbroek EP et al. Web-Based Intensive Monitoring, a New Patient Based Tool for Early signal Detection. [Abstract] Drug Saf 2006; 29: Oosterhuis I, Härmark L, van Puijenbroek EP, et al. Lareb Intensive Monitoring: an interim analysis. [Abstract] Drug Saf 2007; 30: van Grootheest AC, Härmark L, Oosterhuis I, et al. Lareb Intensive Monitoring, a web based system for monitoring ADRs in the postmarketing phase. [Abstract] Pharmacoepidemiol Drug Saf 2007; 16: S Z-Index. Available via Accessed Nov 15, Shakir SAW. PEM in the UK. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 17. Coulter DM. The New Zealand Intensive Medicines Monitoring Programme. Pharmacoepidemiol Drug Saf 1998; 7: Freeman R, Durso-Decruz E, Emir B. Efficacy, safety, and tolerability of pregabalin treatment for painful diabetic peripheral neuropathy: findings from seven randomized, controlled trials across a range of doses. Diabetes Care 2008; 31: Feltner D, Wittchen HU, Kavoussi R, et al. Long-term efficacy of pregabalin in generalized anxiety disorder. Int Clin Psychopharmacol 2008; 23: Statistical review and evaluation: anti-epileptic drugs and suicidality. Food and Drug Administration. Available via Safety/PostmarketDrugSafetyInformationforPatientsandProviders/UCM pdf Accessed Feb 22, van Grootheest AC, van Puijenbroek EP, de Jong-van den Berg LT. Contribution of pharmacists to the reporting of adverse drug reactions. Pharmacoepidemiol Drug Saf :

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103 Chapter 5.2 Intensive monitoring of duloxetine, results from a web-based intensive monitoring study Härmark L van Puijenbroek E van Grootheest K Submitted

104 104 Chapter Abstract Introduction 4. Duloxetine (Cymbalta ) is a serotonin (5-HT) and norepinephrine (NE) re-uptake inhibitor 5. indicated for the treatment of depression, diabetic peripheral neuropathic pain and generalised anxiety disorder. The aim of this study is to gain insight in the user- and safety profile of duloxetine in daily practice, reported by patients via a web-based intensive monitoring 8. system during their first 6 months of use Methods 11. First time users of duloxetine were identified through the first dispensation signal in the 12. pharmacy. Patient demographics and information about drug use and adverse drug reactions (ADRs) were collected through electronic questionnaires sent 2 and 6 weeks, 3 and months after start of duloxetine. ADRs were quantified and signal detection was performed 15. on a case by case basis Results patients registered for the study, 69.1% was female. Depression was the main indication patients (76.1%) filled in at least one questionnaire and 78.9% of these reported an ADR. 20. Serious ADRs were reported by 4 patients. Three new signals were identified, amenorrhea, 21. shock-like paraesthesias and micturition problems Conclusions 24. Web-based intensive monitoring is an observational prospective cohort study mirroring the 25. use and ADRs of duloxetine in daily practice. This study indicates that duloxetine is a relatively 26. safe drug as used by patients during six months in daily practice, but the aforementioned 27. signals need to be evaluated in more detail

105 Description of the Lareb Intensive Monitoring system Introduction Duloxetine (Cymbalta ) is registered in the European Union for the treatment of major depressive disorder, diabetic peripheral neuropathic pain and generalised anxiety disorder [1] It is a serotonin (5-HT) and norepinephrine (NE) re-uptake inhibitor with almost equal affinity 6. for binding to NE and 5-HT transport sites, with little affinity for other receptors such as muscarinic, histaminergic, alpha-adrenergic, dopaminergic, serotonergic and opioid receptors, suggesting that it might have a more benign adverse drug reaction profile as compared to 9. other anti-depressive drugs [2] The efficacy and safety of duloxetine for the treatment of the registered indications were 12. investigated in clinical trials [1,3-6]. Clinical trials are primarily designed to prove efficacy. 13. For detection of adverse drug reactions (ADRs) clinical trials have a number of limitations 14. including a homogenous population which does not mirror the target population concerning age, gender, comorbidity and co-medication, limited sample size and a limited duration [7]. Because of these limitations it is essential to monitor the safety of duloxetine in clinical 17. practice in order to get a clear picture of its ADR profile Spontaneous reporting has been the backbone of pharmacovigilance ever since the thalidomide 20. disaster 50 years ago. In a spontaneous reporting system healthcare professionals and increasingly also patients can submit reports of ADRs. These reports can lead to the detection of a new signal. A signal is defined by the WHO as Reported information on a possible causal relationship between an adverse event and a drug, the relationship being unknown or incompletely documented [8]. Spontaneous reporting is a passive form of drug surveillance, where one is 25. dependent on the willingness of healthcare professionals and patients to report. In order to gain 26. more information about a certain drug, a more active form of drug surveillance is necessary [9,10] In 2006, the Netherlands Pharmacovigilance Centre Lareb, which is responsible for the collection and analysis of spontaneous reports in the Netherlands, introduced a web-based inten sive monitoring system called Lareb Intensive Monitoring (LIM). LIM is a non-interventional 31. prospective observational cohort which follows users of certain drugs during a certain period 32. of time. In LIM, patients eligible for inclusion are identified in community pharmacies through 33. a first dispensation signal. The patient receives information about the study and if willing to 34. participate, the patient registers online. After registration, questionnaires are sent by 35. at specific points in time. In these questionnaires questions are asked about patient characteristics, drug use and possible ADRs. The LIM methodology has been described in more detail elsewhere [11,12]. The aim of this study is to gain insight in the user- and safety profile of duloxetine in daily practice, reported by patients via a web-based intensive monitoring system during their first 6 months of use. 5

106 106 Chapter Method Study population 4. The population consisted of first time users of duloxetine, identified through the first dispensation signal in intensive monitoring participating pharmacies between November 1, and April 30, Data were collected between November 1, 2006 and October 31, Data collection 9. When registering for the study, patients were asked to provide an address which was 10. used for all further correspondence. During registration, patient characteristics and information about duloxetine use and concomitant drug use were collected. After registration, the patient received questionnaires by 2 and 6 weeks, 3 and 6 months after start of the 13. drug where information about possible ADRs due to duloxetine use was collected. If the 14. patient did not fill in the questionnaire immediately, a reminder was sent five days later. If a 15. questionnaire was not completed four weeks after the reminder, the patient was considered 16. lost to follow up for that questionnaire. If the patient stopped the use of duloxetine, or in the 17. event of death of the patient or if the patient actively chose to stop his participation in the 18. study, the patient did not receive any more questionnaires. The participation in the study was 19. then considered to be completed The indication and ADRs were coded using the Medical Dictionary for Regulatory activities 22. (MedDRA) on a Lower Level Term (LLT) level by a qualified assessor [13]. Study drug and 23. co-medication were coded using the Dutch Drugdictionary (Z- index) [14]. If a report was 24. reported as serious according to the CIOMS criteria which includes (prolongation of ) hospitalisation, life-threatening events, events leading to death, disabling events, congenital abnomalities and other medically significant events [15], and also assessed as serious by the 27. assessor, a copy of the report was exported to the national database containing all spontaneous reports, where it was handled according to the regulations regarding serious adverse drug reaction reports. The workflow of Lareb Intensive Monitoring has been described in 30. more depth elsewhere [12] Analysis 33. On gender, age, drug strength used, daily dose and past use of drugs for depression and 34. neuropathic pain, the frequencies were calculated. The number of patients reporting a 35. possible adverse drug reaction, the percentage of serious adverse drug reactions and the 36. incidence of different adverse drug reactions were calculated. Even though a patient could 37. report the same adverse drug reactions in all four questionnaires, one specific reaction was only counted once for each individual when calculating incidences. The possible adverse drug reactions were divided into labeled or not labeled according to the European Public

107 Description of the Lareb Intensive Monitoring system Assessment Report (EPAR) [1]. Reactions that were not labeled and reactions that were labeled but for other reasons were considered to be of potential interest (selection done by one pharmacist (LH) and one physician (EP)) were analysed on a case by case basis. Labeled 4. reactions were considered to be of interest if differences were found between the cohort and 5. the EPAR A comparison between the patients who only filled in the registration form and the patients 8. who provided data on whether or not they had experienced any possible adverse drug 9. reactions was made on basis of age, gender and daily dosage. A p value of 0.05 or below 10. was considered statistical significant. Data were retrieved using Microsoft Access. Statistical 11. analysis was performed using SPSS version Results Between November 1, 2006 and April 30, 2008, 398 patients registered for the duloxetine 17. study. 69.1% of these was female. The average age was 47.0 (SD 12.3) years, ranging from to 82 years. 66.7% of the patients used duloxetine for depression, 16.1% for neuropathic pain 19. and 4.3% for fibromyalgia % of the population cohort used duloxetine capsule 30 mg and 16.6 % the 60 mg capsule. In 3.0% of the cases the capsule strength used was not specified. The average daily dosage was 49.1 mg. 239 patients answered the question if they had used any previous drugs 24. for the treatment of depression and/or neuropathic pain. Of the patients who answered the 25. question, 97 (40.6%) patients had used other drugs for the same indication in the past. The 26. most commonly used drugs were SSRIs including venlafaxine (55 patients), tricyclic antidepressants (13), other antidepressants (12) and benzodiazepines (10) Of the 398 patients that registered for the study, 303 patients (76.1%) filled in at least one 30. questionnaire. Since patients were allowed to skip questionnaires, the number of the respondents to the first questionnaire is lower than the total number of respondents. For an over view of the response rate see Figure 1. There were no statistical significant differences found 33. regarding sex, age and daily dosage between patients filling in a questionnaire compared to 34. the patients who only registered for the study (78. 9%) of the patients who filled in at least the first questionnaire reported an adverse 37. drug reaction. In total 152 different adverse drug reactions were reported. The reported adverse drug reactions, in absolute number as well as percentages, are presented in Table 1. 5

108 108 Chapter Figure 1. Response rate of the questionnaires Questionnaires sent st questionnaire 256 respondents 2 nd questionnaire 236 respondents 3 rd questionnaire 190 respondents 4 th questionnaire 154 respondents Serious adverse drug reactions were reported by 4 patients (1.3%). One was categorised as life threatening, two required hospitalisation and one patient died. For an overview of these reactions see Table 2. Of the 71 ADRs that were reported two or more times with the LIM system, 52 are explicitly mentioned in the EPAR of duloxetine. Signals Events not labeled in the EPAR and events already labeled and for other reasons considered to be of interest, e.g. incidence differences, were analysed on a case by case basis. Amenorrhoea In the LIM cohort two cases of amenorrhea were reported. The first report concerned a female aged 49 who experienced amenorrhea 20 days after the start of duloxetine for the treatment of neuropathic pain. The menstruation returned after withdrawal of duloxetine. Concomitant medication was several inhalation drugs (salbutamol/ipratropium, budesonide, formoterol), montelukast, esomeprazole, oxycodone and calcium carbonate/colecalciferol. The second report concerned a female aged 45 who experienced amenorrhea just after the start of duloxetine for the treatment of depression. After missing two periods, the menstruation returned without change in duloxetine dose. No concomitant medication was reported.

109 Description of the Lareb Intensive Monitoring system 109 Table 1. The reported adverse drug reactions, in absolute number as well as percentages if n> ADR Nausea Dry mouth Dizziness Hyperhidrosis Headache Somnolence Constipation Fatigue Insomnia Sleep disorder Decreased appetite Number of patients Percentage of patients Diarrhoea Libido decreased Micturition disorder Malaise Yawning Anxiety Weight increased Restlessness Erectile dysfunction Myalgia Vision blurred Abdominal pain upper Paraesthesia Restless legs syndrome Abnormal dreams Tremor Pollakiuria Feeling abnormal Tinnitus Dysgeusia Palpitations Shock-like paraesthesia In the EPAR the general term paraesthesia is mentioned as an ADR. In the LIM cohort two reports on electric shock sensation, a special form of paraesthesia, were received. The first report concerned a male aged 35 who experienced small electric shocks in the head three days after starting duloxetine for the treatment of depression. Upon reducing and eventually stopping the drug, the patient recovered. Concomitant medication was lormetazepam and 5

110 110 Chapter Table 2. An overview of serious adverse drug reactions. Sex, Age Type of seriousness Suspected adverse drug reaction F, 55 Hospitalisation suicide attempt, dry mouth, constipation F, 54 Hospitalisation constipation, headache, loss of appetite Concomitant medication zopiclone, propranolol, clorazepate F, 28 Life threatening suicidal ideation, impulsive behaviour, feeling sad, restlessness, paranoid reaction, compulsions oxazepam M, 54 Death hyperhidrosis, dehydration, electrolyte disturbances, coma, death Time to onset, Action with drug outcome 27 days for the suicide attempt, a few days for the dry mouth and Comment patient used duloxetine for depression, constipation, drug was treatment with withdrawn, patient is ECT has been recovering initiated quetiapine, oxazepam 26 days for the loss of appetite, 4 days for the constipation, a few hours for the headache, drug was withdrawn, patient is none reported patient used duloxetine for depression, hospitalisation was due to drug use, however recovered from the loss it is not clear of appetite, has not what the specific recovered from the two reason for the other events hospitalisation is all reactions occurred patient used in the first month, drug duloxetine for dose was not changed, depression The outcome of the suicidal ideation and the restlessness in unknown, patient has recovered from all other events one month, patient died patient used duloxetine for depression death was reported by the patient s partner losartan/hydrochlorothiazide. The second report concerned a female aged 36 who experienced a voltage in the brain on the day of starting duloxetine treatment for depression. The patient recovered upon discontinuation of duloxetine. Comcomitant medication was oxazepam and ethinylestradiol/gestoden. Micturition problems The EPAR of duloxetine mentions urinary disorders as uncommon (frequency 0.1-1%), except dysuria (frequency 1-10%). In the LIM cohort urinary disorders were reported more frequently, a total of 17 patients (5.6%) reported urinary disorders. 10 patients reported urinary hesitation, sometimes in combination with a decreased urine flow. 7 patients reported an increase

111 Description of the Lareb Intensive Monitoring system in the micturition frequency. Of the 17 patients with urinary disorders, 11 were men and 6 2. were women. In 5 cases a positive dechallenge was reported, in another 5 cases the problems 3. seem to disappear while continuing duloxetine treatment. In 4 cases the drug was continued 4. and the patient did not recover. In 2 cases duloxetine was withdrawn, but the patient had not 5. (yet) recovered. In one case the outcome was not reported Discussion Web-based intensive monitoring gives an overview of the safety profile of duloxetine in daily 11. practice and it captures the characteristics of its users as well User characteristics 14. In the study the majority (69.1%) of participants was female which is consistent with the 15. fact that both depression and neuropathic pain is more prevalent in female [16,17]. The age 16. ranged from years with two patients below 18 years of age. Duloxetine is registered 17. for use in adults [1] and this shows that duloxetine, although it is a relatively new drug, is offlabel prescribed to younger patients. The majority of patients started with the 30 mg capsule and the average daily dosage was 49.1 mg, which is low compared to the recommended 20. starting dosage of 60 mg once daily for the treatment of depression and diabetic peripheral 21. neuropathic pain [1]. In this study duloxetine is used mostly as a treatment for depression, 22. only 16.1% of the patients used duloxetine for neuropathic pain. This is quite surprising since 23. there are many treatment options for depression on the market at the time of introduction 24. of duloxetine but few drugs registered for the treatment of neuropathic pain. However, many 25. of the patients who received duloxetine stated that they had used other drugs for the same 26. indication in the past, and SSRIs, together with TCAs and other antidepressant drugs where 27. the most frequently mentioned, indicating that the patients who receive duloxetine did not 28. respond to treatment with other antidepressant drugs. Another possibility is that the prevalence of depression is higher than the prevalence of neuropathic pain. It is surprising that almost 5% stated that they used duloxetine for the treatment of fibromyalgia, even though 31. this is not a registered indication in the European Union. In the US however, duloxetine is 32. indicated for the treatment of fibromyalgia [18]. Just as the intensive monitoring study of 33. pregabalin, which is another drug indicated for the treatment of neuropathic pain, showed 34. [12], it seems that duloxetine is off-label prescribed to patients with fibromyalgia in the 35. Netherlands Adverse drug reactions The adverse drug reactions most frequently reported in this study correspond to the most frequently reported adverse drug reactions in pre-registration trials, as well as in other trials 5

112 112 Chapter [2-6,19,20]. The frequencies obtained with the LIM system are similar to those stated in the 2. EPAR, except in a few cases. Of the possible adverse drug reactions reported via the webbased intensive monitoring system, three are worth additional attention Two reports of amenorrhea were reported. Even though the age of the patients (49 and years old respectively) suggest that the amenorrhea could be due to the women entering 7. the menopause, the absence of other symptoms relating to the menopause as well as the 8. positive dechallenge in one case supports a causal relationship. Amenorrhea is not listed in 9. the EPAR of duloxetine, unspecified menopausal symptoms are, but can be explained from 10. a mechanistic point of view as it is a clinical manifestation of hyperprolactinaemia which 11. is mentioned in the EPAR and is caused by raised serotonin levels, which is a modulator of 12. prolactin secretion [21] Shock-like paraesthesia is sensory perceptions of short electric low-voltage discharges, 15. usually localised in the brain. In addition to these two reports, the Netherlands Pharmacovigilance Centre received 3 reports of shock-like paraesthesia through their spontaneous reporting system, strengthening this signal [22]. Shock-like paraesthesia has been described 18. by the use of SSRIs [23,24]. The symptoms usually occur during drug withdrawal but have also 19. been described with ongoing therapy. As it might not always be recognised as an ADR by 20. patients and healthcare professionals, it is worth paying extra attention to it The EPAR of duloxetine mentions urinary disorders except dysuria as uncommon (frequency %). In the LIM cohort urinary disorders were reported more frequently, a total of patients reported urinary disorders, mainly urinary hesitation and increased micturition 25. frequency. It is notable that 11 of the 17 patients (64.7%) with urinary problems were men, 26. since only 30% of the cohort are men. Only one of the men reported the use of drugs for 27. treatment of benign prostate hypertrophy, which might be a confounding factor for the urinary disorders. The low frequency in the EPAR is surprising, especially for urinary hesitation, since duloxetine is registered under another brand name (Yentreve ) which is indicated for 30. stress urinary incontinence [25] Strengths and weaknesses 33. Web-based intensive monitoring is an observational prospective cohort study mirroring the 34. use and ADRs of duloxetine in daily practice as compared with clinical studies which have 35. strict inclusion and exclusion criteria Eligible patients are identified in community pharmacy, however not all patients eligible for inclusion are participating in the study. Data on duloxetine dispensation during the inclusion period were provided by the Dutch Foundation for Pharmaceutical Statistics [26] and the LIM

113 Description of the Lareb Intensive Monitoring system response rate was 3.5% of all patients receiving a first prescription of duloxetine during the inclusion period. This might contribute to non-response bias. There is no information about the patients who did not participate; it is therefore not possible to know if the patients eventually 4. participating in the study are representative for all patients using duloxetine. Non-response 5. bias in a LIM study has been investigated and it showed that patients participating in LIM are 6. in general younger and use a little less co-medication than non-responders [27]. However it 7. cannot be assumed that younger patients experience less ADRs than older patients [28,29] In this study it was chosen to use the patient as a source of information. This has the advantage that adverse drug reactions are reported by the person who has actually experi enced the reaction. Since patients do not have any professional filter in what they report, 12. as compared to healthcare professionals, it enhances the chance to find new ADRs which 13. would not be considered as ADRs, and therefore not reported by healthcare professionals. 14. For example, shock-like paraesthesias is an ADR that is primarily reported by patients as compared to healthcare professionals at the Netherlands Pharmacovigilance Centre Lareb. Since the patient is the source of information, it might be difficult to obtain information about fatal 17. outcomes. In this study we received one report with a fatal outcome, and this was reported 18. by the patient s wife, showing that patient-based tools also can collect information about 19. fatal outcomes It is surprising that almost 80% of the patients who filled in a questionnaire reported an ADR. 22. This is a rather high percentage and it is possible that patients who experienced an ADR were 23. more inclined to fill in a questionnaire compared to those not experiencing any ADRs but 24. analyses showed no difference in gender, age and daily duloxetine dosis between the groups. 25. Another reason for the high percentage might be channeling. 40% of the participants had 26. in the past used one or more drugs for the same indication. It is not known if they switched 27. because lack of efficacy or because of ADRs. If the latter were the reason for switching, it can 28. be assumed that these patients might have an increased susceptibility to ADRs as compared 29. to others Conclusion 32. This study indicates that the ADR profile of duloxetine as reported by patients during six 33. months in daily practice is similar to the profile described in the EPAR of duloxetine [1]. Four 34. patients (1.3%) experienced a serious adverse drug reaction, of which one fatal due to electrolyte disturbances. In addition three signals of a possible new adverse drug reaction were identified namely amenorrhoea, shock-like paraesthesias and urinary disorders which need 37. to be further evaluated in more detail. Web-based intensive monitoring shows to be a useful and efficient method to get insight into the behavior of new drugs in daily practice. 5

114 114 Chapter References 1. EPAR Cymbalta. European Medicines Agency Available via docs/en_gb/document_library/epar_-_product_information/human/000572/wc pdf Accessed Feb 15, Raskin J, Goldstein DJ, Mallinckrodt CH, et al. Duloxetine in the long-term treatment of major depressive disorder. J Clin Psychiatry 2003; 64: Detke MJ, Lu Y, Goldstein DJ, et al. Duloxetine 60 mg once daily dosing versus placebo in the acute treatment of major depression. J Psychiatr Res 2002; 36: Detke MJ, Lu Y, Goldstein DJ, Hayes JR, et al. Duloxetine, 60 mg once daily, for major depressive disorder: a randomized double-blind placebo-controlled trial. J Clin Psychiatry 2002; 63: Goldstein DJ, Mallinckrodt C, Lu Y, et al. Duloxetine in the treatment of major depressive disorder: a double-blind clinical trial. J Clin Psychiatry 2002; 63: Goldstein DJ, Lu Y, Detke MJ, et al. Duloxetine in the treatment of depression: a double-blind placebo-controlled comparison with paroxetine. J Clin Psychopharmacol 2004; 24: Stricker BH, Psaty BM. Detection, verification, and quantification of adverse drug reactions. BMJ 2004; 329: Safety of Medicines A guide to detecting and reporting adverse drug reactions. WHO Available via Accessed Feb 15, Härmark L, van Grootheest AC. Pharmacovigilance: methods, recent developments and future perspectives. Eur J Clin Pharmacol 2008; 64: Härmark L, van Grootheest AC. Web-based Intensive Monitoring, from passive to active drug surveillance. Expert Opin Drug Saf 2012; 11: Härmark L, van Puijenbroek E, van Grootheest K. Longitudinal monitoring of the safety of drugs by using a web-based system: the case of pregabalin. Pharmacoepidemiol Drug Saf 2011; 20: Härmark L, van Puijenbroek E, Straus S, et al. Intensive Monitoring of Pregabalin, Results from an Observational, Web-Based, Prospective Cohort Study Using Patients as a Source of Information. Drug Saf. 2011; 34: MedDRA and MSSO. Available via Accessed Feb 15, Z-Index. Available via z-index nl Accessed Feb 15, International reporting of adverse drug reactions. Council for International Organisations of Medical Sciences working group report. World Health Organisation, Geneva, Dieleman JP, Kerklaan J, Huygen FJ, et al. Incidence rates and treatment of neuropathic pain conditions in the general population. Pain 2008; 137: Nolen-Hoeksema S, Girgus JS. The emergence of gender differences in depression during adolescence. Psychol Bull 1994; 115: Micromedex. Available via Accessed Feb 15, Pangallo BA, Zhang Q, Desaiah D, et al. Long-term safety of duloxetine during open-label compassionate use treatment of patients who completed previous duloxetine clinical trials. Curr Med Res Opin 2010; 26: Gartlehner G, Thaler K, Hansen RA, et al. The general and comparative efficacy and safety of duloxetine in major depressive disorder: a systematic review and meta-analysis. Drug Saf 2009; 32: Torre DL, Falorni A. Pharmacological causes of hyperprolactinemia. Ther Clin Risk Manag 2007; 3:

115 Description of the Lareb Intensive Monitoring system Duloxetine and electric shock-like sensations. Netherlands Pharmacovigilance Centre Lareb. Available via Accessed Feb 15, de Graaf L, van Puijenbroek EP. Serotonin reuptake inhibitors and shocklike paresthesia. J Clin Psychiatry 2003; 64: Frost L, Lal S. Shock-like sensations after discontinuation of selective serotonin reuptake inhibitors. Am J Psychiatry 1995; 152: EPAR Yentreve. European Medicines agency Available via docs/en_gb/document_library/epar_-_product_information/human/000545/wc pdf Accessed Feb 15, Dutch Foundation for Pharmaceutical Statistics. Available via Accessed Feb 15, Härmark L, Huls H, de Gier H, et al. Non-response in a pharmacy and patient based intensive monitoring system, a quantitative study on non-response bias and reasons for non-response. Submitted. 28. Begaud B, Martin K, Fourrier A, et al. Does age increase the risk of adverse drug reactions? Br J Clin Pharmacol 2002; 54: Gurwitz JH, Avorn J. The ambiguous relation between aging and adverse drug reactions. Ann Intern Med 1991; 114:

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117 Chapter 5.3 Longitudinal monitoring of the safety of drugs by using a web-based system: the case of pregabalin Härmark L van Puijenbroek E van Grootheest K Pharmacoepidemiology and Drug Safety 2011; 20:591-7.

118 118 Chapter Abstract Purpose 4. Information about the time course of adverse drug reactions (ADRs) is often lacking. If this 5. information would be available, it could help increase patient s adherence to drugs when 6. experiencing an ADR. The aim of this study was to demonstrate how a web-based intensive 7. monitoring system using the patient as a source of information can be used to gather longitudinal safety data of a drug. In this study, pregabalin was used as an example Methods 11. First-time users of pregabalin were approached in Dutch pharmacies between August 1, and January 31, After online registration, patients received questionnaires by weeks, 6 weeks, 3 months and 6 months after the start of the drug use. Data on patient 14. characteristics, drug use and ADRs were collected and analysed Results 17. A total of 1373 patients registered for the pregabalin study. Of these patients, 1051 (76.5%) 18. filled in at least one questionnaire. On an aggregated level, the ADR profile remained relatively 19. stable over time. Incidence densities showed that the five most frequently reported reactions 20. occurred early in the treatment. Initially, the majority of the patients did not undertake any 21. action when experiencing an ADR. Recovery did not seem to be completely dependent of 22. drug cessation Conclusions 25. With web-based intensive monitoring, it is possible to study the time course of ADRs. This 26. method can be a valuable addition to pharmacovigilance because it can generate other 27. types of information as compared with spontaneous reporting and other intensive monitoring methodologies

119 Description of the Lareb Intensive Monitoring system Introduction For a pharmacological intervention to be successful, the right drug has to be prescribed for 4. the right condition in the right patient. However, these criteria are not the only things necessary to ensure that a patient benefits from the drug. Patient adherence, the extent to which patients take medications as prescribed by their healthcare provider, is essential to achieve 7. the intended effect [1]. Studies have shown that the occurrence of adverse drug reactions 8. (ADRs) or the fear thereof is of great importance when it comes to a patient s adherence [2-4]. 9. To increase adherence, it is important to have access to information about ADRs. Information 10. about time to onset of the ADR, how long it persists and if it disappears spontaneously or 11. not can help to motivate the patient to be adherent to their medication when experiencing 12. an ADR Traditionally, medical doctors and in some countries also pharmacists have been the main 15. source of information in pharmacovigilance [5]. In a spontaneous reporting system, doctors 16. and pharmacists provide mainly cross-sectional information about the ADR, that is, the status 17. of the ADR at the time of reporting. In a few cases, follow-up information is provided, but 18. this is not the case in all reports because reporting as well as providing follow-up information is a time-consuming task for the healthcare professional. Spontaneous reporting was not developed to gather the information mentioned previously and is therefore not able to 21. capture it. To fill this gap, new methods need to be developed In recent years, the patient is getting more involved in drug safety. A number of countries 24. around the world have introduced patient reporting to their spontaneous reporting systems, 25. and the experiences so far are favourable [6,7]. The new European pharmacovigilance legislation underpins the role of consumer reporting by making it mandatory. As patient involve ment increases in drug safety, patients become an important new source of information 28. about the safety of a drug In the Netherlands, the Netherlands Pharmacovigilance Centre Lareb has been responsible 31. for the collection and analysis of spontaneous reports since In 2006, a web-based intensive monitoring system, called Lareb Intensive Monitoring (LIM) was introduced as a comple ment to the spontaneous reporting system. Intensive monitoring is a non-interventional 34. observational cohort, which can monitor selected drugs over time. The Intensive Medicines 35. Monitoring Programme in New Zealand [8] and the Prescription Event Monitoring in the UK 36. [9] are examples of intensive monitoring programmes. Although the methodology of LIM 37. has similarities with these programmes, it has characteristics that distinguish it from them. The main differences are that the source of information is not the healthcare professional 5

120 120 Chapter but the patient, data are collected at several points in time and the system is web-based. The 2. longitudinal character of data collection makes it possible to study the time course of ADRs Pregabalin is a relatively new drug registered for the treatment of neuropathic pain, as adjuvant therapy in the treatment of epilepsy and for generalised anxiety disorder [10]. It is a gamma-aminobutyric acid analogue and exerts its effects by binding to the α 2 δ subunit of 7. voltage-gated calcium channels, leading to a decreased synaptic release of neurotransmitters [11] The aim of this study was to demonstrate how a web-based intensive monitoring system 11. using the patient as a source of information can be used to gather longitudinal safety data of 12. a drug. In this study, pregabalin (Lyrica, Pfizer, New York, NY) was used as an example Method Lareb Intensive Monitoring identifies first-time users of a drug in a pharmacy by using the 18. first prescription signal. The first prescription signal is generated if the patient has not filled 19. in a prescription of that particular drug in the previous 12 months, based on the information from that particular pharmacy. Patients in the Netherlands are linked to one pharmacy only, which makes it is possible to monitor a patient s drug use. Eligible patients are asked to 22. participate in the study. After online registration, the patient is sent periodic questionnaires 23. per , in which information about drug use and possible ADRs is collected. If the patient 24. has not experienced any ADRs, this will be reported as well [12-14]. The LIM methodology has 25. been described in more detail elsewhere [15] Study population 28. First-time users of pregabalin were approached in Dutch pharmacies between August 1, and January 31, Data were collected between August 1, 2006 and July 31, Data collection 32. Patient characteristics such as gender, birth date, length and weight were asked for. 33. Information about pregabalin use including start date, strength, product code, dosage, 34. administration form and indication was collected. This information was also gathered for 35. all concomitant medication. For a detailed overview of the questionnaires, see Härmark et 36. al [15]. After registration, the patient received questionnaires by 2 weeks, 6 weeks, months and 6 months after the start of the drug use. In these questionnaires, questions about possible ADRs, which were considered to be related to the use of pregabalin, were asked. Furthermore, the seriousness of the reaction according to the Council for International

121 Description of the Lareb Intensive Monitoring system Organisations of Medical Sciences (CIOMS) criteria [16], the start date of the reaction, the 2. action taken after experiencing an ADR, the action taken with pregabalin (stopping/dose 3. reduction/no dose change) and the outcome of the reaction were asked for If the patient did not fill in the questionnaire immediately, a reminder was sent 5 days later. 6. If a questionnaire was not completed, the patient was considered lost to follow-up for the 7. questionnaire. If the patient stopped the use of pregabalin, reasons for stopping were asked. 8. In the event of death of the patient or if the patient actively chose to stop his or her participation in the study, the patient did not receive any more questionnaires. The participation in the study was then considered to be completed on the date the notification was received. 11. Indication and reported ADRs were coded using the Medical Dictionary for Regulatory Activities (MedDRA) terminology. Indication and ADRs were coded on a lower-level term level by a qualified assessor [17]. Study drug and co-medication were coded using the Dutch drug 14. dictionary [18]. If a report was considered to be serious according to the CIOMS criteria, a 15. copy of the report was forwarded to the national database containing all spontaneous reports, where it was handled according to the regulations regarding serious ADR reports [19] Analysis Cohort characteristics 21. Descriptive analysis was performed on the response rate, age, gender, indication for use and 22. daily dose Adverse drug reaction spectrum of pregabalin at different points in time 25. The number of patients reporting an ADR- were grouped per questionnaire and per MedDRA 26. system organ class (SOC). Reactions belonging to the SOC nervous system disorders were, in 27. addition, grouped per questionnaire and per MedDRA preferred term (PT) The absolute number of ADRs per SOC or per PT per questionnaire was divided by the total 30. number of patients who responded to the questionnaire in order to calculate the percentage 31. of patients experiencing the ADR at that specific point in time Additional information on the top five reported adverse drug reactions 34. Incidence densities were calculated for the five most frequently reported ADRs during four 35. different periods (0-2 weeks, 2-6 weeks, 6-12 weeks and weeks). If a patient reported 36. more than one reaction falling into this PT, the latency for the first reaction was used. If the 37. patient did not provide a date on which he or she stopped using pregabalin, it was assumed that the patient stayed in the cohort for as long as he or she kept filling in the questionnaires. The time to onset of the reactions was graphically illustrated as Kaplan-Meier curves. 5

122 122 Chapter Descriptive analysis was undertaken on the action taken with the drug when experiencing 3. an ADR, and the outcome of the reaction. In the analysis of the outcome of the reaction, the 4. total number of answers exceeded the number of patients because one or more answers 5. could be chosen All data were retrieved using MS Access. Statistical analysis was performed using SPSS (SPSS Inc.,Chicago, IL, USA) Results Cohort characteristics 14. A total of 1373 patients registered for the pregabalin study, and 796 (58.0%) of these patients 15. were women. The average age was 54.5 years (standard deviation ±13), ranging from 11 to years. Neuropathic pain was the indication in 85.9% of the cases. The average daily dosage 17. was 201 mg. Of these patients, 1051 (76.5%) filled in at least one questionnaire, 896 filled in 18. the first questionnaire and 737, 544 and 400 filled in the remaining questionnaires Adverse drug reaction spectrum of pregabalin at different points in time 21. In total, 1503 possible adverse drug reactions were reported by 728 patients. Of these patients, 534 reported their first ADR in the first questionnaire, 134 in the second questionnaire, in the third questionnaire and 21 in the last questionnaire. Reactions belonging to the SOC 24. nervous system disorders are the most frequently reported. Figure 1 shows the whole ADR 25. profile for pregabalin per MedDRA SOC. Figure 2 shows the ADR profile for ADRs belonging 26. to the SOC nervous system disorders per MedDRA PT The five most frequently reported ADRs, namely, dizziness, somnolence, feeling drunk, fatigue and weight increase were analysed in more detail. Table 1 shows the incidence density; Figure 3 shows the corresponding Kaplan Meier curve. Table 2 shows the action taken with 31. the drug when experiencing an ADR and the outcome of the ADR when stopping and continuing pregabalin use Discussion In pharmacovigilance, there is a need for more information about ADRs. Information about when the ADR occurs, how long it persists and if it disappears spontaneously or not can help to motivate the patient to be adherent to their medication when experiencing an ADR. In

123 Description of the Lareb Intensive Monitoring system 123 Figure 1. Percentage of patients experiencing an ADR due to pregabalin use during different time periods. ADRs are grouped per System Organ Class, SOC. The five SOCs with the most reported ADRs are shown weeks weeks weeks weeks Gastrointestinal disorders General disorders and administration site Investigations Psychiatric disorders Nervous system disorders 16. conditions MedDRA SOC Figure 2. Percentage of patients experiencing an ADR belonging to the nervous System Organ Class, SOC. ADRs are grouped per Preferred Term, PT. The five PTs with the most reported ADRs are shown weeks weeks 6 12 weeks weeks Disturbance in attention Dizziness Headache MedDRA PT Memory impairment Somnolence this article, we illustrate that a web-based intensive monitoring system using the patient as a source of information can be used to generate this type of information. The results from the pregabalin study will be discussed first and thereafter the role of web-based intensive monitoring as a new pharmacovigilance tool. Percentage of patients Percentage of patients 5

124 124 Chapter 5.3 Figure 3. Kaplan-Meier curves illustrating the incidence densities of the five most frequently reported adverse drug reactions. From the top down to the first line represents increased weight followed by fatigue, feeling drunk, somnolence and dizziness. Survival pertains to those patients who did not develop particular adverse drug reaction, and + represents the censored patients Table 1. Incidence densities per 1000 person- days per time period for the 5 most frequently reported ADRs associated with pregabalin use days days days days Dizziness Somnolence Feeling drunk n.a n.a 27. Fatigue n.a Weight increase Table 2. Action taken with the drug after experiencing an adverse drug reaction and the outcome of the reaction depending on if the drug was withdrawn or not shown in absolute numbers as well as percentages. Since not all patients had answered all questions, the number of patients on the different 32. questions is not always constant. 33. Feeling Weight 34. Dizziness Somnolence drunk Fatigue increase Action taken with the drug after experiencing an ADR* No action Dose reduced after consult Drug withdrawn after consult 39 (44.3%) 8 (9.1%) 19 (21.6%) 18 (43.9%) 4 (9.8%) 3 (7.3%) 11 (32.4%) 4 (11.8%) 8 (23.5%) 14 (36.8%) 2 (5.3%) 8 (21.15%) 13 (52.0%) 1 (4%) 6 (24.0%)

125 Description of the Lareb Intensive Monitoring system Table 2. (continued) 2. Feeling Weight Dizziness Somnolence drunk Fatigue increase Dose reduced on own initiative Drug withdrawn on own initiative Other reasons Outcome of the ADR after stopping pregabalin Recovering/resolving Not recovered Unknown 6 (6.9%) 7 (8.0%) 9 (10.2%) 80 (66.1%) 25 (20.7%) 16 (13.2%) 3 (7.3%) 4 (9.8%) 9 (22.0%) 42 (82.4%) 3 (5.9%) 6 (11.8%) 4 (11.8%) 3 (8.9%) 4 (11.8%) 30 (79.0%) 4 (10.5%) 4 (10.5%) 3 (7.9%) 3 (7.9%) 8 (21.1%) 19 (57.6%) 9 (27.2%) 5 (15.1%) 0 2 (8.0%) 3 (12.0%) 11 (45.8%) 11 (45.8%) 2 (8.3%) Outcome of the ADR while continuing using 12. pregabalin 13. Recovering/resolving 67 (46.5%) 40 (41.1%) 14 (41.2%) 12 (34.3%) 4 (12.1%) 14. Not recovered 76 (52.7%) 55 (57.9%) 20 (58.0%) 22 (62.9%) 29 (87.9%) 15. Unknown 1 (0.7%) (2.9%) *Since one or more answers could be chosen, the total number of answers exceeds the number of patients The adverse drug reaction profile of pregabalin Calculation of incidence densities and Kaplan-Meier curves show that the five most frequently reported reactions occur early in the treatment, with the highest incidence in the first 2 weeks. This is consistent with the fact that these ADRs are probably type A ADRs, a direct pharmacological effect of the drug [20] It is surprising that after the first 2 weeks the ADR profile on an aggregated level did not change. It is believed that ADRs, which can be attributed to the pharmacological properties of the drugs, would be more pronounced in the beginning of the treatment and would disappear spontaneously if drug treatment continued. This does not seem to apply in all cases. Another reason that the ADR profile did not change (less ADRs) over time is that patients probably continue their drug use even when experiencing an ADR. Apparently, the positive effects of the drugs outweigh the negative effects when deciding to continue drug use Initially, the majority of the patients did not undertake any action when experiencing an ADR. The differences in the outcome of the reaction between patients who withdrew the drug and patients who continued drug treatment are dependent on the type of ADR. For example, for dizziness, 66.1% of the patients who had stopped pregabalin use were reporting to have recovered or were recovering. In contrast, 46.5% of those who continued pregabalin use reported that they were recovering or had recovered. In this case, a rather large proportion of the patients who continued the use of pregabalin also recovered from dizziness, indicating that dizziness may be a transitory ADR, not always requiring cessation of the drug in order to 5

126 126 Chapter disappear. For weight increase, drug withdrawal had a more pronounced effect on recovery: % of the patients recovered after drug cessation compared with 12.1% of those who 3. continued drug use. In this case, it seems that the outcome is more dependent on drug cessation as is the case with dizziness Web-based intensive monitoring 7. The LIM system was developed as an addition to the spontaneous reporting system. Spontaneous reporting systems are a great source of information when it comes to identifying new signals, especially concerning serious and rare ADRs. Of the major safety issues in recent 10. years, the majority was identified using evidence from spontaneous reporting [21]. Spontaneous reporting has a few limitations, for example, underreporting and inability to calculate incidences. In addition, it only provides cross-sectional data of the reaction, which do not 13. provide any information about the time course of the reaction With a web-based intensive monitoring system, it is possible to address a few of the limitations of spontaneous reporting. With this system, incidences of certain reactions can be cal culated, and because of its longitudinal character, it is also possible to collect information 18. about the time course of ADRs. In the following paragraphs, the strengths and weaknesses of 19. this system will be discussed In the literature, most information available about the ADRs of a newly marketed drug 22. originate from randomised controlled trials, where strict inclusion and exclusion criteria are 23. present and where the duration of the trial is usually quite short. With web-based intensive 24. monitoring, there are no inclusion or exclusion criteria that might lead to a different population than in clinical trials, and therefore, it will give a better picture of the ADR profile in daily practice Even though there are no restrictions for inclusion in the web-based intensive monitoring 29. system, there might be a selection of the patient population. Only 6.6% of all the patients 30. who received a first prescription of pregabalin decided to participate in the study (data 31. provided by the Dutch Foundation for Pharmaceutical Statistics). Because we have no information about the patients who did not participate, it is not possible to know if the patients who eventually participated in the study are representative for the patients using pregabalin, 34. which means that the results have to be interpreted with this in mind For this web-based intensive monitoring to be a powerful tool in generating new data about 37. ADRs, patient participation has to be increased. To increase patient participation, there are activities ongoing in order to stimulate active participation from the pharmacist (e.g. phar-

127 Description of the Lareb Intensive Monitoring system maceutical care projects, training) as well as research into the motives for patient participation and investigation of the non-responders In this study, we chose to use the patient as a source of information. This has the advantage 5. that ADRs are reported by the person who has actually experienced the reaction. In the study, 6. patients were asked to report reactions that they believed were caused by the drug. Reactions that are not perceived as ADRs or which are asymptomatic will not be reported. In a few SOCs, for example blood and lymphatic disorders, ear and labyrinth disorders, endocrine 9. disorders, hepatobiliary disorders and immune system disorders, no or very few reports were 10. received. ADRs falling into these categories are of course quite rare, but it is possible that 11. patients do not have tangible symptoms of ADRs concerning these organs or that patients 12. do not correlate these complaints to drug use. If a patient experiences an ADR which unables 13. him to fill in any further questionnaires, this information will not be collected. It is therefore 14. possible that the system will be less valuable in order to detect these types of reactions Because all questionnaires are web-based, it is possible to send a patient multiple questionnaires over time. Longitudinal data collection makes it possible to study the time course of ADRs. In a study where multiple questionnaires are sent, there is always a risk of receiving 19. conflicting information. In the questionnaires, there were no logical checks for start dates 20. and end dates; that is, it was not checked for if the start date of the drug proceeded the start 21. date of the ADR, which sometimes hampered calculating, for example, latency times. Another example concerning conflicting information is the outcome of the reaction. The patient was allowed to give the answer that he or she had recovered and had not recovered at the 24. same time. In the analysis, this was addressed by choosing the least favourable outcome (not 25. recovered > recovering > recovered), so there would not be an overestimation of positive 26. outcomes During data analysis, it became clear that the patients did not always report the suspected 29. ADRs in the questionnaire which covered the period in which they experienced the ADR, 30. but they reported it in one of the remaining questionnaires. In the analysis for incidence 31. densities, it is corrected for this, and the latency of the reaction was calculated based on the 32. start date of the drug and the start date of the reaction rather than calculated based on the 33. number of reactions in each questionnaire, thereby assuming that the reaction occurred in 34. the questionnaire in which it was reported A weakness with the longitudinal character of this study is that patients were allowed to fill 37. in a questionnaire even though they had not filled in the previous questionnaire. By allowing skipping questionnaires, the chance that patients fill in a questionnaire when experiencing an ADR is greater than when they are not, giving an overestimation of ADRs occurrence. To 5

128 128 Chapter address this bias, an analysis could have been made with the data from the patients who 2. filled in the questionnaires sequentially. In future studies, this will not be a problem because 3. we will change the process of sending of the questionnaires. Only those who fill in a questionnaire will receive the other questionnaires Because the system is web-based, patients who do not have access to Internet or are not 7. familiar with using the Internet will be underrepresented in the sample. This would probably 8. be more prominent in the older age categories. Statistics from 2008 show that 86% of the 9. Dutch households have access to Internet at home [22]. It is difficult to draw conclusions to 10. what extent age contributes to the selection bias, but older people not being familiar with 11. the Internet would be underrepresented in this study Because the web-based intensive monitoring methodology is new, there are some refinements necessary as discussed previously. However, this study shows that it is possible to study the time course of ADRs by using web-based intensive monitoring. This method can be 16. a valuable addition to pharmacovigilance because it can generate other types of information 17. as compared with spontaneous reporting and other intensive monitoring methodologies

129 Description of the Lareb Intensive Monitoring system References 1. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med 2005; 353: Kwara A, Herold JS, Machan JT, et al. Factors associated with failure to complete isoniazid treatment for latent tuberculosis infection in Rhode Island. Chest 2008; 133: Baldessarini RJ, Perry R, Pike J. Factors associated with treatment nonadherence among US bipolar disorder patients. Hum Psychopharmacol 2008; 23: Kane SV, Brixner D, Rubin DT, et al. The challenge of compliance and persistence: focus on ulcerative colitis. J Manag Care Pharm 2008; 14:s2 s van Grootheest K, Olsson S, Couper M, et al. Pharmacists role in reporting adverse drug reactions in an international perspective. Pharmacoepidemiol Drug Saf 2004; 13: de Langen J, van Hunsel F, Passier A, et al. Adverse drug reaction reporting by patients in the Netherlands: three years of experience. Drug Saf 2008; 31: Aagaard L, Nielsen LH, Hansen EH. Consumer reporting of adverse drug reactions: a retrospective analysis of the Danish adverse drug reaction database from 2004 to Drug Saf 2009; 32: Harrison-Woolrych M, Coulter DM. PEM in New Zealand. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 9. Shakir SAW. PEM in the UK. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 10. SPC Lyrica. European Medicines Agency Available via humandocs/pdfs/epar/lyrica/emea-combined-h546en.pdf Accessed Aug 19, Taylor CP, Angelotti T, Fauman E. Pharmacology and mechanism of action of pregabalin: the calcium channel α2 δ (alpha2 delta) subunit as a target for antiepileptic drug discovery. Epilepsy Res 2007; 73: Härmark L, Kabel JS, van Puijenbroek EP, et al. Web-based intensive monitoring, a new patient based tool for early signal detection. [Abstract] Drug Saf 2006; 29: Oosterhuis I, Härmark L, van Puijenbroek EP, et al. Lareb Intensive Monitoring: an interim analysis. [Abstract] Drug Saf 2007; 30: van Grootheest AC, Härmark L, Oosterhuis I, et al. Lareb Intensive Monitoring, a web- based system for monitoring ADRs in the postmarketing phase. [Abstract] Pharmacoepidemiol Drug Saf 2007; 16:S252 S Härmark L, van Puijenbroek E, Straus S, et al. Intensive monitoring of pregabalin: results from an observational, web-based, prospective cohort study in the Netherlands using patients as a source of information. Drug Saf 2011; 34: International Reporting of Adverse Drug Reactions. Council for International Organisations of Medical Sciences. Working Group Report. World Health Organisation, Geneva, MedDRA and MSSO. Available via Accessed Aug 19, Z Index. Available via index.nl Accessed Aug 19, Regulation (EEC) No 2309/93. The Council of the European Communities Available via ec.europa.eu/enterprise/pharmaceuticals/eudralex/vol 1/reg_1993_2309/reg_1993_2309_ en.pdf Accessed Aug 19, Meyboom RH, Lindquist M, Egberts AC. An ABC of drug-related problems. Drug Saf 2000; 22: Raine JM. Risk management a European regulatory view. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 22. Mediaproducten steeds meer via Internet. Centraal Bureau voor de Statistiek Availabe via NL/menu/themas/vrije tijdcultuur/publicaties/artikelen/archief/2008/ pb.htm Accessed Nov 29,

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133 Chapter 6.1 Monitoring the safety of influenza A (H1N1) vaccine using web-based intensive monitoring Härmark L van Hunsel F Hak E van Grootheest A.C Vaccine 2011; 29:

134 134 Chapter Abstract Background 4. When adjuvant vaccines against the pandemic influenza A (H1N1) virus became available 5. after an accelerated registration process, safety issues dominated the public debate. As part 6. of the immunisation campaign, the Dutch government installed an active monitoring of possible adverse events following immunisation (AEFIs). As part of the monitoring we conducted an anonymous prospective cohort study to identify and quantify the occurrence of AEFIs 9. related to pandemic vaccination among the population immunised in general practice Method 12. Adults aged 60 years and older or persons with a risk-elevating medical condition recommended for vaccination in general practice were eligible for participation. After receipt of the first pandemic vaccine the administrator handed over an information flyer of the web-based 15. monitoring program. The patient could sign up for study participation online. Within one 16. week, three weeks and three months after the first immunisation questions were asked about 17. demographics and health, immunisations, injections site reactions and labeled reactions as 18. well as other possible new AEFIs Results 21. In all, 3569 participants filled in the first questionnaire. Corresponding figures for the second 22. and third questionnaires were 3395 (95.1%) and 3162 (88.6%). Mean age was 58 years (SD ) and 50.1% was female. Main indication was 60 years or older followed by presence of 24. pulmonary or cardiovascular disease. Of all participants, 1311 (37%) reported an AEFI. Unexpected serious reactions were not reported nor were there signals of possible new AEFIs. The occurrence of an AEFI was determined by gender, age and type of co-morbidity Conclusion 29. The web-based intensive monitoring system among patients immunised in general practice 30. revealed AEFIs due to pandemic vaccination in one-third of participants. There were no 31. unexpected serious adverse events in this population. This advanced methodology can be 32. further developed to monitor real-time use and AEFIs of vaccines

135 Application of web-based intensive monitoring Introduction In March and early April 2009, Mexico experienced outbreaks of respiratory illness and 4. increased reports of patients with influenza-like illness. On April 23 several cases of severe 5. respiratory illness were confirmed as swine origin influenza A (H1N1) [1]. The virus spread 6. throughout the world and on June 11, 2009, the World Health Organisation declared an 7. influenza pandemic [2] Vaccination is the most effective measure to control the spread of influenza virus and reduces 10. associated morbidity and mortality. The development of vaccines against the influenza A 11. (H1N1) virus became a high priority for vaccine manufacturers. In the European Union special 12. registration procedures were put in place in order to speed up the availability of vaccines. 13. These procedures managed by the European Medicines Agency allowed an influenza vaccine to be authorised more quickly than the months usually required [3]. By the end of September and beginning of October 2009, three influenza vaccines were approved for 16. marketing in the European Union; Focetria, Pandemrix and Celvapan [3]. When the vaccines became available a fierce public debate about their safety started in the Netherlands as well as in the rest of the world. Because the new influenza vaccines only had been tested in 19. a small population and had been approved through an accelerated registration process, the 20. public was concerned about the vaccine actually causing influenza, Guillain-Barré syndrome 21. and other neurological syndromes and adjuvants being harmful [4]. As part of the large-scale 22. immunisation campaigns careful monitoring of the adverse events following immunisation 23. (AEFIs) was therefore urgently needed [5,6]. An adverse event following immunisation is 24. defined by the WHO as a medical incident that takes place after an immunisation, causes 25. concern and is believed to be caused by the immunisation [7] The Netherlands Pharmacovigilance Centre Lareb was appointed by the Dutch Ministry 28. of Health to monitor the safety of the pandemic vaccines. In addition to the spontaneous 29. reporting system, Lareb was asked to conduct a prospective cohort study using a modified 30. form of the intensive monitoring methodology to follow people who had been vaccinated 31. with Focetria in general practice during a three month period [8-10].The aim of this study 32. was to identify and quantify AEFIs associated with the pandemic vaccine Focetria. Secondly, 33. we investigated risk factors for the occurrence of AEFIs

136 136 Chapter Method Setting and study population 4. In the Netherlands, the Health Council, which acts as an advisor to the Minister of Health, 5. recommended vaccination to all persons with a medical indication which warrants the seasonal flu vaccination (persons with pulmonary-, cardiovascular- and renal disease, diabetes and immunodeficiency), healthy persons above the age of 60, pregnant women in the 2nd or 8. 3rd trimester, healthcare personnel with direct patient contact and family members and care 9. givers of patients with a high risk of serious complications following an influenza infection 10. were offered the vaccine [11, 12]. The vaccination of all the above mentioned groups except 11. the healthcare personnel would be carried out by the general practitioner. Specific software 12. to search for these patients in general practice has been in use since 1995 and has been 13. updated according to the guidelines [13] GPs who had reported an ADR to Lareb in the past two years and all GPs living in the 16. Northern provinces of the Netherlands (duplicate addresses were identified), in total practices, were sent an invitation letter with information about the study. Of those practices responded that they wanted to participate in the study. 100,000 flyers were sent to these 19. practices to hand out to the patients during their first pandemic vaccination in November The flyer contained information about the aim of the study and instruction on how to 21. sign up for the study via a dedicated and password safeguarded website. Eligible participants 22. were those who were enlisted at the general practice who met the eligibility criteria for such 23. immunisation according to the guidelines of the Dutch Health Council as described above Data collection 26. Data were collected between November 16, 2009 and March 3, After online registration, patients received a questionnaire via within a week after the first immunisation In the vaccination schedule an interval of at least two weeks was recommended between 29. the first and second immunisation. The second questionnaire in which AEFIs attributed to 30. the second immunisation were reported, were sent three weeks later. The third questionnaire was sent three months after the first questionnaire to monitor AEFIs with a late onset If the participant failed to fill out one questionnaire, a reminder was sent after 7 days. Nonresponders were considered to be lost to follow up and did not receive any further ques tionnaires. In the questionnaires, questions were asked about personal characteristics that 35. could be potential risk factors for developing AEFIs, the received vaccinations and possible 36. AEFIs (see Appendix A). In order to increase the response rate and make the questionnaire 37. more user friendly, we actively asked for injection site reactions and labeled reactions such as fatigue, influenza-like illness, headache, myalgia, arthralgia, pyrexia and enlarged lymph nodes through multiple choice questions [14]. Other possible AEFIs could be filled in as free

137 Application of web-based intensive monitoring text. If the patient reported an AEFI which was considered to be serious according to the 2. Council for International Organizations of Medical Sciences (CIOMS) criteria, the seriousness 3. of the event was first assessed by two assessors. If deemed serious, the report was exported 4. to the Lareb database and handled according to the European regulations for serious adverse 5. drug reaction reports [15,16]. Questionnaires were designed and data were collected using 6. the commercially available software Survey Monkey with secure entry [17]. Before finalising 7. and sending the questionnaire, it was tested by a test panel for comprehensibility Sample size and data analysis 10. Since no data were available on the occurrence of AEFIs, we conservatively assumed a prevalence of potential AEFIs after one week of 10% based on data from seasonal influenza vac cines. The sample size calculation was done for the risk factor analysis. According to the rule 13. of thumb to have adequate statistical power to develop a multi-variable model with at least cases for each determinant, we needed at least 2000 participants. We used descriptive 15. statistics to describe response rate, gender, age, indication for vaccination, administration 16. of seasonal vaccination, injection site reactions and labeled reactions. The latency, outcome 17. and duration of the AEFIs were analysed as well as action taken when experiencing an AEFI, 18. if the patient had experienced the reaction in association with the seasonal influenza vaccine in the past and other reasons for the AEFI. AEFIs reported as free text were coded by a qualified assessor using the the Medical Dictionary for Regulatory Activities (MedDRA) Lower 21. Level Term (LLT) [18]. Reactions were grouped per MedDRA Preferred Term, PT. The reported 22. reactions were divided into labeled and not labeled according to the EPAR. Reactions that 23. were not labeled and considered to be potential signals were analysed on a case by case 24. basis. In the case by case analysis causality was assessed by looking at the temporal relationship between the drug and the reaction and to exclude other causes for the reaction Multivariable logistic regression was carried out to develop a prediction model of risk factors 28. for developing an AEFI encoded as a dichotomous outcome variable (yes/no). Potential risk 29. factors were age (in four equally sized categories, the youngest group was used as reference category), gender and the different indications for the vaccination (dichotomous). Both backward and forward selection procedures were used with a significance level of p <0.05 to 32. develop the model. Odds ratios and their 95% confidence interval (95% CI) were estimated as 33. measures of relative risks. The Hosmer Lemeshow goodness of fit was assessed as a measure 34. of calibration of the final model. Data were analysed using SPSS 17 for Windows

138 138 Chapter Results In total, 3775 persons registered as potential participants, see Figure 1. Of these persons, 3569 (94.5%) filled in the first questionnaire. Mean age of the respondents was 58.4 years (standard deviation 14.8 years) and 1789 (50.1%) were female. The main indication for use was age above 60, followed by pulmonary- and cardiovascular disease, see Figure 2. Of the respondents 85.1% reported to have received the second immunisation. The majority had also received the seasonal flu vaccination a few weeks earlier (84%). Figure 1. Response rate of the different questionnaires Questionnaires sent st questionnaire 3569 respondents 2 nd questionnaire 3385 respondents 3 rd questionnaire 3160 respondents 206 Loss to follow up 184 Loss to follow up 225 Loss to follow up In total 1311 (37%) of the participants reported an AEFI. After the first vaccination, 963 (27%) participants reported to have experienced 2401 AEFIs. After the second immunisation 746 (24.6%) patients reported 2479 AEFIs. 420 patients reported an AEFI after both the first and the second immunisation. 43 patients reported 69 AEFIs, which were not possible to attribute with certainty to nor the first nor the second immunisation. There were no differences in loss to follow up between the first and second questionnaire between patients who had reported an AEFI and patient who did not report AEFIs (Chi-squared test, p = 0.52).

139 Application of web-based intensive monitoring 139 Figure 2. Indication for vaccination. Age is the main indication followed by pulmonary and cardiovascular 1. disease. Since the patient could chose one or more indication, the percentages add up to more than 100% Age > 60 years 59.6% 6. Pulmonary disease 21.4% 7. Cardiovascular disease 18.7% Diabetes 11.8% 8. Immunodeficiency 7.9% 9. Health care w orker 4.6% 10. Other reasons 7.8% 11. Pregnancy > 13 w eeeks 2,0% 12. Unknow n 1.6% Renal disease 1,2% Injection site reactions 19. After the first immunisation, 562 patients reported 1065 injection site reactions (1.9 events/ 20. patient). After the second immunisation 472 patients reported 1240 injection site reactions 21. (2.6 events/patient). See Table 1 for an overview of the type of reactions. Table 3 provides 22. additional information about the injection site reactions Labeled AEFIs patients experienced 1077 labeled AEFIs (2.2 events/patient) after the first immunisation. 26. After the second immunisation 1121 labeled AEFIs were reported by 389 patients (2.9 events/ 27. patient). See Table 2 for an overview of the type of reactions. Table 4 provides additional 28. information about the frequently occurring AEFIs. Because some of the frequently occurring 29. AEFIs are similar to influenza symptoms, the question was asked if there were any other factors contributing to the occurrence of the reaction. Nasopharyngitis was the most commonly reported other factor followed by influenza, increased infection susceptibility, fatigue and 32. stress Other AEFIs patients reported 264 other AEFI after the first immunisation (1.4 events/patient). After 36. the second immunisation 83 patients reported 118 AEFIs (1.4 events/patient). In the third 37. questionnaire which was filled in after three months 43 patients reported 69 AEFIs (1.6 events/person). For an overview of reported reactions see Table 5. None of the reported AEFIs were considered to be potential signals. In total 3 reports (incidence of 1/1000) were received 6

140 140 Chapter 6.1 Table 1. Injections site reactions reported after the first and second immunisation. In total 562 patients reported an injection site reaction after the first immunisation and 472 patients reported such a reaction after the second immunisation. The patients could report one or more injection site reactions, therefore the total number of reactions per immunisation exceeds the number of patients reporting an injection site reaction. The percentages are calculated using the total number of respondents per questionnaire as a denominator st immunisation Injection site pain Injection site swelling Injection site erythema Injection site warmth Injection site bruising Injection site itching Total number of patients % nd immunisation Total number of patients % 13. Injection site pain Injection site swelling Injection site erythema Injection site warmth Injection site bruising Injection site itching Table 2. Labeled AEFIs reported after the first and second immunisation. In total 494 patients reported a labeled AEFI after the first immunisation and 472 patients reported such a reaction after the second immunisation. The patients could report one or more labeled AEFIs, therefore the total number of reactions per immunisation exceeds the number of patients reporting an injection site reaction. The percentages are calculated using the total number of respondents per questionnaire as a denominator st immunisation Fatigue Headache Influenza-like symptoms Myalgia Arthralgia Pyrexia Lymph nodes enlarged 2nd immunisation Fatigue Headache Influenza-like symptoms Myalgia Arthralgia Pyrexia Lymph nodes enlarged Total number of patients Total number of patients % %

141 Application of web-based intensive monitoring Table 3. Information about injections site reactions grouped per immunisation. The time to onset is given as a latency and the duration of the reaction is described as well. Injection site reactions Time to onset Duration of AEFI Contact general practitioner Treatment Recovering/resolving 1st immunisation less than 1 day 3 days 2.3% 0.2% 95.6% 2nd immunisation less than 1 day 3 days 2.8% 0.0% 95.6% Similar reaction in the past when receiving the seasonal flu 9. vaccination % 83.2% Table 4. Information about frequently occurring AEFIs grouped per immunisation. 12. Frequently occurring AEFIs 13. 1st immunisation 2nd immunisation 14. Latency 1 day 1 day 15. Duration 2 days 3 days Contact general practitioner Treatment Recovering/resolving Similar reaction in the past when receiving the seasonal flu vaccination 11.5% 3.5% 83.6% 22.7% 15.8% 4.5% 84.8% 3% concerning serious AEFIs leading to one of the CIOMS criteria. The reactions reported were atrial fibrillation, aggravation of MS and influenza-like illness persisting for over a month Logistic regression Male patients experienced less AEFIs than females and the risk of AEFIs decreases with age, see Table 6. Cardiovascular disease, pulmonary disease, immunodeficiency and pregnancy increased the risk of an AEFI Discussion Principal findings Prior to the large-scale immunisation campaign against the influenza A (H1N1) virus there was a fierce public debate about the safety of adjuvanted pandemic vaccines. Our study shows that the incidence of AEFIs in the population who were vaccinated by the general practitioners in the Netherlands was 36.7%. The results of the current study do not raise any concerns about the safety of the used vaccine in The Netherlands. The reactions reported were expected and non-serious. Injection site reactions and labeled AEFIs have a short 6

142 142 Chapter 6.1 Table 5. AEFIs reported as free text grouped per Meddra PT and per immunisation. For each immunisation 1. the 10 most reported events are shown. 2. 1st immunisation 2nd immunisation 3 months Dizziness Nausea Diarrhoea Nasopharyngitis Pain in extremity Dyspnoea Oropharyngeal pain Dizziness Nasopharyngitis Oropharyngeal pain Palpitations Diarrhoea Nausea Oedema peripheral Nasopharyngitis Dizziness Cough Dysphonia Palpitations Oropharyngeal pain Rhinorrhoea Palpitations 12 Oral herpes 6 Dyspnoea Abdominal pain 11 Dyspnoea 6 Eructation Injection site pain 10 Flank pain 4 Cough decreased Cough 10 Pain in extremity 4 Pain in extremity Feeling hot Cough decreased Muscular weakness Abdominal pain upper Agitation Table 6. Logistic prediction model for the occurrence of an AEFI Gender Age ( years) Age ( years) Age ( years) Age ( years) OR 0.6 ( ) 0.54 ( ) 0.4 ( ) 0.3 ( ) p <0.001 <0.001 <0.001 <0.001 AEFI+ Male 344, F AEFI - Male 1431, Female Cardiovascular disease 1.32 ( ) Pulmonary disease 1.36 ( ) Immunodeficiency 1.5 ( ) Pregnancy 2.61 ( ) < Hosmer and Lemeshow test Chi-Square 4.593, df 7, P latency, a short duration and are in most cases self-limited. The occurrence of an AEFI was determined by gender, age and type of co-morbidity Strengths and weaknesses Since we did not control how many of the flyers were actually handed out at the GPs office we do not know if there is a selection bias in who was given a flyer for participation

143 Application of web-based intensive monitoring or not. Because the lack of denominator data it is also not possible to calculate an overall 2. response rate (numbers of patients participating/number of patients receiving a folder) In order to check if the population of this cohort was representative for the patients receiving the pandemic influenza vaccine in general practice, the population was compared to vaccination data from a sample of 72 general practices, believed to be representative for the 7. Dutch population as described in the report Monitoring Vaccination rate, Dutch National 8. Influenza Prevention Program When comparing the characteristics between these two 9. cohorts the percentage of men is slightly higher in our cohort (49.9% compared to 49.6%). 10. The main indication for vaccination in this cohort which is assumed to be representative 11. for the Dutch population was, except age, cardiovascular disease, followed by pulmonary 12. disease and diabetes mellitus. This is similar with the indications in our cohort [19] Only patients with a medical indication which warrants the seasonal flu vaccination, healthy 15. persons above the age of 60, pregnant women in the 2nd or 3rd trimester, and family members and care givers of patients with a high risk of serious complications following an influ enza infection were vaccinated in general practice. How these results apply to children and 18. healthy adults is uncertain, notably since young age seems to be associated with more AEFIs. 19. In the Netherlands, children were vaccinated with another adjuvanted vaccine (Pandemrix ), 20. so comparisons are difficult Injection site reactions and labeled reactions were actively asked for, other reactions could 23. be reported as free text. Because it might be easier for a patient to answer a question with a 24. multiple choice option than filling in AEFIs as free text, there might be an overestimation of 25. the AEFIs where multiple choice questions were used For injection site reactions the causality is strong since there is a very clear link between the 28. injection and the reaction. For the labeled AEFIs and the reactions that were reported as free 29. text, it is more difficult to assess causality, most of the symptoms can also be due to influenza 30. itself. In order to see to what extent patients were aware of other factors playing a role in the 31. occurrence of the AEFI, patients were asked to name other factors. Nasopharyngitis was the 32. most commonly reported other factor followed by influenza, increased infections susceptibility, fatigue and stress. These factors were only reported by a small proportion of all patients reporting a labeled AEFI In this study it was assumed that all reactions reported in the first questionnaire were attributed to the first vaccination an all reactions in questionnaire two, plus the injection site 37. reactions and frequently occurring AEFIs in the third questionnaire were attributed to the second vaccination if the second vaccination had been taken. Since this division between 6

144 144 Chapter the first and second immunisation is done after collecting the data, there is a possibility that 2. reactions, which were considered to be attributed to the second vaccination actually were 3. caused by the first vaccination In recent years the patient has become an important player in pharmacovigilance and in 6. a number of countries patients are allowed to submit reports to a spontaneous reporting 7. system [20]. Patients do not have a professional filter in what to report; therefore the chance 8. of finding new associations is high. A disadvantage often mentioned with patient reports 9. is that they are not medically confirmed. For the type of reactions reported in this study, 10. medical confirmation is not necessary. In the cases where AEFIs were reported which were 11. considered to be serious, follow up information was asked in order to confirm the diagnosis This study was performed using web-based questionnaires. With web-based questionnaires, 14. it is possible to structure the data received so that they will be more complete than data 15. received on paper. Through the web-based character of the study, interim analysis could be 16. performed at any time, making it possible to monitor the AEFIs in real time. Older people 17. might be underrepresented in the cohort since they are not familiar with using internet. 18. Recent statistics show that 86% of Dutch households have access to internet, however 19. persons aged above 75 and persons living in an institution were not included [21]. In this 20. study the patient was followed over time making it possible to collect information about 21. latency, recovery and duration of the AEFI. This type of information is important, since it can 22. reassure the patient who will be immunised. This type of information is rarely presented in 23. the SmPC and spontaneous reporting might not be able to capture it, therefore web-based 24. cohort monitoring can be a valuable addition Strengths and weaknesses in relation to other studies 27. The SmPC of Focetria reports a study conducted with 131 adults and 123 elderly. In this study 28. most of the AEFIs were mild and of short duration. The incidence of symptoms observed 29. in subjects over 60 years of age was generally lower as compared to subjects aged years [14]. In a study done by Clark et al. the vaccine was tested in 176 adults years 31. of age. 80% of subjects reported adverse reactions after either dose (73% after the first and % after the second). The frequency or severity did not increase after the second dose was 33. administered. The reported reactions were graded as mild or moderate and were generally 34. self-limiting resolving within a 72 h period. The most frequent local and systemic reactions 35. were pain at the injection site and muscle aches [22]. The incidence of AEFIs in these studies 36. is much higher compared to the incidences in our study. A possible explanation might be 37. that the data collection methods differs between our study and this study. In this study selfcompleted diaries where used where patients could report both solicited and unsolicited symptoms. The study by Clarke et al. was performed in a group aged years, in our study

145 Application of web-based intensive monitoring the median age was 58 years. It has also been clear both from clinical trials as well through 2. the logistic regression in this study, that young age is associated with more AEFIs than older 3. age, this might be another explanation for the higher incidence rate Also for the labeled AEFIs the incidences in the SPC for headache, myalgia and fatigue are 6. higher than in our cohort whereas the incidence of arthralgia and pyrexia are consistent 7. with our findings. The incidence of influenza-like illness is much higher in our cohort than 8. mentioned in the SPC. A possible explanation for this is that the patients in our cohort were 9. vaccinated during the influenza season and it is possible that the symptoms they report are 10. actually due to influenza itself instead of the vaccine Both clinical trials as our study are prospective cohort studies. The difference between them 13. is that with our study we did not have any additional inclusion or exclusion criteria, making 14. it possible to collect data from the actual users of the vaccine. Furthermore, because of its 15. observational character it is possible to follow a greater number of patients as compared to 16. clinical trials which makes it possible to gather more data. Because we worked with three 17. questionnaires it was also possible to follow the time course of the AEFIs and report information about time to onset, duration of AEFI and action taken when experiencing an AEFI, data which are rarely published as a result of RCTs whose main focus is to investigate efficacy and 20. not report on AEFIs Meaning of the study and future research 23. This study shows the AEFI spectrum in the population immunised in general practice in the 24. Netherlands. In order to get a complete picture of the AEFIs from this vaccine, research has 25. to be done also in other populations since both from our study as well as other studies it 26. has been indicated that for example age might influence the AEFI pattern. Secondly, our 27. study monitored the vaccine and its effects during three months. In order to be sure that 28. there are no unforeseen late onset effects, a longer follow up period might be warranted. 29. Thirdly our cohort size was not large enough to identify any rare AEFIs. In order to detect new 30. rare signals spontaneous reporting would probably be a more suitable method, and a case 31. control study could verify that signal. Cohort studies are inefficient in finding these types 32. of reactions because one needs to follow a very large cohort in order to identify these kind 33. of events for example cases of Guillain Barré syndrome. In Europe the VAESCO consortium 34. initiated a study to look at the association between the pandemic influenza vaccines using a 35. case control approach [23]

146

147 Application of web-based intensive monitoring Appendix A Questions asked in the questionnaires Gender Date of Birth On which date did you receive your Influenza A (H1N1) immunisation? Is this your first or second immunisation? 1st 2nd Did you receive the seasonal flu immunisation earlier this year? Yes No What is the reason for receiving the Influenza A (H1N1) immunisation? (multiple answers possible) Pulmonary disease Cardiovascular disease Diabetes Pregnancy Age above 60 Renal disease Immunodeficiency I am a healthcare worker Don t know/unknown Other reasons than above mentioned Did you experience any AEFIs from the Influenza A (H1N1) vaccine? Yes No 34. If No, end of questionnaire

148 148 Chapter If Yes, did it concern an injection site reaction? Yes No 5. If No, skip to question If Yes, please tick the appropriate reaction (multiple answers possible) Pain Erythema Swelling or induration Feeling of warmth Pruritus Hematoma Since when do you have this reaction? Has the reaction lead to one of the following serious situations? Hospitalisation Disability Life threatening situation Congenital abnormality Death No, none of the above If one of the above situations occurred, do you give us permission to contact you for further information? Yes No Have you recovered from the AEFI? Yes, I have The AEFI is getting less severe but I am not fully recovered yet No, I have not recovered If yes, when did you recover?

149 Application of web-based intensive monitoring Which action did you undertake when experiencing the AEFI? I have discussed the AEFI with a doctor but have not yet received treatment I have been treated by the doctor I have not undertaken any of the actions above 16. Did you experience similar complaints by seasonal flu vaccination? Yes No 17. Are there other explanations for the reactions, if yes, which ones? 18. Have you experienced any other AEFIs? No, end of questionnaire 19. If yes, have you had any of the below described, frequently occurring AEFI? Yes No, skip to question If yes, which ones? Headache Fatigue Pyrexia Myalgia Arthralgia Sweating, chills and influenza-like illness Lymphadenopathy Repetition of questions Have you experienced any other AEFIs? No, end of questionnaire 22. Yes, free text field to write the AEFI. For each AEFI reported questions were repeated. Question 21 and 22 was repeated until the patient had filled in all the experienced AEFIs 6

150 150 Chapter References 1, Outbreak of swine-origin influenza A (H1N1) virus infection in Mexico, March April Morb Mortal Wkly Rep 2009; 58: New influenzaa (H1N1) virus: global epidemiological situation, June Wkly Epidemiol Rec 2009; 84: European Medicines Agency pandemic influenza (H1N1) website. European Medicines Agency Available via htm Accessed Vaccine safety: informing the misinformed. Lancet Infect Dis 2009; 9: Huang WT, Chuang JH, Kuo SH. Monitoring the safety of pandemic H1N1 vaccine. Lancet 2010; 375: Destefano F, Tokars J. H1N1 vaccine safety monitoring: beyond background rates. Lancet 2010; 375: Vaccine safety and adverse events following immunization. WHO Available via who.int/immunization monitoring/routine/immunization adverse/en/index.html Accessed Härmark L, van Grootheest AC. Pharmacovigilance: methods, recent developments and future perspectives. Eur J Clin Pharmacol 2008; 64: Härmark L, Kabel JS, van Puijenbroek EP, et al. Web-based intensive monitoring, a new patient based tool for early signal detection. [Abstract] Drug Safety 2006; 29: van Grootheest AC, Härmark L, Oosterhuis I, et al. Lareb intensive monitoring, a web based system for monitoring ADRs in the postmarketing phase. Pharmacoepidemiol Drug Safety [Abstract] 2007; 16:S Vaccinatie tegen pandemische influenza A/H1N1 2009: doelgroepen en prioritering. The Health Council of the Netherlands. Available via samenvatting% pdf Accessed Aanvulling advies vaccinatie influenza A/H1N The Health Council of the Netherlands. Available via Accessed Hak E, Buskens E, van Essen GA, et al. Clinical effectiveness of influenza vaccination in persons younger than 65 years with high-risk medical conditions: the PRISMA study. Arch Intern Med 2005; 165: SmPC Focetria. European Medicines Agency Available via docs/en GB/document library/ EPAR - Product Information/human/000710/WC pdf Accessed International Reporting of Adverse Drug Reactions. Council for International Organisations of Medical Sciences. Working Group Report. World Health Organisation, Geneva, Regulation (EEC) No 2309/93. The Council of the European Communities Available via ec.europa.eu/enterprise/pharmaceuticals/eudralex/vol 1/reg_1993_2309/reg_1993_2309_ en.pdf Accessed Survey Monkey. Available via Accessed MedDRA and MSSO. Available via Accessed Tacken M. Mulder J, Visscher S, et al. Monitoring vaccination rate Dutch National Influenza Prevention Program Available via %20rapport.pdf Accessed de Langen J, van Hunsel F, Passier A, et al. Adverse drug reaction reporting by patients in the Netherlands: three years of experience. Drug Saf 2008; 31:

151 Application of web-based intensive monitoring Mediaproducten steeds meer via Internet. Centraal Bureau voor de Statistiek Availabe via NL/menu/themas/vrije tijdcultuur/publicaties/artikelen/ archief/2008/ pb.htm Accessed Clark TW, Pareek M, Hoschler K, et al. Trial of 2009 influenza A (H1N1) monovalent MF59-adjuvanted vaccine. N Engl J Med 2009; 361: Dielemann J, Sturkenboom M, Hviid A, et al. European wide study on the association between Guillain-Barré syndrome and new Influenza A (H1N1) vaccination. [Poster] Available via Accessed

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153 Chapter 6.2 Web-based intensive monitoring: from passive to active drug surveillance Härmark L van Grootheest A.C Expert Opinion on Drug Safety 2012; 11:45-51.

154 154 Chapter Abstract Introduction 4. Recently, the European pharmacovigilance legislative framework changed. Post Authorisation 5. Safety Studies (PASS) and additional monitoring of drugs will be important tools in ensuring 6. the safety of drugs. Methods that can facilitate gathering of the requested information are 7. essential. In this article, web-based intensive monitoring is described and future applications 8. of this method are discussed Areas covered 11. Web-based intensive monitoring is a non-interventional observational cohort study using 12. patients as a source of information. Eligible patients are identified in the pharmacy, and information about drug use and adverse events is collected through web-based questionnaires An overview of the results as well as the pros and cons of this method is given. A discussion 15. on how this methodology can be expanded to other settings and how it can be used in the 16. future is included Expert opinion 19. The main idea with web-based intensive monitoring, using a specific inclusion point, letting 20. patients be the source of information and following the patients over time via web questionnaires, can be a useful tool in post-marketing surveillance. Aspects other than adverse drug reactions, such as information about indication for use and off-label use, dosage and 23. compliance can also be collected

155 Application of web-based intensive monitoring Introduction The safety of drugs has gained much attention since the withdrawal of rofecoxib in 2004 [1,2] 4. both in the regulatory and scientific world as well as in the public domain [3-5]. This has led 5. to a greater awareness about the importance of a robust pharmacovigilance system that is 6. able to detect possible harm from drugs in a timely manner. Pharmacovigilance, defined by 7. the WHO as the science and activities relating to the detection, assessment, understanding 8. and prevention of adverse effects or any other drug-related problems [6] needs to continue 9. its development of new methods in order to ensure that patients can use their drugs in a safe 10. manner In order to keep up pace with the developments in pharmacovigilance, regulatory agencies 13. have been evaluating and reforming their systems in recent years [7,8]. In Europe, a public 14. consultation Strategy to Better Protect Public Health by Strengthening and Rationalising EU 15. Pharmacovigilance was published in 2007 with key proposals for legislative changes within 16. the EU [9]. This proposal was adopted by the European Commission in December 2008 and 17. at the end of September 2010 the European Parliament endorsed the new directive and 18. regulation [10,11]. The new measures can be divided into three different areas with the 19. broad objectives of: i) strengthening post-authorisation regulation of medicines; ii) improving efficiency within the pharmaceutical industry and through reduced duplication of effort between the member states; and iii) increasing transparency [12] The strengthening of post-authorisation regulation of medicines has two key elements: the 24. first one is related to the process, where it is important that there are clear roles, responsibilities and obligations for the key responsible parties. The second one is related to the collection of high-quality data relevant to the safety of medicines and patient safety An important change related to the process is the creation of the Pharmacovigilance Risk 29. Assessment Committee (PRAC) at the European Medicines Agency (EMA). The PRAC will be 30. responsible for the leading scientific opinion on any question relating to pharmacovigilance 31. of medicinal products for human use that will occur at any time during the pre- and postlicensing procedure. In more detail, this means assessment of periodic safety update reports, risk management plans (RMPs) and protocols for post-authorisation safety studies (PASS) The collection of high quality data is a requirement for the prompt identification of potential 36. risks. The reporting of adverse drug reactions (ADRs) by doctors, pharmacists and patients 37. has been the backbone of data collection in pharmacovigilance and has proven its value in detecting relatively rare and serious ADRs [13]. Within the new legislation, spontaneous reporting will continue to play an important role and the range of possible reporters will be 6

156 156 Chapter expanded to also include patients. The Eudravigilance database to which all spontaneous 2. reports are being forwarded will play a bigger role in signal detection than it currently does Besides reporting by healthcare professionals and patients, there is also a need for more 5. structured data collection about the safety of drugs. With the new legislation regulators will 6. have the legal power to request PASS as a condition of marketing authorisation. In the past, 7. there were no legal obligations for marketing authorisation holders (MAHs) to carry out such 8. studies, making it difficult for regulators to force companies to carry out specific studies. 9. These non-interventional PASS will be carried out within the framework of RMPs, and will 10. be financed by the MAH and involve the collection of data from healthcare professionals or 11. patients Another step to monitor the safety of certain drugs is that the EMA, in collaboration with the 14. member states, will set up and maintain a list of medicinal products for human use subject 15. to additional monitoring [14,15]. The aim of this paper is to describe a web-based intensive 16. monitoring system and discuss how it can be used as a tool to further strengthen pharmacovigilance, taking into account the recent European pharmacovigilance developments Web-based Intensive Monitoring The new European pharmacovigilance legislation will put more focus on PASS and additional 23. monitoring. Spontaneous reporting could and will play a role herein but it will not be sufficient to rely on spontaneous reporting only. Spontaneous reporting is focused on detecting new ADRs and if necessary take regulatory actions needed to protect public health by, for 26. example, changing the summary of product characteristics or withdrawing the drug from 27. the market. It has been suggested that pharmacovigilance should be less focused on finding 28. harm and more focused on extending knowledge of safety [16]. The relatively low number of 29. reports received for a specific association via a spontaneous reporting system makes it less 30. useful as a tool to extend the knowledge on safety, for example, identifying patient characteristics and risk factors that will contribute to the occurrence of an ADR. There is a need for the development of pharmacovigilance tools which can provide the information requested This need was recognised by the Netherlands Pharmacovigilance Centre Lareb, which is responsible for the collection and analysis of ADR reports by doctors, pharmacists and patients in the Netherlands. In 2006 a web-based intensive monitoring system called Lareb Intensive 37. Monitoring (LIM) was introduced, as a complement to the spontaneous reporting system.

157 Application of web-based intensive monitoring In this web-based intensive monitoring system, the information obtained about the drug use 2. and adverse events originates from the patient. Patients eligible for inclusion are identified 3. in the pharmacy when filling the first prescription of a drug under study. A first prescription signal is generated by the pharmacy computer software if the patient has not filled a prescription of that particular drug in the previous 12 months. The patient is informed about 6. the intensive monitoring study and is asked to participate. An information flyer is handed 7. to the patient, together with a specific code, which is used when signing up for the study 8. online. On registration, patients are asked for an address which will be used for further 9. correspondence. Patient characteristics such as gender, birth date, length and weight are 10. asked for. Information about the use of the study drug including start date, strength, product 11. code, dosage, administration form and indication for use is collected. This information is also 12. gathered for all concomitant medication. After registration, the patient receives questionnaires by at specific points in time. In these questionnaires, questions are asked about possible ADRs, seriousness of event, start date of event, action taken with the study drug 15. (stopping/dose reduction/no dose change) and outcome of the event. If the patient states 16. that he or she stopped drug use, no more questionnaires will be sent [17] Web-based intensive monitoring is based on the intensive monitoring methodology. Intensive monitoring is a non-interventional observational cohort, differentiating itself from spontaneous reporting because it actively monitors selected drugs during a certain period 21. of time. Through its non-interventional character, intensive monitoring provides real world 22. clinical data involving neither inclusion nor exclusion criteria throughout the collection 23. period. It is unaffected by the kind of selection and exclusion criteria that characterise clinical 24. trials, thereby eliminating selection bias. Another strength of the methodology is that it is 25. based on event monitoring and is, therefore, capable of identifying signals for events that 26. were not necessarily suspected as being ADRs of the drug studied. Intensive monitoring 27. allows estimation of the incidence of adverse events which makes it possible to quantify 28. the risk of certain events. However, the proportion of adverse effects that go unreported is 29. unknown. The studies also produce reported event rates rather than true incident rates. This 30. is the same for all studies based on medical record data including computer databases and 31. record linkage. There is no control group in standard intensive monitoring studies and the 32. true background incidence for events is, therefore, not known [18-20] Web-based intensive monitoring has a few key elements which are important for its good 35. functioning, namely, the identification and inclusion procedure, the source of information 36. and the way of collecting the information. These elements, together with their strengths and 37. weaknesses are discussed in more detail below. 6

158 158 Chapter With the web-based intensive monitoring system, patients are directly approached by the 2. pharmacist when filling their first prescription of the drug. The advantage is that patients 3. are included at the moment they receive the drug for the first time and can, therefore, be 4. followed from the first day of use causing no delay in the gathering of data and identification 5. of risk. This makes web-based intensive monitoring a fast way of collecting safety data about 6. a drug In order to be able to use the pharmacy as an inclusion point, the pharmacy has to be able 9. to identify the patients eligible for the study. Pharmacists in the Netherlands are regarded 10. as part of the healthcare team. Just as a patient is coupled to one general practitioner (GP), 11. a patient is also coupled to one pharmacy. Due to the high degree of automation in the 12. pharmacy, it is possible for the pharmacy to keep track of a patient s drug use and the 13. pharmacy can ensure that the drugs the patient uses are compatible. The computer can also 14. identify first prescriptions and in co-operation with the major software companies providing software for the pharmacy automation systems, a special intensive monitoring flag has been implemented. In countries where pharmacy systems operate in a different way, one 17. has to investigate if the pharmacy would be the most suitable inclusion point for the webbased intensive monitoring system. If the pharmacy is chosen as the main inclusion point, it is important to be able to identify new users. If patients go to different pharmacies, this 20. can be solved by having a central database where a patient s prescription data are stored. 21. Because pharmacies are located close to the patient, by applying multi-level analysis, the 22. data gathered could also be analysed on the basis of, for example, the socio-economic status 23. of the area where the pharmacy is located By letting the pharmacy be the point of inclusion, it is possible to follow drugs prescribed 26. in different settings. Both drugs prescribed by GPs as well as drugs prescribed by medical 27. specialists in the hospital can be monitored; the only restriction is that the drug has to be 28. dispensed in the community pharmacy. Drugs that are mainly used in a hospital setting or 29. in intramural institutions need to have another inclusion point. A disadvantage by using this 30. approach is that it is not possible for the researchers to control the inclusion at all. The first 31. LIM study showed that only 6.6% of the patients given a first prescription of the drug under 32. study chose to participate [17]. Because we do not know to what extent patients are asked to 33. participate with the web-based intensive monitoring, it is difficult to determine the reason for 34. non-response; were patients not asked or were patients asked but chose not to participate? An important development in pharmacovigilance is the recognition of the patient as an 37. important player. Patients are the users of drugs. Their use of a drug in a safe manner is the ultimate goal of all pharmacovigilance activities. Patients and patient organisations are getting more involved in pharmacovigilance and this has also been acknowledged in the new

159 Application of web-based intensive monitoring pharmacovigilance legislation. All member states are obliged to accept reports from patients 2. to their spontaneous reporting system by mid Before the legislative changes an increasing number of countries, including Denmark, the 5. UK and the Netherlands had introduced patient reporting to their spontaneous reporting 6. system. The experience so far is that the quality of patient reports are comparable to the 7. reports of healthcare professionals [21-23] and they contribute significantly to signal detection [24]. Because of the positive experiences with patient reporting in the spontaneous reporting system and the shift in pharmacovigilance towards patients, the next step is to use 10. patients as reporters in web-based intensive monitoring methodology. The advantage of using patients as a source of information is that the events reported originate from the person who has actually experienced the events. Patients can provide first-hand information about 13. their experiences with drugs and possible ADRs, including the impact of the experienced 14. ADR on their quality of life. Using the patient as a reporter also minimises reporting bias. 15. Because they lack medical knowledge, patients are more likely to report associations that 16. may seem unlikely from a medical point of view. However, patients cannot always provide a 17. confirmation of a medical diagnosis. Experience suggests that patients are willing to provide 18. additional information upon request. If the patient cannot provide the information needed 19. it is possible, with the patient s permission, to contact the treating physician for further 20. information. It is important, especially if serious events are reported, that these events are followed up to ensure that the information about the event is as complete as possible. Another advantage by using patients as reporters is that drug-drug interactions between prescribed 23. drugs and over the counter (OTC) drugs and/or herbal medicines can be detected. The use of 24. OTC drugs and herbal drugs is not always known by the healthcare professionals, but when 25. patients report the medicine used, these types of drugs will be included In web-based intensive monitoring all correspondence and data collection go through 28. the web. When a patient fills in a questionnaire the data is immediately transferred to the 29. database making data collection and processing fast. This eliminates the step of manual 30. data entry, which is necessary when paper questionnaires are used, making data collection 31. less work intensive and in the long run also cheaper. Due to the web-based character of the 32. questionnaire, it is possible to collect data in a structural way which improves data quality All the questionnaires are sent by which makes it possible to send a patient multiple 35. questionnaires at specific points in time without major logistic problems, enabling longitudinal collection of data. The information gathered can be used to get a clear picture of the time course of ADRs, for example, when does an ADR occur? How long does it persist? Does it disappear during continued use or is alteration of drug use and treatment necessary? 6

160 160 Chapter The web-based character of the questionnaires makes it easy to modify the content and 2. customise the questions for a specific study. Although web-based intensive monitoring has 3. been developed in order to extend knowledge about the safety of drugs, it can be used for 4. collection of other information as well, such as medication adherence and the impact of 5. ADRs on quality of life and cost that are associated with an impaired quality of life In order for a web-based system using patients as a source of information to be successful, it 8. is essential that the patient has the cognitive ability and technical skills to be able to forward 9. the information. In situations where one or both of these abilities is impaired, one could 10. consider the other family members or caregivers as sources of information Results from web-based intensive monitoring studies Recent studies have shown that web-based intensive monitoring is a feasible methodology 16. to collect information about the safety of drugs. In a study monitoring the safety of pregabalin, it was shown that it was possible to collect information about ADRs with this method and to quantify these reactions, particular type A ADRs could easily be quantified. In addition to 19. quantifying reactions, it was also possible to detect signals and possible drug-drug interactions. Although not the aim of the study, with the web-based intensive monitoring method it was possible to collect information about age and gender of the patients as well as indication and drug use [17]. Because of the longitudinal character of the web-based intensive monitoring system, it is also possible to collect information about the time course of ADRs. 24. For example, it was possible to establish the ADR spectrum over time and in addition it was 25. shown that time to onset of a reaction could be specified. Information about duration and 26. recovery from the ADR could also be obtained [25]. Until now, this information has been very 27. difficult to obtain Role of web-based intensive monitoring in the future Regulatory aspects 33. The European countries have made efforts to develop drug safety within the registration 34. procedure without slowing down the registration process; an example of this is the conditional marketing authorisation. In the US, the FDA has a similar procedure called accelerated approval. The Committee for Medicinal Products for Human Use delivers such a conditional 37. marketing authorisation for products where there is a specific patient need. It is granted in the absence of comprehensive clinical data referring to the safety and efficacy of the medicinal product. Conditional marketing authorisations are valid for 1 year, on a renewable basis.

161 Application of web-based intensive monitoring The holder is required to complete ongoing studies or conduct new studies with a view to 2. confirming that the risk-benefit balance is positive. In addition, specific obligations may be 3. imposed in relation to the collection of pharmacovigilance data [26]. Another step in a more 4. pro-active post-marketing surveillance in the EU is the introduction of RMPs [27]. RMPs are 5. being set up in order to identify, characterise, prevent or minimise risk relating to medicinal 6. products, including the assessment of the effectiveness of those interventions. The EU RMP 7. contains two parts, the first part containing a safety specification and a pharmacovigilance 8. plan and the second part containing an evaluation of the need for risk minimisation activities 9. and a risk minimisation plan. Where a risk minimisation plan is necessary, both routine and 10. additional activities are to be included. In order to be able to follow a drug after (conditional) 11. approval and monitor its ADRs, web-based intensive monitoring could be used. It is possible 12. to identify users of a specific drug via this system and follow these users over time. This would 13. generate real life data on the safety without the limitations from clinical trials and spontaneous reporting. If there are special risks that have to be addressed, the questionnaires can be customised in order to fit the needs of the particular research question. With this methodology, it will also be possible to make head-to-head comparisons between two drugs The web-based intensive monitoring system could also be used in creating registries for 19. certain drugs. For some drugs, a drug monitoring programme on a voluntary basis is not 20. sufficient. In these cases, a registry is necessary so that every user of the drug can be followed; 21. an example of this is the bosentan registry [28]. Participation in this registry was mandatory; 22. otherwise, the drug could not be prescribed. If this methodology would be used for such a 23. purpose, one has to consider if the community pharmacy is the most convenient place to 24. identify users of the drug Clinical aspects 27. But not only ADRs need to be monitored. Because drugs get more and more sophisticated 28. and because drug users get more and more diverse, it would be interesting to identify and 29. follow certain groups of people such as children or the elderly. What drugs do they use and 30. for what indication? Which dosage do they use? For this kind of research, the aim would be to 31. investigate what drugs a certain group of people uses, the dosage, indications and ADRs. A 32. previous LIM study has shown that it is possible to collect information about drug indication 33. and drug dosage and also relate this to labelled and unlabelled use [17] Identifying a cohort would in this case be different compared to LIM. The starting point 36. would not be the use of a new drug as signalled in the pharmacy but the inclusion would be 37. at a point in the healthcare system in which, for example, children frequent. Though the identification of the cohort would be different in this kind of research, the web-based intensive monitoring technology could be useful in data collection. 6

162 162 Chapter An example where web-based intensive monitoring was used in order to monitor the safety 3. of a new drug was during the vaccination campaign against the influenza A (H1N1) virus in 4. late 2009 and beginning of Because the vaccine had gone through an expedited approval process it was necessary to monitor the safety closely and because there were worries about the safety of vaccine, real-time monitoring was necessary In the UK, patients were recruited for enrollment in the study through posters/leaflets and 9. a website. After recruitment, information about vaccination and ADRs was collected using 10. , text and web-based forms. The researchers conclude that this kind of active surveillance offers potential for near real time vaccine safety monitoring and alerts with minimal additional workload for healthcare staff [29]. In addition, the study showed the viability of 13. using modern technology to support patient self-reporting within an active surveillance 14. system [30] In the Netherlands, the influenza A (H1N1) vaccine was monitored as well through webbased intensive monitoring. The methodology was similar to the LIM methodology, but the inclusion point was not the pharmacy but the GP s office, as the vaccine was administered by 19. the GP. This study also demonstrated that this kind of active surveillance can be a valuable 20. tool when real time data needs to be collected [31] Conclusion In a changing world where information about drugs, not only adverse reaction but also its 26. use and other aspects needs to be investigated, web-based intensive monitoring could be 27. an additional tool in the pharmacovigilance toolkit. At the moment, there are a few places in 28. the world where web-based intensive monitoring systems are operated. The method needs 29. to be validated further and to be implemented in more settings, but it holds potential for 30. becoming an important way of collecting information about ADRs The main idea with web-based intensive monitoring, using a specific inclusion point, letting patients be the source of information and following the patients over time via web questionnaires, can be useful for other aims such as following a specific patient drug after 35. a (conditional) marketing authorisation or as part of a risk minimisation activity. Also, other 36. aspects than ADRs, such as information about indication for use and off-label use, dosage 37. and compliance, can be collected.

163 Application of web-based intensive monitoring Expert Opinion In the EU, the new legislative changes will have a major impact on the conduct of pharmacovigilance. Also, elsewhere in the world these processes of change have been set in motion. As described above, web-based intensive monitoring holds the potential of being an important 6. tool in collecting safety data about drugs. It combines the strengths of spontaneous reporting, namely, collecting data for the sole purpose of drug safety in real life users during real life conditions with those of a more formal cohort study which allows for frequency calculations 9. and follow-up In times where the demands on healthcare professionals are increasing, their willingness 12. to report information about ADRs is decreasing. Patients, because they are the users of 13. drugs and also the ones who experiences ADRs, will have an increasingly important role in 14. providing this information. Data from patients can easily be collected through a web-based 15. intensive monitoring system. Another advantage of using patients as a source of information 16. in web-based intensive monitoring is that it facilitates the possibility of asking for additional 17. information in an efficient way with regard to time and costs In the last 20 years, the means of communication has changed completely. Earlier, telephone 20. and postal mail were the major means of exchanging information; today, several different 21. means are available to exchange information such as mobile (smart) phones and Internet 22. with a number of possibilities including and Internet communities for fast collection 23. and dissemination of information New pharmacovigilance methods need to be developed and adapted to the ways the reporters of information (whether healthcare professionals or patients) are used to exchange information. Using a web-based intensive monitoring system, data can be collected in a fast 28. and relatively cheap way enabling collection of data in a longitudinal manner during a long 29. period of time. By collecting longitudinal data, it is possible to follow the time course of ADR, 30. information that very few methods today can provide

164 164 Chapter References Merck Announces Voluntary Worldwide Withdrawal of VIOXX. Merck & Co Available via Accessed June 24, Bresalier RS, Sandler RS, Quan H, et al. Cardiovascular events associated with rofecoxib in a colorectal adenoma chemoprevention trial. N Engl J Med 2005; 352: Krumholz HM, Ross JS, Presler AH, et al. What have we learnt from Vioxx? BMJ 2007; 334: Strom BL. How the US drug safety system should be changed. JAMA 2006; 295: Mitka M. Report criticizes lack of FDA oversight. JAMA 2006; 296: The Importance of Pharmacovigilance. WHO 2002 Available via Accessed June 24, Committe on the Assessment of the US Drug Safety System. In: Baciu A, Stratton K, Burke SP. editors. The future of drug safety: promoting and protecting the health of the public. Institute of Medicine; Washington DC, Assessment of the European Community System of Pharmacovigilance. Fraunhofer Available via rappfraunhofer.pdf Accessed June 24, Strategy to better protect public health by strengthening and rationalising EU pharmacovigilance. European Commission Enterprise and Industry Directorate-general, Regulation 1235/2010. Official Journal of the European Union 10 A.D.,L Available via 6:EN:PDF Accessed June 23, Directive 2010/84/EU. Official Journal of the European Union 2010,L Available via 9:EN:PDF Accessed June 24, Waller P. Getting to grips with the new European Union pharmacovigilance legislation. Pharmacoepidemiol Drug Saf 2011; 20: Raine JM. Risk management - a European Regulatory View. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 14. Borg JJ, Aislaitner G, Pirozynski M, et al. Strengthening and rationalizing pharmacovigilance in 25. the EU: where is Europe heading to? A review of the new EU legislation on pharmacovigilance Drug Saf 2011; 34: Garattini S, Bertele V. Anything new in EU pharmacovigilance? Eur J Clin Pharmacol Published online 4 May Waller PC, Evans SJ. A model for the future conduct of pharmacovigilance. Pharmacoepidemiol Drug Saf 2003; 12: Härmark L, van Puijenbroek E, Straus S, et al. Intensive monitoring of pregabalin results from an observational, web-based, prospective cohort study using patients as a source of information. Drug Saf 2011; 34: Mackay FJ. Post-marketing studies: the work of the Drug Safety Research Unit. Drug Saf 1998; : Harrison-Woolrych M, Coulter DM. PEM in New Zealand. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester Shakir SAW. PEM in the UK. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester de Langen J, van Hunsel F, Passier A, et al. Adverse drug reaction reporting by patients in the Netherlands: three years of experience. Drug Saf 2008; 31:

165 Application of web-based intensive monitoring Aagaard L, Nielsen LH, Hansen EH. Consumer reporting of adverse drug reactions: a retrospective analysis of the Danish adverse drug reaction database from 2004 to Drug Saf 2009; 32: McLernon DJ, Bond CM, Hannaford PC, et al. Adverse drug reaction reporting in the UK: a retrospective observational comparison of yellow card reports submitted by patients and healthcare professionals. Drug Saf 2010; 33: van Hunsel F, Talsma A, van Puijenbroek E, et al. The proportion of patient reports of suspected ADRs to signal detection in the Netherlands: case-control study. Pharmacoepidemiol Drug Saf 2011; 20: Härmark L, Puijenbroek E, Grootheest K. Longitudinal monitoring of the safety of drugs by using a web-based system: the case of pregabalin. Pharmacoepidemiol Drug Saf 2011; 20: Human Medicines EMEA Pre-Submission Guidance European Medicines Agency. Available via Accessed Guideline on Risk management Systems for Medicinal Products for Human Use European Medicines Agency. Available via Accessed Segal ES, Valette C, Oster L, et al. Risk management strategies in the postmarketing period : safety experience with the US and European bosentan surveillance programmes. Drug Saf 2005; 28: Layton D, Rutherford D, MacDonald TM, et al. Pilot swine flu vaccination active surveillance study: design and rationale [Abstract]. Drug Saf 2011; 33: Layton D, Rutherford D, MacDonald TM, et al. Pilot Swine Flu Vaccination Active Surveillance Study: Interim results [Abstract]. Drug Saf 2011; 30: Härmark L, van Hunsel F, Hak E, et al. Monitoring the safety of influenza A (H1N1) vaccine using web-based intensive monitoring. Vaccine 2011; 29:

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167 Chapter 7 General discussion

168

169 General discussion General discussion The objective of this thesis is to describe a web-based intensive monitoring system using 4. patients as a source of information and its application as a pharmacovigilance tool. In the 5. final chapter of this thesis the main findings will be summarised and discussed and additional 6. applications of the system as well as possible future research will be presented Method development in pharmacovigilance 9. The renewed attention for pharmacovigilance the last decade has led to an increased activity in developing methods that can lead to timely and more detailed identification of harm Post-marketing studies can roughly be divided into descriptive or analytical studies. Descriptive studies, such as spontaneous reporting and intensive monitoring, generate signals and analytical studies, such as pharmaco-epidemiological studies, test hypotheses and seek to 14. confirm signals and measure the size of these effects [1]. Much focus has been on developing 15. methods that make use of already existing sources of information, for example electronic 16. healthcare records, administrative and insurance claims databases, and registries. By linking 17. various kinds of databases, signals of adverse drug reactions can be identified or confirmed. 18. In the US, the Sentinel Initiative was started in 2008 with the aim to develop and implement a 19. proactive system that will complement existing pharmacovigilance systems that the FDA has 20. already in place [2]. Recently the first step in the Sentinel Initiative, the Mini-Sentinel has been 21. described in depth [3-5]. Mini-sentinel has access to data about nearly 100 million patients, billion prescription drug dispensations and 2.4 billion unique medical encounters [2] in 23. which they can perform signal detection or conduct research to confirm signals In the European Union similar initiatives have been taken, for example the EU-ADR project 26. where electronic healthcare record data from over 30 million patients from several European 27. countries has been used in order to develop new signal detection techniques [6]. Another initiative is the Pharmacoepidemiology Research on Outcomes of Therapeutics by a European ConsorTium (PROTECT) which is developing a set of innovative tools and methods that will 30. enhance the early detection and assessment of adverse drug reactions from different data 31. sources [7] These developments illustrate that the methods that were primarily used in pharmacoepidemiology in the past are being applied to a wider extent in pharmacovigilance today Techniques using already existing sources of information in the search for signals of adverse 36. drug reactions make it possible to perform studies in large populations and if a safety issue 37. emerges, offer the possibility to rapidly conduct studies to confirm or reject the safety signal. The biggest limitation of these methods is that they use data that was not merely collected with the aim of generating knowledge about adverse drug reactions, therefore not all the 7

170 170 Chapter information one might want to have about the safety of drugs is available, simply because the data needed to give answers to these questions is lacking. In addition, by using data primarily collected for another purpose makes it almost impossible for the researcher to go back to the case (patient) to obtain more clinical information which might be necessary in order to, for example, confirm the diagnosis. Pharmacovigilance, as has been described in this thesis, started with the clinical observation of one doctor that was shared with others through a letter in the Lancet [8]. Spontaneous reporting as a method relies on the clinical observations of healthcare professionals and their ability to recognise new adverse drug reactions. This concerned reporting [9] acts as a pre-selection in what might be a signal, enhancing the chance of finding a signal among the reports. Spontaneous reporting has met a lot of criticism in the past. The main points of criticism are under-reporting [10] and the inability to calculate incidences of adverse drug reactions. However, the latter point has never been the goal of the system. It merely focuses on the identification of clinical events that may represent adverse drug reactions. Further confirmation or estimation of incidences has to be carried out by other methods. Web-based intensive monitoring as a pharmacovigilance tool Web-based intensive monitoring was aimed at combining the strengths of both the pharmaco-epidemiological approach as well as the clinical pharmacovigilance approach. The method needed to be close to clinical practice and be able to contribute to the extension of knowledge about the safety of drugs in ways that other methods available today cannot do. The characteristics of web-based intensive monitoring are: It is an active method which monitors selected drugs during a certain period of time. In contrast to spontaneous reporting that passively monitors all drugs during their whole life cycle, web-based intensive monitoring focuses on certain drugs during a limited time period in which information about adverse drug reactions is actively asked for. In this manner, for the monitored drugs, much information can be obtained in a relatively short time period as compared to spontaneous reporting. It is a non-interventional observational cohort study. Through its non-interventional character it provides real world clinical data with no limiting inclusion or exclusion criteria as compared to clinical studies [11]. In addition, because it is a cohort study, it allows for estimation of the incidence of adverse drug reactions which makes it possible to quantify the risk of certain reactions. Although a causality assessment has not been performed on all the information gathered with webbased intensive monitoring, it was chosen to use the term adverse drug reaction instead

171 General discussion of adverse events for the reactions reported because patients are asked only to report symptoms that they believe are associated with the use of the drug It follows first time users from the first day of use, collecting longitudinal data through multiple questionnaires. This approach makes it possible to gather time related information about adverse drug reactions. The longitudinal collection of data gives the possibility to obtain more information about the time course of an ADR, for example when it occurs and if stopping the drug would be necessary for recovery. This type of information is difficult to obtain through spontaneous reporting since it only gives a cross-sectional view. By using electronic healthcare records it is also difficult to obtain this kind of information, since this information is quite specific for adverse drug reactions and not often available in electronic healthcare records. It uses the patient as the source of information. By using patients as a source of information, as compared to healthcare professionals, the reactions are reported by the ones who actually have experienced the ADR, reducing the risk of underreporting. In addition, it might be possible to identify signals for reactions that were not necessarily suspected as being ADRs by healthcare professionals [12]. It uses web-based technology to collect data. Through its web-based character it is a very fast and flexible system. Data are immediately transferred to the database, eliminating the step of manual data entry. Flexible because it is possible to customise the questionnaires for each study. In addition, web-based data collection enables structural data collection which improves data quality Patient as a source of information Although some countries have allowed patients to report to a spontaneous reporting system for decades [13], it is in the past decade that the role of patients in pharmacovigilance has been properly acknowledged [14,15]. The existing intensive monitoring systems in place [16,17] use general practitioners or other medical doctors as a source of information, although in 2012 the IMMP in New Zealand reported that they are trying to use patients information in their intensive monitoring system as well [18]. The contribution of patient reporting to spontaneous reporting systems has been described in literature [12], but there is little information about patients participation in active pharmacovigilance systems such as intensive monitoring. In order to gain more knowledge about patients as a source of information in active pharmacovigilance systems, this was further investigated in this thesis (Chapter 3). 7

172 172 Chapter 7 1. In Chapter 3 patients motives for participating in a web-based intensive monitoring system 2. as well as their experiences with this system were investigated using a mixed model approach. This research was performed since it is of vital importance to have enough patients participating in web-based intensive monitoring to gather data about the safety of drugs. If 5. the patients do not want to participate, that would render the system useless. By knowing the 6. motives for participation, it is also possible to adjust the presentation of web-based intensive 7. monitoring, to make it more appealing to future patients eligible for participation. The study 8. showed that the main motives for participation can be classified as altruistic reasons, for example Other patients can be treated better (89%) and I want to help healthcare workers (84%) Often experiencing ADRs or other negative experiences with drugs are not important as 11. motivation. The patient s gender is an important determinant for the motivation. Women are 12. more inclined to participate on altruistic grounds and because they experience more adverse 13. drug reactions and are more worried about interactions than men. For men, having personal 14. gain from the results was more important as compared to women. The overall opinion about 15. the web-based intensive monitoring system is very positive; completing the surveys with the 16. computer seems to be easy [19] The study described above was conducted in a population that is already participating with 19. web-based intensive monitoring which might give a biased view towards the positive. The 20. first web-based intensive monitoring studies have shown that not all patients who are eligible 21. for inclusion chose to participate. The reasons for non-participation are unclear, however 22. both pharmacies and patients may be contributing factors. The pharmacy because informing the patient about the study is a prerequisite for participation. The patients because they are the ones actually providing the information. In Chapter 3 reasons for non-participation 25. were investigated to see if barriers for participation could be identified. The major reason 26. for non-participation was that patients were not informed in the pharmacy about the study, % did not get any information and around 20% could not remember if they had gotten any 28. information. For the patients who received information about web-based intensive monitoring, not having access to internet was the reason for non-response for about a quarter of the patients. For those with access to internet, about a quarter stated that they tried to register 31. for the study but failed. Not one major reason was identified for non-response except that 32. most patients found that they would gain very little on an individual level by participating. 33. Because about half of all patients were not asked about participation in the pharmacy, it was 34. investigated if receiving information about the system was influenced by the patient s age 35. or gender. Our study shows that age and gender did not influence if the patient received 36. information in the pharmacy. 37. The relatively high response to the postal questionnaire (around 40%), together with the answers about reasons for non-response suggests that patients are willing to participate

173 General discussion in an active pharmacovigilance system if they are asked and have the means to do so, i.e 2. internet access [20] These studies show that patients are prepared to give their time in order to contribute to 5. increasing knowledge about the safety of drugs by participating in a web-based intensive 6. monitoring system. The main cause of non-response is that a majority of patients who receives 7. a first dispensation of the drug in the pharmacy is not informed about the study. In order to 8. increase the response rate, measures have to be taken to increase pharmacy participation in 9. web-based intensive monitoring Information obtained from web-based intensive monitoring 12. One of the aims of this thesis was to provide proof of concept for web-based intensive 13. monitoring. In Chapter 5, three studies are described that show that web-based intensive 14. monitoring can generate information relevant for pharmacovigilance. Chapter 5.1 and 5.2 are 15. focused on the safety and user profile of pregabalin and duloxetine respectively. In addition 16. to providing data about safety such as incidences of adverse drug reactions and signals, the 17. system could also provide information about the use of the drug in daily practice such as 18. gender distribution, age, drug dose and indication for use. From these data, it is possible to 19. see if the drug is prescribed off-label both with regards to the indicated age as well as the 20. registered indication and starting dose. In the duloxetine study it was also possible to obtain 21. information about channeling [21,22] Chapter 5.1 and 5.2 show that web-based intensive monitoring can provide the information 24. it was intended to provide (estimation of incidences and detection of signals). In addition, 25. it can also provide extensive information about the use of a drug in daily practice. It was 26. not designed for this purpose, but direct collection of information from patients makes it 27. possible to collect all kind of information regarding drug use and adverse drug reactions, 28. for example the impact of an ADRs on the quality of life. The possibilities that web-based 29. intensive monitoring offer in terms of data collection have to be explored further In pharmacovigilance there is a need for more information about adverse drug reactions 32. such as the time course of ADRs. If it is clear when an ADR occurs and how long it persists, this 33. knowledge can help motivate the patient to be adherent to his medication when experiencing an ADR. With web-based intensive monitoring longitudinal data is collected, making it possible to answer this type of questions. Chapter 5.3 shows that with web-based intensive 36. monitoring it is possible to make an ADR profile for a drug at different points in time. By 37. calculating incidence densities it is possible to show when an ADR occurs, for example the five most frequently reported ADRs in relation to the use of pregabalin occur early in the treatment with the highest incidence in the first two weeks. Since web-based intensive 7

174 174 Chapter 7 1. monitoring not only registers ADRs but also drug use, it is possible to see what action patients undertake when experiencing an ADR. Surprisingly the majority of patients does not undertake any action when experiencing an ADR. In addition, it is also possible to study the 4. outcome of a reaction. For dizziness during pregabalin use 66.1% of the patients who had 5. stopped pregabalin were reporting to have recovered or were recovering. On the other hand, % of those who continued pregabalin use reported that they were recovering or had 7. recovered of dizziness. This study shows that with the collection of longitudinal data, it is 8. possible to generate information that until now has been very difficult to obtain which makes 9. it a valuable addition to the pharmacovigilance tools used today Even though the sample sizes in both cohorts presented were quite small, it was still possible 12. to detect signals with a case by case approach. However, in the future when cohort sizes are 13. increasing, methods for (statistical) signal detection have to be developed. With increasing 14. cohort sizes it will also be possible to further explore the possibilities that the longitudinal 15. data collection offer and make full use of the potential that this kind of data collection offers Application of the results from web-based intensive monitoring to the general 18. population 19. Almost all research that is conducted is not performed on the whole population of interest 20. since that would be very expensive and time consuming. In most cases it is chosen to perform 21. the research in a representative sample of the population and if the sample is truly representative, the results can be generalised to the population at large. In web-based intensive monitoring, only a small proportion of the patients eligible for participation eventually chose 24. to participate. This does not necessarily have to be a problem but it is important to know 25. how the patients participating in the study compare to the whole population of patients 26. receiving the drug. If the non-inclusion or non-response is not random, it can lead to bias and 27. ultimately influence the generalisability of the results obtained In Chapter 3.2 a direct comparison was made between responders and non-responders 30. in web-based intensive monitoring. This study showed a significant difference between 31. non-responders and responders in age and the number of drugs used as co-medication. 32. Non-responders were older and used slightly more co-medication than responders. No differences in gender distribution were detected [20] In Chapter 4 the web-based intensive monitoring population participating in the diabetes 36. study was compared to an external diabetes reference population. The comparison showed 37. differences in patient characteristics, diabetes characteristics and number of co-medications. Patients participating in web-based intensive monitoring were more often men and in general younger and healthier, by that meaning that they were more often de novo patients,

175 General discussion had a shorter diabetes treatment duration and used less co-medication than patients in the 2. reference population [23] From these studies it is clear that there is a difference in age and the number of co-medication 5. between the patients participating in web-based intensive monitoring compared to both the 6. population at large as well as the reference population. As to gender, it is not possible to 7. draw firm conclusions since the studies give contradicting results. When generalising results 8. from web-based intensive monitoring, these differences have to be taken into account. As 9. older age, more concomitant drugs and female gender [24-27] has been associated with an 10. increased susceptibility for ADRs, the results from web-based intensive monitoring studies 11. would probably give an underestimation of the frequency of adverse drug reactions Applications of web-based intensive monitoring as a pharmacovigilance tool 14. The basic principles of web-based intensive monitoring, having a specific point of inclusion 15. and follow patients over time with web-based questionnaires can be applied in other settings with other research questions as the ones presented in this thesis. In Chapter 6.1 there is an example of how web-based intensive monitoring was used to investigate the safety of 18. the Influenza A (H1N1) vaccine when issues around its safety arose. In this case, the pharmacy 19. was not the inclusion point, but the general practitioner s office where the vaccines were administered. Because of its web-based character it was possible to set up, conduct the study and analyse the results rapidly and within the shortest time possible provide information 22. about the safety of the vaccine Conclusions and further research 25. The studies in this thesis were focussed on showing what kind of information can be collected 26. with web-based intensive monitoring and to characterise the method. In this last chapter, 27. limitations and possible further research is discussed Our studies show that patients are motivated to participate in this kind of research and that 30. the main motivation is to do good (altruism) but the inclusion in the pharmacy sometimes 31. restricts patient participation. In order to come to terms with this limitation and increase 32. patient participation, pharmacies need to provide information more actively about the participation. In the years to come it has to be investigated how the pharmacy s commitment to web-based intensive monitoring can increase An aspect of patient participation that has not been investigated in this thesis is the validity 37. of the answers that patients provide. In Chapter 4.1 it was shown that the number of comedication reported by participants in web-based intensive monitoring did not increase by age as one would expect. The validity of the patient s answers about co-medications could 7

176 176 Chapter 7 1. be investigated by comparing the medication reported in web-based intensive monitoring 2. with the information in the pharmacy information system. Another issue touching upon the 3. validity of patient reported outcomes is the type of reactions that are reported in Chapter Patients primarily reported ADRs that manifested itself as symptoms. ADRs which in the first 5. place are asymptomatic are rarely reported and this can possibly bias the ADR profile generated by web-based intensive monitoring. The limitations of web-based intensive monitoring as described above need to be addressed in future research since it important for the validity 8. of the system The results originating from web-based intensive monitoring include both quantification of 11. ADRs, identification of signal as well as time related information about adverse drug reactions. In order to interpret and generalise the results from web-based intensive monitoring studies it is important to know how a web-based intensive monitoring population compares 14. to the whole population using the drug. The studies in which this was investigated showed 15. that patients participating in web-based intensive monitoring are in general younger and 16. use less co-medication than patients who do not participate, which is a limitation. Further 17. research has to be done in order to see if these differences will lead to a different response to 18. the drug and thereby influencing the generalisability of the results This thesis has demonstrated that web-based intensive monitoring is an additional tool in 21. the pharmacovigilance toolkit. The method needs to be developed further and needs to be 22. implemented in more settings, but it holds potential for becoming an important method of 23. collecting information about adverse drug reactions Future perspectives 26. The basic idea behind web-based intensive monitoring, using a special point of inclusion, 27. using patients as a source of information and collecting longitudinal information directly 28. from clinical practice using web-based questionnaires has more possibilities than the ones 29. described in this thesis In this thesis the pharmacy has been the point of inclusion in all but one studies. By changing 32. the inclusion point from the pharmacy to other inclusion points such as the prescribing doctor or other healthcare professionals it will be possible to monitor all kind of drugs, not only drugs that are dispensed through community pharmacy. By changing the inclusion point, 35. the type of information that can be obtained also changes. If the inclusion is in an intramural 36. setting it gives the possibility to use data from the institutions own system together with the 37. data from web-based intensive monitoring. As a methodology, web-based intensive monitoring does not need to have a certain drug as a starting point, it can also have a certain population as starting point, for example children,

177 General discussion elderly or pregnant women. In these populations drugs are often prescribed off-label and 2. the safety profile might be different than for the indications the drug was registered for. 3. Since information about drug use and ADRs in these groups are scarce, web-based intensive 4. monitoring could provide useful information. For this kind of research the aim would be to 5. investigate what drugs a certain group of people use, the dosage, indications and adverse 6. drug reactions. In the case of pregnant women, possible congenital abnormalities can be 7. taken into account as well Web-based intensive monitoring was developed to gather information about adverse drug 10. reactions. By collecting longitudinal data, it is possible to gather time related data concerning ADRs such as time to onset and duration. The method does not have to be restricted to collection of ADRs only. It can also be used to investigate other aspects of drug use such as 13. the impact of drug use and adverse drug reaction on the quality of life, adherence to drug 14. therapy and even efficacy In the EU, the recent legislative changes will have a major impact on the conduct of pharmacovigilance. With the new legislation regulators will have the legal power to request Post Authorisation Safety Studies (PASS) as a condition of marketing authorisation. In order for 19. PASS to be useful, methods have to be developed which can ensure that the information 20. gathered with PASS can help regulators to make a decision about a drug s benefit-harm balance. Web-based intensive monitoring can play an important role in this

178 178 Chapter References 1. Wardell WM, Tsianco MC, Anavekar SN, et al. Postmarketing surveillance of new drugs, Review of objectives and methodology. J Clin Pharmacol 1979; 19: FDA s Sentinel Initiative. Food and Drug Administration Available via gov/ Safety/FDAsSentinelInitiative/ucm htm Accessed Feb 7, Platt R, Carnahan RM, Brown JS, et al. The U.S. Food and Drug Administration s Mini-Sentinel program: status and direction. Pharmacoepidemiol Drug Saf 2012; 21 Suppl 1: Robb MA, Racoosin JA, Sherman RE, et al. The US Food and Drug Administration s Sentinel Initiative: Expanding the horizons of medical product safety. Pharmacoepidemiol Drug Saf 2012; 21 Suppl 1: Forrow S, Campion DM, Herrinton LJ, et al. The organizational structure and governing principles of the Food and Drug Administration s Mini-Sentinel pilot program. Pharmacoepidemiol Drug Saf 2012; 21 Suppl 1: EU-ADR project. Available via alert-project org/drupal/?q=home Accessed Feb 7, PROTECT. Available via imi-protect eu/index html Accessed Feb 7, McBride WG. Thalidomide and congenital malformations. Lancet 1961; 2: Edwards IR. Spontaneous reporting-of what? Clinical concerns about drugs. Br J Clin Pharmacol 1999; 48: Hazell L, Shakir SA. Under-reporting of adverse drug reactions : a systematic review. Drug Saf 2006; 29: Stricker BH, Psaty BM. Detection, verification, and quantification of adverse drug reactions. BMJ 2004; 329: van Hunsel F. The contribution of direct patient reporting to pharmacovigilance, Thesis Groningen University van Hunsel F, Härmark L, Pal S, et al. Experiences with adverse drug reaction reporting by patients: an 11-country survey. Drug Saf 2012; 35: Directive 2010/84/EU. Official Journal of the European Union 2010, Dec 31,L Regulation 1235/2010. Official Journal of the European Union 2010, Dec 31,L Harrison-Woolrych M, Coulter DM. PEM in New Zealand. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester. 17. Shakir SAW. PEM in the UK. In: Mann R, Andrews E (eds) Pharmacovigilance. 2nd edn Wiley, Chichester 18. Harrison-Woolrych M. Patient reporting encouraged during monitoring of dapoxetine in New Zealand. Drug Saf 2011; 34: Härmark L, Lie-Kwie M, Berm L, et al. Patients Motives for Participating in Active Post Marketing Surveillance. Submitted. 20. Härmark L, Huls H, de Gier H, et al. Non-response in a pharmacy and patient based intensive monitoring system. Submitted. 21. Härmark L, van Puijenbroek E, Straus S, et al. Intensive monitoring of pregabalin results from an observational, web-based, prospective cohort study using patients as a source of information. Drug Saf 2011; 34: Härmark L, van Puijenbroek E, van Grootheest K. Intensive Monitoring of Duloxetine, Results from a web-based intensive monitoring study. Submitted. 23. Härmark L, Alberts S, Denig P, et al. Representativeness of diabetes patients participating in a web-based adverse drug reaction monitoring system. Submitted. 24. Begaud B, Martin K, Fourrier A, et al. Does age increase the risk of adverse drug reactions? Br J Clin Pharmacol 2002; 54:550-2.

179 General discussion Gurwitz JH, Avorn J. The ambiguous relation between aging and adverse drug reactions. Ann Intern Med; 114: Tran C, Knowles SR, Liu BA, et al. Gender differences in adverse drug reactions. J Clin Pharmacol 1998; 38: Leendertse AJ, Egberts AC, Stoker LJ, et al. Frequency of and risk factors for preventable medication-related hospital admissions in the Netherlands. Arch Intern Med 2008; 168:

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181 Summary Samenvatting Sammanfattning

182

183 Summary Summary Drugs are prescribed to treat, cure, prevent or diagnose disease but sometimes the patient 4. can experience, besides the positive effect of the drugs, adverse drug reactions (ADRs). The 5. science which focuses on adverse drug reactions is called pharmacovigilance. Pharmacovigilance is defined by the WHO as the science and activities relating to the detection, assess ment, understanding and prevention of adverse effects or any other drug related problem Chapter 2 gives an introduction to pharmacovigilance and the methods used to collect data 10. about ADRs are described. The collection of adverse drug reaction reports from healthcare 11. professionals and patients, also known as a spontaneous reporting system (SRS) has been 12. the back bone of pharmacovigilance since the birth of the discipline in the 1960s. The main 13. function of a SRS is the early detection of signals of new, rare and serious ADRs. A SRS is 14. an efficient and inexpensive system, which monitors the safety of drugs throughout their 15. whole life cycle. However, it has some limitations, the most frequently mentioned are underreporting and the inability to calculate incidences. Although critics say that a SRS is not the ideal method for monitoring the safety of drugs, it has proven its value throughout the years Besides spontaneous reporting there is also a need for more structured data collection about 20. the safety of drugs. A way to actively gather information about adverse drug reactions is 21. through intensive monitoring. The basis of intensive monitoring is a non-interventional 22. cohort, which distinguishes itself from spontaneous reporting because the former only 23. monitors selected drugs during a certain period of time. Intensive monitoring enables the 24. incidence of adverse events to be estimated. This approach, however, also has recognised 25. limitations. The proportion of adverse effects that go unreported to doctors is unknown and 26. the studies also produce reported event rates rather than true incident rates. This is the same 27. for all studies based on medical record data, including computer databases and record linkage The Netherlands Pharmacovigilance Centre Lareb has developed a web-based intensive 31. monitoring system called Lareb Intensive Monitoring (LIM). Patients eligible for inclusion in 32. LIM are identified in the community pharmacy when receiving the first dispensation of a 33. drug which is being studied. The patient is informed about the intensive monitoring study 34. and is asked to participate. After registering online, the patient receives questionnaires by e- 35. mail at specific points in time, allowing longitudinal data collection. In these questionnaires, 36. questions are asked about patient characteristics, drug use and possible ADRs. These data 37. are coded and analysed with the purpose of identifying new signals or information that will extend the knowledge about the safety of the drug under study. In August 2006 the LIM system was taken into use. 183

184 The objective of this thesis is to describe a web-based intensive monitoring system using patients 3. as a source of information and its application as a pharmacovigilance tool In Chapter 3 the patient as the source of information about ADRs is further explored. The first 6. study focuses on patients motives for participating in intensive monitoring. To date little is 7. known about patients motivation to participate in active pharmacovigilance systems such as 8. LIM. Increased insight into patients motives for participating can help to better understand 9. and interpret patient reported information. Increased knowledge about patients motives 10. for participation can also be used for developing and improving patient based pharmacovigilance tools. Patients motives for participation were first explored in 21 semi-structured in-depth interviews. The information gathered through these interviews formed the basis for 13. a questionnaire which was sent to over 2000 LIM participants. The main motives for participating with LIM are mainly altruistic: Other patients can be treated better (89%) and I want to help healthcare workers (84%) Not all patients who are eligible for inclusion chose to participate with web-based intensive 18. monitoring. By identifying reasons for non-response, measures to increase patient participation can be taken. In the second study reasons for non-response were investigated using a paper questionnaire. The main reason for non-response was that the patients were not asked 21. to participate in LIM by the pharmacy. 50.9% of the patients did not receive information 22. about LIM in the pharmacy and another 21.2% did not remember if they received information 23. or not. For the patients who received information about LIM, not having access to internet 24. was the reason for non-response for about a quarter of the patients. For those with access to 25. internet, about a quarter stated that they tried to register for the study but failed. Of all possible reasons for non-response not one major reason was identified except that most patients found that they would gain very little on an individual level by participating For a new pharmacovigilance system such as LIM to be a useful tool, it is important to know 30. whether the population who chooses to participate with LIM is comparable to the whole 31. population using the drug. Otherwise it might be difficult to extrapolate the results to the 32. population at large. In Chapter 4 the representativeness of the LIM diabetes population was 33. compared to a reference population derived from the Groningen Initiative to ANalyse Type diabetes Treatment (GIANTT) database which is a registry of ambulant patients with type diabetes mellitus in the northern part of the Netherlands. The LIM diabetes population 36. was compared to the reference population on parameters which might influence a patient s 37. susceptibility to develop an ADR, such as age, gender, Body Mass Index (BMI) and polypharmacy. Comparisons were also made between the two populations regarding clinical 184

185 Summary parameters related to their diabetes status, such as diabetes medication used, and diabetes 2. treatment duration The comparison of the LIM diabetes population with a reference population showed differences in patient characteristics, diabetes characteristics and number of co-medication. LIM patients were in general younger and healthier, by that meaning that they were more often 7. de novo anti-diabetic drug users, had a shorter treatment duration and used less co-medication than patients in the reference population. In contrast to the reference population, co-medication did not increase for patients in the LIM population with increasing age. These 10. differences might lead to an underestimation of adverse drug reactions but it is not clear 11. whether this would also influence the type or time-course information of ADRs reported. 12. Differences found in this study have to be taken into account when interpreting results from 13. web-based intensive monitoring studies In Chapter 5 the results from the first web-based intensive monitoring studies are presented. 16. Two studies concern the safety of pregabalin, a drug registered for the treatment of neuropathic pain, epilepsy and generalised anxiety disorder and one study concerns the safety of duloxetine which is registered for the treatment of major depressive disorder, diabetic 19. peripheral neuropathic pain and generalised anxiety disorder The pregabalin cohort consisted of 1373 patients who were followed for 6 months with webbased intensive monitoring. 796 (58.0%) of these were female. The average age was 54.5 (SD ) years, ranging from years. Neuropathic pain was the indication in 85.9% of cases. 24. Of all included patients, 1051 (76.5%) completed at least one questionnaire, providing data 25. on whether or not they had experienced any possible ADRs. The five most reported ADRs 26. were dizziness, somnolence, feeling drunk, fatigue and increased weight. Four associations 27. with pregablin, namely headache, upper abdominal pain, drug-drug interactions between 28. pregabalin and blood-glucose lowering drugs and suicidal ideation were considered to be 29. signals. This study indicates that pregabalin is a relatively safe drug as used by patients in 30. daily practice over a period of 6 months In the pregabalin study patients filled in questionnaires 2 weeks, 6 weeks, 3 months and months after the start of the drug use. In the second pregabalin study, the time course of 34. ADRs was analysed in more detail. On an aggravated level, the ADR profile of pregabalin 35. remained relative stable over time. The five most frequently reported ADRs were analysed in 36. more detail. Calculation of incidence densities showed that they occur early in the treatment, 37. with the highest incidence in the first 2 weeks. This is consistent with the fact that these ADRs are probably type A ADRs, a direct pharmacological effect of the drug. Initially, the majority of the patients did not undertake any action when experiencing an ADR. The outcome of the 185

186 ADR was not solely dependent on drug cessation. 66.1% of the patients who had stopped 2. pregabalin use due to dizziness were reporting to have recovered or were recovering. In contrast, 46.5% of those who continued pregabalin use while experiencing dizziness, reported that they were recovering or had recovered. In this case, a rather large proportion of the 5. patients who continued the use of pregabalin also recovered from dizziness, indicating that 6. dizziness may be a transitory ADR, not always requiring cessation of the drug in order to 7. disappear The safety of duloxetine was investigated in a cohort consisting of 398 patients of which % were female. The average age was 47.0 (SD 12.3 ) years, ranging from 14 to 82 years. 11. The main indication was depression (66.7%) followed by neuropathic pain (16.1%) and fibromyalgia (4.3%). Of the 398 patients that registered for the study, 303 patients (76.1%) filled in at least one questionnaire. Of these 239 (78.9%) reported an ADR. The most frequently reported ADRs were consistent with the ADRs described in the SPC of duloxetine. Four patients (1.3%) experienced a serious ADR, of which one was fatal due to electrolyte disturbances. 16. Three signals were identified, amenorrhea, shock-like paraesthesia and micturition problems, 17. which need to be further evaluated in more detail. This study indicates that the ADR profile of 18. duloxetine as reported by patients during six months in daily practice is similar to the profile 19. described in the SPC of duloxetine In all studies described so far, the community pharmacy has been the point of inclusion. 22. Web-based intensive monitoring was originally developed with community pharmacies 23. as the inclusion point, but other inclusion points are also possible. In Chapter 6 a study is 24. described where the safety of the Influenza A (H1N1) vaccine was monitored using the general practitioner s office as the point of inclusion. Adults aged 60 years and older or persons with a risk-elevating medical condition recommended for pandemic influenza vaccination 27. in general practice were eligible for participation. After receipt of the first pandemic vaccine 28. the administrator provided an information flyer of the web-based monitoring program. The 29. patient could sign up for study participation online. Within one week, three weeks and three 30. months after the first immunisation questions were asked about demographics and health, 31. immunisations, injections site reactions and labeled reactions as well as other possible 32. new Adverse Events Following Immunisation (AEFIs) In total 3569 patients participated in 33. this study. Of all participants, 1311 (37%) reported an AEFI. Unexpected serious reactions 34. were not reported nor were there signals of possible new AEFIs. The reactions reported were 35. expected and non-serious. Injection site reactions and labeled AEFIs have a short latency, a 36. short duration and are in most cases self-limited. The occurrence of an AEFI was determined 37. by gender, age and type of co-morbidity. The results from this study did not raise any concerns about the safety of the pandemic influenza vaccine used in the Netherlands. 186

187 Summary The study mentioned above showed that it is possible to use the web-based intensive monitoring methodology also in other settings. In Chapter 6.2 possible future applications of web-based intensive monitoring are discussed in more detail, a summary hereof is given 4. below. The European countries have made efforts to develop drug safety within the registration procedure without slowing down the registration process; an example of this is the conditional marketing authorisation. In order to be able to follow a drug after (conditional) 7. approval and monitor its ADRs, web-based intensive monitoring could be used. It is possible 8. to identify users of a specific drug via this system and follow these users over time. This would 9. generate real life data on the safety without the limitations from clinical trials and spontaneous reporting. If there are special risks that have to be addressed, the questionnaires can be customised in order to fit the needs of the particular research question The web-based intensive monitoring system could also be used in creating registries for 14. certain drugs. For some drugs, a drug monitoring program on a voluntary basis is not sufficient. In these cases, a registry is necessary so that every user of the drug can be followed Participation in the registry will be a condition for the patient to obtain the drug As a methodology, web-based intensive monitoring does not need to have a certain drug 19. as a starting point, it can also have a certain population as the starting point, for example 20. children, elderly or pregnant women. In these populations drugs are often prescribed offlabel and the safety of these drugs might differ from the indications the drug is registered for Since knowledge about drug use and ADRs in these groups is scarce, web-based intensive 23. monitoring could provide useful information. For this kind of research the aim would be to 24. investigate what drugs are used by a certain group of people, including information on the 25. dosage, indications and ADRs. In the case of pregnant women, possible congenital abnormalities can be taken into account as well At the moment there is much attention for developing methods that make use of already existing sources of information, for example electronic healthcare records, administrative- and insurance claims databases, and registries. The biggest limitation of these methods is that 31. they use data that was not merely collected with the aim of generating knowledge about 32. adverse drug reactions. Therefore not all the information one might want to have about 33. the safety of drugs is available, simply because the data needed to give answers to these 34. questions is lacking. The design of web-based intensive monitoring was aimed at combining 35. the strengths of both the pharmaco-epidemiological approach as well as the clinical pharmacovigilance approach. The method needs to be close to clinical practice and to be able to contribute to the extension of knowledge about the safety of drugs in ways that other methods available today cannot do. 187

188 The aim of this thesis was to show what kind of information can be collected with web-based 2. intensive monitoring and to characterise the method. In Chapter 7, limitations and possible 3. further research is discussed. In conclusion this thesis has demonstrated that web-based 4. intensive monitoring is a valuable additional tool in the pharmacovigilance toolkit. The 5. method needs to be developed further and needs to be implemented in more settings, but it 6. holds potential for becoming an important method of collecting information about adverse 7. drug reactions

189 Samenvatting Samenvatting Geneesmiddelen worden toegepast om ziektes te behandelen, te voorkomen en te diagnosticeren. In sommige gevallen ervaart de patiënt niet alleen het gewenste effect, maar kun nen ook ongewenste effecten, ofwel bijwerkingen, optreden. De wetenschap die zich bezig 6. houdt met bijwerkingen wordt geneesmiddelenbewaking of farmacovigilantie genoemd. 7. Farmacovigilantie is door de Wereld Gezondheids Organisatie (WHO) gedefineerd als de 8. wetenschap en de activiteiten met betrekking tot de opsporing, beoordeling, kennis en preventie 9. van bijwerkingen of andere mogelijke aan geneesmiddelen gerelateerde problemen Hoofdstuk 2 legt uit wat farmacovigilantie is en beschrijft de methoden die gebruikt worden 12. om informatie over bijwerkingen te verzamelen. Het verzamelen van meldingen van bijwerkingen afkomstig van zorgverleners en patiënten, ook bekend als spontaneous reporting system of vrijwillig meldsysteem, is sinds de jaren 60 de meeste gebruikte methode. Het 15. doel van een vrijwillig meldsysteem is het tijdig vinden van nieuwe, zeldzame en ernstige 16. bijwerkingen. Een vrijwillig meldsysteem is een efficiënte en relatief goedkope manier om de 17. veiligheid van geneesmiddelen te bewaken. Met een vrijwillig meldsysteem is het mogelijk 18. om alle geneesmiddelen tijdens hun hele levenscyclus te bewaken. Een vrijwillig meldsysteem heeft ook een aantal beperkingen; de vaakst genoemde zijn onderrapportage en het feit dat er geen frequenties van bijwerkingen bepaald kunnen worden. Hoewel er soms 21. gezegd wordt dat een vrijwillig meldsysteem niet de ideale methode is om de veiligheid van 22. geneesmiddelen te bewaken, heeft het systeem in de afgelopen jaren bewezen dat het snel 23. signalen van tot dan toe onbekende bijwerkingen kan vinden Naast een vrijwillig meldsysteem is er behoefte aan meer structurele data verzameling over 26. de veiligheid van geneesmiddelen. Een manier om actief informatie over bijwerkingen te verzamelen is intensive monitoring. Intensive monitoring is een observationele cohort studie, die zich onderscheidt van een vrijwillig meldsysteem doordat alleen bepaalde geneesmiddelen tijdens een bepaalde tijdsperiode bewaakt worden, waarbij in die periode actief naar het optreden van bijwerkingen wordt gevraagd. Met intensive monitoring is het mogelijk om 31. het risico op een bepaalde bijwerking te kwantificeren. Maar ook hier zijn er beperkingen; 32. het aantal bijwerkingen dat niet gemeld wordt is onbekend en de frequentiebepalingen 33. is de gerapporteerde frequentie en niet de echte frequentie. Dit geldt overigens voor alle 34. methodes die gebruik maken van informatie uit databases Het Nederlands Bijwerkingen Centrum Lareb heeft een web-based intensive monitoring systeem ontwikkeld: Lareb Intensive Monitoring (LIM). Patiënten die een met de LIM-methode 37. gevolgd geneesmiddel gaan gebruiken, worden in de openbare apotheek op basis van het eerste uitgifte signaal geïdentificeerd. De patiënt ontvangt in de apotheek informatie over 189

190 de LIM studie en wordt gevraagd of hij of zij wil meedoen. Na online registratie ontvangt de 2. patiënt op verschillende tijdstippen een vragenlijst per . In de vragenlijsten worden 3. vragen gesteld over persoonsgegevens, geneesmiddelgebruik en eventuele bijwerkingen. 4. De informatie wordt bij Lareb gecodeerd en geanalyseerd met het doel om nieuwe bijwerkingen te vinden of nieuwe informatie over al bekende bijwerkingen te identificeren. In is het LIM systeem van start gegaan Het doel van dit promotieonderzoek is het beschrijven van een web-based intensive monitoring 9. systeem waarin patiënten als bron van informatie gebruikt worden en hoe deze methode toegepast kan worden om de veiligheid van geneesmiddelen te bewaken In hoofdstuk 3 wordt de patiënt als bron van informatie onderzocht. In de eerste studie 13. worden de motieven voor deelname aan LIM onderzocht. In de literatuur is weinig informatie 14. beschikbaar over de motieven van patiënten om mee te doen aan geneesmiddelenbewakingssysteem zoals LIM. Meer kennis hierover kan leiden tot beter begrip van de door de patiënt gerapporteerde informatie. Meer kennis over de motieven van patiënten om deel te 17. nemen aan LIM kan ook gebruikt worden om patiënt gebaseerde farmacovigilantie methoden te verbeteren en verder te ontwikkelen. In 21 semi-gestructureerde diepte interviews met patiënten die deelnamen aan LIM werden de motieven voor deelname geïnventariseerd. 20. Op basis van deze informatie is een vragenlijst ontwikkeld die naar meer dan 2000 LIM deelnemers gestuurd werd. De voornaamste redenen voor deelname aan LIM zijn altruïstisch, namelijk Andere patiënten kunnen hierdoor beter behandeld worden (89%) en Ik wil medewerkers in de gezondheidszorg helpen (84%) Niet alle patiënten die in aanmerking komen voor LIM deelname doen uiteindelijk mee. Door 26. redenen voor non-respons te onderzoeken, kunnen maatregelen ondernomen worden om 27. de deelname te verhogen. In de tweede studie worden redenen voor non-respons onderzocht 28. door middel van een schriftelijke vragenlijst. De hoofdzakelijke reden dat patiënten niet 29. meedoen aan LIM is dat ze geen informatie ontvangen in de apotheek (50.9%), 21.2% kan 30. zich niet herinneren of ze informatie hadden ontvangen. Van degenen die wel informatie 31. hadden gekregen in de apotheek is geen toegang tot internet de reden voor non-respons in 32. ongeveer een kwart van de gevallen. Van degenen die wel toegang tot internet heeft, probeerde een kwart zich aan te melden voor LIM zonder succes. Er wordt geen duidelijke reden voor non-respons geïdentificeerd, behalve dat de meeste patiënten vinden dat deelname 35. weinig directe voordelen oplevert Voor een nieuw geneesmiddelenbewakingssysteem zoals LIM, is het belangrijk om te weten of de patiënten die kiezen om deel te nemen vergelijkbaar zijn met de algemene populatie die het geneesmiddel gebruikt, anders is het moeilijk om de resultaten van LIM te extrapo- 190

191 Samenvatting leren naar andere populaties. In hoofdstuk 4 wordt de LIM diabetespopulatie vergeleken 2. met een referentiepopulatie. Hiervoor is gebruikt gemaakt van de Groningen Initiative to 3. ANalyse Type 2 diabetes Treatment (GIANTT) database. GIANTT verzamelt informatie over 4. patiënten met type 2 diabetes mellitus in het noorden van Nederland. De LIM diabetespopulatie werd vergeleken met de referentiepopulatie op kenmerken die een rol kunnen spelen in het ontstaan van een bijwerking zoals leeftijd, geslacht, Body Mass Index (BMI) en 7. polyfarmacie. Ook het type gebruikte diabetesmiddel en de diabetes behandelduur werden 8. tussen de twee groepen vergeleken. De vergelijking tussen de LIM diabetes populatie en de 9. referentiepopulatie laat zien dat de LIM populatie over het algemeen jonger en gezonder 10. is dan de referentiepopulatie. De LIM populatie heeft een grotere percentage nieuwe antidiabetica gebruikers, een kortere behandelingsduur en gebruikt minder comedicatie dan de referentiepopulatie. Deze verschillen zouden ertoe kunnen leiden dat de frequentie van 13. bijwerkingen onderschat wordt. Het is niet duidelijk of de verschillen ook een rol spelen in 14. het type bijwerkingen die optreden of in het beloop van de bijwerking. Er moet rekening met 15. deze verschillen gehouden worden als resultaten van LIM geïnterpreteerd worden In hoofdstuk 5 worden de resultaten van de eerste LIM studies gepresenteerd. Twee studies 18. betreffen het geneesmiddel pregabaline en één studie betreft het geneesmiddel duloxetine. 19. Pregabaline wordt gebruikt voor de behandeling van neuropathische pijn, epilepsie en gegeneraliseerde angststoornis. In de studie waarin de bijwerkingen van pregabaline onderzocht werden, deden 1373 patiënten mee waarvan 796 (58.0%) vrouw was. De gemiddelde leeftijd 22. was 54.5 (SD 13) jaar, variërend van jaar. Neuropathische pijn was de indicatie in 85.9% 23. van de gevallen. Van alle geïncludeerde patiënten vulde 1051 (76.5%) tenminste één vragenlijst in. De vijf meest gemelde bijwerkingen waren duizeligheid, slaperigheid, een dronken gevoel, vermoeidheid en gewichtstoename. Vier bij het gebruik van pregabaline genoemde 26. bijwerkingen, namelijk hoofdpijn, buikpijn, een wisselwerking met bloedsuikerverlagende 27. middelen en zelfmoordgedachten, werden als signalen geïdentificeerd. Deze studie laat zien 28. dat pregabaline een relatief veilig geneesmiddel is In de pregabaline studie hebben de patiënten 2 weken, 6 weken, 3 maanden en 6 maanden na start van de behandeling vragenlijsten ingevuld. In de tweede pregabaline studie wordt gekeken naar het beloop van de bijwerkingen. Op geaggregeerd niveau blijft het 33. bijwerkingenprofiel van pregabaline relatief stabiel bij langer gebruik. De vijf meest gemelde 34. bijwerkingen treden vooral in de eerste twee weken op. Dit komt goed overeen met het 35. feit dat dit waarschijnlijk type A bijwerkingen zijn, dat wil zeggen: een direct farmacologisch 36. effect van het geneesmiddel. 66.1% van de patiënten die pregabaline staakte vanwege duizeligheid, gaf aan dat ze herstellend of hersteld waren. Van de patiënten met duizeligheid die 37. doorgingen met het pregabalinegebruik, gaf 46.5% aan dat ze herstellend of hersteld waren van de duizeligheid. Dit voorbeeld laat zien dat een groot deel van de patiënten herstellen 191

192 ondanks het voortgezet gebruik van pregabaline. Duizeligheid is in sommige gevallen van 2. voorbijgaande aard en het staken van het geneesmiddel is niet altijd noodzakelijk voor het 3. verdwijnen van de bijwerking Duloxetine is een geneesmiddel dat toegepast wordt als behandeling van depressie, neuropathische pijn ten gevolge van diabetes en gegeneraliseerde angststoornis. De veiligheid van duloxetine werd onderzocht in een cohort van 398 patiënten, waarvan 69.1% vrouw was. 8. De gemiddelde leeftijd was 47.0 (SD 12.3) jaar, variërend van 14 tot 82 jaar. 66.7% van de 9. patiënten gebruikte duloxetine tegen depressie, 16.1% tegen neuropathische pijn en 4.3% 10. tegen fibromyalgie. Van de 398 patiënten vulden 303 (76.1%) tenminste een vragenlijst in. 11. Van deze meldden 239 (78.9%) tenminste een bijwerking. De meest frequent gerapporteerde 12. bijwerkingen komen overeen met de bijwerkingen die in de bijsluiter van duloxetine beschreven staan. Vier patiënten (1.3%) meldden een ernstige bijwerking, waarvan één fataal was vanwege elektrolytstoornissen. Drie signalen werden geïdentificeerd die verder geanalyseerd dienen te worden, te weten amenorroe, tintelingen die op elektrische stoten lijken en plasproblemen. Deze studie laat zien dat het bijwerkingenprofiel van duloxetine dat 17. verkregen is door LIM vergelijkbaar is met het bijwerkingenprofiel zoals dat is beschreven 18. in de bijsluiter In de tot nu toe beschreven studies heeft de inclusie van patiënten voor LIM in de openbare apotheek plaatsgevonden. Web-based intensive monitoring is ontwikkeld met deze gedachte. Maar ook andere plekken zijn geschikt als inclusiepunt. Hoofdstuk 6 beschrijft 23. een studie waarin de veiligheid van het influenza A (H1N1) vaccin onderzocht wordt. In deze 24. studie werd de huisartsenpraktijk gebruikt als inclusiepunt. Volwassenen boven 60 jaar en 25. personen met medische indicatie die in aanmerking kwamen voor vaccinatie met het pandemische influenzavaccin in de huisartsenpraktijk, konden geïncludeerd worden in de studie Na toediening van de eerste vaccinatie ontvingen de patiënten een briefje met informatie 28. over de studie en vervolgens kon de patiënt zich via internet aanmelden. Binnen een week, 29. na drie weken en drie maanden na de eerste vaccinatie werden vragenlijsten gestuurd met 30. vragen omtrent de patiënt en diens gezondheidstoestand, vaccinaties en eventuele bijwerkingen. In totaal hebben 3569 patiënten meegedaan met de studie, van deze rapporteerde (37%) een bijwerking. Onverwachte, ernstige bijwerkingen zijn niet gerapporteerd. De 33. meerderheid van de gerapporteerde bijwerkingen zijn bekende, niet-ernstige bijwerkingen. 34. Prikplaatsreacties hebben over het algemeen een korte latentietijd, een korte duur en vereisten geen behandeling. De kans op het krijgen van een bijwerking wordt beïnvloed door geslacht, leeftijd en type comorbiditeit. Deze studie geeft aan dat er geen aanleiding is tot 37. zorg over de veiligheid van het pandemisch influenza vaccin dat in Nederland is gebruikt. 192

193 Samenvatting De boven beschreven studie laat zien dat het mogelijk is om web-based intensive monitoring 2. ook te gebruiken in andere settings. In hoofdstuk 6 worden toekomstige toepassingen van 3. web-based intensive monitoring verder besproken. De Europese landen hebben zich ingespannen om de veiligheid van geneesmiddelen te waarborgen, zonder dat dit de registratie van nieuwe geneesmiddelen vertraagt. Een voorbeeld hiervan is conditional approval ofwel 6. voorwaardelijke toelating van een geneesmiddel. Om de bijwerkingen van een geneesmiddel te kunnen volgen na voorwaardelijke toelating, zou web-based intensive monitoring gebruikt kunnen worden. Dit zou leiden tot gegevensverzameling van de veiligheid van 9. het geneesmiddel uit de dagelijkse praktijk, zonder de beperkingen van klinische studies 10. en vrijwillige meldsystemen. Als er bijzondere risico s zijn, kunnen de vragenlijsten hierop 11. worden aangepast om de risico s in kaart te brengen Web-based intensive monitoring kan ook gebruikt worden in het opzetten van registers voor 14. bepaalde medicijnen. Voor sommige geneesmiddelen zijn vrijwillige meldsystemen niet 15. voldoende om de veiligheid van het middel te kunnen garanderen. In deze situaties is een 16. register noodzakelijk, zodat elke gebruiker van het geneesmiddel gevolgd wordt. Deelname 17. aan het register is dan een voorwaarde voor de patiënt om het geneesmiddel te verkrijgen Als methode is web-based intensive monitoring niet beperkt tot een geneesmiddel als 20. uitgangspunt. Ook een bepaalde populatie, zoals bijvoorbeeld kinderen, ouderen of zwangere vrouwen, kan het uitgangspunt voor de cohort vormen. In deze populaties worden geneesmiddelen vaak off-label voorgeschreven, en de veiligheid van het geneesmiddel kan 23. in deze populaties anders zijn dan als het geneesmiddel gebruikt wordt volgens indicatie. 24. Omdat informatie over geneesmiddelengebruik en bijwerkingen in deze groepen schaars 25. is, kan web-based intensive monitoring een manier zijn om meer informatie te verkrijgen. 26. Voor dit type onderzoek is het doel om zowel het geneesmiddelgebruik (type geneesmiddel, 27. dosering, indicatie) als de bijwerkingen in een bepaalde groep in kaart te brengen. In het 28. geval van zwangere vrouwen kunnen ook aangeboren afwijkingen in relatie tot geneesmiddelgebruik bestudeerd worden Momenteel is er veel aandacht voor het ontwikkelen van farmacovigilantie methoden 32. die gebruik maken van al bestaande informatiebronnen, zoals bijvoorbeeld informatie uit 33. elektronische patiëntendossiers, administratieve- en verzekeringsgegevens en registers. De 34. grootste beperking van deze methoden is dat ze gebruik maken van data die niet verzameld 35. is met het doel om kennis over bijwerkingen te vergroten, waardoor de informatie die je 36. omtrent bijwerkingen zou willen hebben, niet altijd beschikbaar is en de klinische informatie 37. van de individuele casus waarop de conclusies gebaseerd zijn soms gebrekkig is. 193

194 Met web-based intensive monitoring wordt getracht om de voordelen van zowel de farmacoepidemiologische als de meer klinische farmacovigilantie methoden te combineren Het systeem moet dicht bij de praktijk blijven, maar moet ook informatie over bijwerkingen 4. kunnen verzamelen die de huidige methoden niet kunnen. Het doel van dit proefschrift is om 5. te laten zien welke informatie er verzameld kan worden met web-based intensive monitoring 6. en het systeem verder te beschrijven. In hoofdstuk 7 worden beperkingen van het systeem 7. en suggesties voor verder onderzoek gedaan Dit proefschrift laat zien dat web-based intensive monitoring een waardevolle toevoeging 10. is op de huidige methoden die binnen de geneesmiddelenbewaking gebruikt worden. De 11. methode dient verder ontwikkeld te worden en ook in andere settings toepast te worden, 12. maar het heeft de potentie om een belangrijke bijdrage te leveren aan het verzamelen van 13. informatie over bijwerkingen

195 Sammanfattning Sammanfattning Läkemedel används för att behandla, läka, förebygga och diagnostisera sjukdom. Ibland kan 4. en patient förutom den önskade effekten även ervara biverkningar av läkemedlet. Vetenskapen som arbetar med biverkningar av läkemedel heter farmakovigilans. Farmakovigilans är definierat av Världshälsoorganisationen (WHO) som vetenskapen och de aktiviteter som 7. relaterar till att upptäcka, utvärdera, förstå och förhindra biverkningar av läkemedel samt alla 8. andra läkemedelsrelaterade problem I kapitel 2 ges en inledning till farmakovigilans och de metoder som används för att samla 11. information om läkemedelsbiverkningar. Att samla biverkningsrapporter från sjukvårdspersonal och patienter, ett så kallat spontaneous reporting system eller spontanrapporterings system har varit det huvudsakliga sättet att få information om läkemedelsbiverkningar sedan talet. Det huvudsakliga målet med ett spontanrapporteringssytem är signalspaning, 15. att upptäcka nya, sällsynta och allvarliga biverkningar. Ett spontanrapporteringssytem är ett 16. effektivt och billigt sätt att bevaka läkemedelssäkerheten under den tiden som läkemedelt 17. finns tillgängligt på marknaden. Det har dock vissa begränsningar, de som oftast nämns är 18. underrapportering och oförmågan att beräkna hur ofta en biverkning uppträder. Även om 19. spontanrapporteringssystemet har fått mycket kritik har det visat sitt sitt värde genom åren 20. genom att kunna identificera nya biverkningar Förutom spontanrapportering finns det ett behov av mer strukturerad datainsamling av 23. läkemedelsbiverkningar. Ett sätt att aktivt samla in information om biverkningar är genom 24. intensive monitoring. Grunden for denna typ av övervakning är en non-interventional 25. cohort studie vilket skiljer sig från spontanrapportering eftersom den endast följer ett antal 26. utvalda läkemedel under en begränsad tidsperiod. Via intensive monitoring är det möjligt 27. att beräkna hur ofta en biverkning förekommer. Denna metod har emellertid också erkända 28. begränsningar, andelen biverkningar som inte rapporteras är okänd och därför kan endast 29. rapporterade frekvenser erhållas, detta gäller för alla metoder som använder sig av data från 30. patientjournaler, register och databaser The Netherlands Pharmacovigilance Centre Lareb som är ansvariga för spontanrapporteringen in Nederländerna har utvecklat ett web-based intensive monitoring system som heter Lareb Intensive Monitoring (LIM). Patienter som använder de läkemedel som följs med LIM 35. identifieras i apoteket när de hämtar ut det nya läkemedlet för första gången. Patienterna 36. informeras om intensive monitoring studien och frågas om de vill delta. Efter att de anmält 37. sig online, skickas enkäter via e-post vid ett flertal tillfäller så att longitudinell information kan samlas. I enkäterna ställs frågor om patienten, hans/hennes läkemedelsanvändning och eventuella biverkningar. Informationen analyseras sedan med syftet att identifiera nya 195

196 biverkningar eller att få mer kunskap om redan bestående biverkningar. I augusti 2006 togs 2. LIM systemet i bruk Syftet med denna avhandling är att beskriva ett web-based intensive monitoring system som 5. använder information rapporterad av patienter och hur det kan användas för att få ökad information om läkemedelsbiverkningar Kapitel 3 ägnas åt patienten som informationskälla. Den första studien handlar om patienters 9. motiv för att delta i intensive monitoring. Vad som motiverar patienter att delta i ett farmakovigilanssytem såsom LIM är hittills okänt. Ökad kunskap kan leda till att det blir lättare att förstå och tolka patientrapporterad information. Ökad insikt i patienters motiv för att delta 12. kan också användas för att utveckla och förbättra farmakovigilansmetoder som använder 13. patientrapporterad information. Patienters motiv för att delta i LIM inventariserades först i semi-strukturerade djupintervjuer. Informationen från dessa intervjuer låg till grund för 15. en enkät som skickades till över 2000 LIM deltagare. De viktigaste motiven för att delta i LIM 16. var främst altruistiska: Andra patienter kan behandlas bättre (89%) och Jag vill hjälpa sjukvårdspersonalen (84%). Inte alla patienter som skulle kunna medverka i LIM väljer att delta Genom att identifiera orsaker för non-respons, bortfall, kan man försöka åtgärda orsakerna 19. som gör att patienter inte deltar. I den andra studien undersöktes orsakerna för non-respons 20. met hjälp av en skriftlig enkät. Det främsta skälet till non-respons var att patienterna inte blev 21. frågade i apoteket om de ville delta, 50.9% av patienterna fick inte någon information om 22. LIM i apoteket och 21.2% kom inte ihåg om de fått någon information. För de patienter som 23. fick information om LIM var ingen tillgång till internet orsaken för non-respons i ungefär en 24. fjärdedel av fallen. För dem som har tillgång till internet uppgav en fjärdedel att de försökte 25. registrera sig för studien men misslyckades. Av alla möjliga orsaker för non-respons kunde 26. inte en enda orsak identificeras förutom att de flesta patienter tyckte att medverkan inte ger 27. någon direkt individuell vinst För att en ny farmakovigilansmetod som LIM ska vara användbar är det viktigt att veta om 30. patienterna som väljer att delta i LIM är jämförbara med de patienter som använder läkemedlet, annars kan det vara svårt att generalisera resultaten. I kapitel 4 jämförs de patienter som deltog i en LIM studie över diabetesläkemedel met en referensgrupp bestående av patienter 33. från Groningen Initiative to ANalyse Type 2 diabetes Treatment (GIANTT) databasen. Denna 34. databas samlar information över patienter med typ 2 diabetes i norra delen av Nederländerna LIM diabetespopulationen jämfördes med referenspopulationen på variabler som kan påverka en patientens mottaglighet att utveckla en biverkning såsom ålder, kön, Body Mass 37. Index (BMI) och polyfarmaci. Kliniska parametrar relaterade till diabetesstatusen såsom 196

197 Sammanfattning vilken typ diabetesmedicin de använder och hur länge de behandlats med diabetesmedicin 2. jämfördes också mellan de två grupperna En jämförelse mellan LIM diabetespopulationen med referenspopulationen visade att det 5. finns skillnader mellan grupperna. LIM patienterna är i allmänhet yngre och friskare vilket 6. betyder att de oftare är nya diabetesmedicinsanvändare, har behandlats en kortare tid med 7. medicinen och använder mindre andra mediciner än referenspopulationen. Dessa skillnader 8. skulle kunna leda till en underskattning av biverkningar i LIM men det är oklart om detta 9. också skulle kunna påverka typen eller tidsförloppet av de biverkningar som rapporteras. 10. Skillnaderna som identifierats i denna studie måste beaktas vid tolkningen av resultaten från 11. LIM studier I kapitel 5 presenteras de första resultaten från web-based intensive monitoring. Två studier undersökte läkemedlet pregabalin, en medicin som används för att behandla perifer och central neuropatisk smärta, epilepsie och generaliserat ångestsyndrom och en studie 16. undersökte läkemedlet duloxetin som används för att behandla depression, smärtsam diabetesneuropati och generaliserat ångestsyndrom Pregabalinstudien bestod av 1373 personen som följdes under sex månader med web-based 20. intensive monitoring. 796 (58.0%) var kvinnor, den genomsnittliga åldern var 54.5 (SD 13) 21. år, varierande från år. Neuropatisk smärta var indikationen i 85.9% av fallen. Av de 22. inkluderade patienterna fyllde 1051 (76.5%) i åtminste en enkät med information om läkemedelsanvändning och eventuella biverkningar. De fem biverkningar som rapporterades oftast var yrsel, sömnighet, en berusad (full) känsla, trötthet och viktökning. Fyra biverkningar, huvudvärk, ont i magen, en läkemedelsinteraktion mellan pregabalin och blodglukossänkande läkemedel och självmordstankar identificerades som signaler, dvs nya biverkningar I pregabalinstudien fyllde patienterna i enkäter 2 veckor, 6 veckor, 3 månader och 6 månader 29. efter att de börjat att använda läkemedlet. In den andra pregabalinstudien undersöktes 30. biverkningarnas tidsförlopp. På en aggregerad nivå är biverkningaprofilen av pregabalin 31. stabil över de olika mätmomenten. De fem mest rapporterade biverningarna analyserades 32. i mer detalj. Beräkningar visar att dessa biverkningar främst uppträder i de första två behandlingsveckorna. Detta stämmer överens med att dessa biverkningar är så kallade typ A biverkningar, en direkt farmakologisk effekt av läkemedlet. 66.1% av patienterna som 35. slutade att använda pregabalin för att de fick yrsel, rapporterade att de återhämtade eller 36. hade återhämtat sig från biverkningen. Å andra sidan rapporterade 46.5% av patienterna 37. som forsatte att använda pregabalin trots att de hade yrsel att de återhämtade eller hade återhämtat sig från yrseln. Detta exemplet illustrerar att även om pregabalinbehandelingen 197

198 fortsätter kan biverkningen försvinna. Det är inte alltid nödvändigt att sluta med läkemedlet 2. för att återhämta sig från biverkningen Säkerheten av duloxetin undersöktes i en grupp bestående av 398 patienter. Av dessa var % kvinnor och den genomsnittliga ålderna var 47.0 (SD 12.3) år, varierande från år. De flesta (66.7%) använde läkemedlet för att behandla depression, följt av smärtsam 7. diabetesnueropatie (16.1%) och fibromyalgi (4.3%). Av de 398 patienterna som registrerade 8. sig för studien fyllde 303 patienter (76.1%) i åtminstone en enkät. Av dessa patienter rapporterade 239 (78.9%) en biverkning. De mest rapporterade biverkningarna var jämförbara med biverkningarna som beskrivs i bipackssedeln av duloxetin. Fyra patienter (1.3%) hade en 11. allvarlig biverkning, varav en patient dog till följd av elektrolytrubbningar. Tre nya signaler 12. identificerades nämligen amenorré, känselrubbningar som kändes som elchocker och urineringsproblem I alla studier som beskrivits hittills har patienterna identificerats i apoteket. Grundtanken med 16. web-based intensive monitoring var att patienterna skulle indentificeras i apoteken men patienter kan också identificeras på andra plaster. I kapitel 6 beskrivs en studie där säkerheten av det pandemiska Influenza A (H1N1) vaccinet undersöktes. I denna studien identificerades 19. patienterna hos husläkaren. I Nederländerana rekommenderades vuxna äldre än 60 år och 20. patienter som hade en sjukdom som ansågs som riskförhöjande för allvarliga komplikationer 21. av svininfluensan att vaccineras hos husläkaren. Efter den första vaccinationen fick patienterna en informationsborschyr med information om web-based intensive monitoring studien Patienterna kunde anmäla sig via en speciell sida på internet. Inom en vecka, efter tre veckor 24. och efter tre månader efter den första vaccinationen fick patienterna en enkät via 25. med personlinga och demografiska frågor samt frågor om vaccinationen och eventuella 26. biverkningar. Totalt medverkade 3569 patienter i studien, av dessa rapporterade 1311 (37%) 27. en biverkning av vaccinet. Det rapporterades inga oväntade, allvarliga biverkningar och inga 28. nya signaler identificerades. De rapporterade biverkningarna var övervägande milda och 29. kända biverkningar. Reaktioner på injektionsplatsen och biverkningar som var beskrivna i 30. bipackssedeln av vaccinet träder snabbt upp och försvinner också i de flesta fallen relativt 31. snabbt. I de flesta fallen krävs ingen behandling för att återhämta sig från dessa biverkningar. 32. Chansen att få en biverkning påverkades av patientens kön, ålder och sjukdomar Ovanstående studie visar att web-based intensive monitoring kan användas för att identificera patienter på andra platser än i apoteket. I kapitel 6.2 diskusseras olika framtida användingsområden av web-based intensive monitoring. 37. I Europa har läkemedelssäkerheten fått mycket uppmärksamhet de senaste åren. Man har försökt att göra läkemedlen säkrare utan att fördröja registrationen av läkemedlet. Ett 198

199 Sammanfattning exempel på detta är conditional approval eller villkorligt godkännande. För att kunna följa läkemedlet och dess biverkningar efter ett villkorligt godkännande skulle man kunna använda web-based intensive monitoring. På detta sätt skulle man kunna få information om läkemedlets användning och dess biverkningar utan de begränsningar som kliniska prövningar och spontanrapportering har. Om läkemedlet har speciella risker som måste undersökas kan 6. enkäterna anpassas så att dessa risker kan studeras i detalj Web-based intensive monitoring kan också användas för att skapa ett läkemedelsregister. 9. För vissa läkemedel är det inte tillräckligt att bevaka säkerheten på frivillig basis. I dessa fallen är det nödvändigt att ha ett register så att alla personer som använder läkemedlet följs Medverkan i registret blir ett måste för att kunna använda läkemedlet Web-based intensive monitoring behöver inte ha ett läkemedel som utgångspunkt, det 14. kan också ha en viss population såsom barn, äldre eller gravida som utgångspunkt. I dessa 15. befolkningsgrupper används läkemedel ofta off-label och biverkningarna från off-label 16. användning kan skilja sig från biverkningarna som upptäder när läkemedlet används enligt 17. bipackssedeln. Eftersom kunskaperna om biverkningar i dessa grupper är begränsad skulle 18. web-based intensive monitoring kunna samla in nyttig information. För den här typen av studier skulle målet vara att undersöka vilka läkemedel (typ, dosering, indikation) som används i dessa grupper och vilka biverkningar som uppträder. När man följer gravida kvinnor kan man 21. också undersöka förekomsten av medfödda missbildningar Just nu utvecklas många metoder som baseras på att man använder redan bestående informationskällor såsom elektroniska patientjournaler, register och databaser med information om sjukdom och läkemedelsanvändning. Den största begränsningen med dessa metoder är 26. att de använder data som inte har samlats in med syftet att studera biverkningar. Därför saknas det ofta information som behövs när man vill generera ny information om ett läkemedels säkerhet. När web-based intensive monitoring utvecklades ville man kombinera styrkan från 29. det farmakoepidemiologiska tillvägagångsättet med styrkan från det mer kliniska farmakovigilans tillvägagångsättet. Det var viktig att metoden stod nära praktiken och att den skulle kunna bidra till ökad kunskap om läkemedelsbiverkningar Syftet med den här avhandlingen är att visa vilken sorts information man kan samla in med 34. web-based intensive monitoring och att beskriva metoden och dess möjligheter. I kapitel diskusseras metodens begränsningar och ges förslag till vidare forskning Avslutningsvis kan sägas att denna avhandlingen visar att web-based intensive monitoring är ett värdefullt verktyg i farmakogvigilansarsenalen. Metoden måste utvecklas vidare och 199

200 implementeras i andra situationer men har potentialen att bli en vikting metod i insamlandet 2. av biverkningsinformation

201 Dankwoord Publications About the author

202

203 Dankwoord Dankwoord Al sinds mijn studie farmacie heb ik de wens gehad om te promoveren. Destijds had ik 4. gehoopt dat ik deze mijlpaal zou bereiken voordat ik 30 werd. Ik ben nu ruim boven de 30, 5. maar eindelijk is het zo ver. Er zijn een aantal personen die mij op deze lange weg hebben 6. geholpen en die ik graag wil bedanken Allereerst mijn promotoren, professor A.C. van Grootheest en professor J.J. de Gier. 9. Beste Kees, dank voor alle kansen die je mij gegeven hebt. Het begon toen je mij, een jonge 10. apotheker die slechts twee maanden in Nederland woonde, durfde aan te nemen bij Lareb. 11. Onder jouw begeleiding heb ik mij in de jaren die wij samen hebben gewerkt mogen ontwikkelen zowel op professioneel als wetenschappelijk vlak. Ik ben bijzonder dankbaar voor de mogelijkheid om naast het werk ook promotieonderzoek te mogen doen, en daarin heb je 14. mij uitstekend begeleid. Ik had mij geen betere begeleider en mentor kunnen wensen. 15. Beste Han, jij bent de enige van mijn (co-)promotoren die apotheker is, en jouw perspectief 16. op mijn onderzoek was heel belangrijk. Dank hiervoor! 17. Daarnaast wil ik ook mijn co-promotor dr. E.P van Puijenbroek bedanken. Beste Eugene, dank 18. voor alle discussies, alle commentaren en alle praktische hulp tijdens de data-analyse. Je 19. bijdrage wordt gewaardeerd! 20. I would also like to thank the members of the reading committee Prof. Saad Shakir, Prof. Bert 21. Leufkens and Prof. Bob Willfert. Thank you for taking the time to read my thesis and for being 22. great role models in the field of pharmacovigilance Tijdens dit promotietraject heb ik de kans gehad om deel uit te maken van de vakgroep FT/ 25. FZ en PE2 in Groningen. Hoewel ik er niet altijd was, heb ik mij altijd op de afdeling thuis gevoeld. Via de universiteit heb ik ook de kans gekregen om een aantal stagiaires te begeleiden Behalve dat zij mij hebben geholpen met de dataverzameling en analyse heb ik door hen 28. ook veel geleerd. Beste Miguel, Susanne, Lisette en Harmen, dank voor jullie bijdrage aan dit 29. proefschrift. 30. Overige co-auteurs, Sabine Straus, Florence van Hunsel, Petra Denig en Eelko Hak. Dank voor 31. de prettige samenwerking die wij hebben gehad Voor mij is een prettige omgeving een vereiste om goed te kunnen functioneren en te 34. presteren. Dank aan alle (ex)collega s bij Lareb, in het bijzonder de mensen op mijn afdeling. 35. Dank voor jullie steun de afgelopen maanden toen ik bezig was met het afronden van mijn 36. promotie. Dankzij jullie ga ik elke dag met plezier naar mijn werk!

204 Florence, ik vind het bijzonder dat wij zowel het promotie traject als de epidemiologieopleiding aan de VU tegelijkertijd hebben doorgelopen. Zonder jou was het heel anders geworden! Dank aan alle apothekers en patiënten die Lareb Intensive Monitoring mogelijk maken Om te kunnen promoveren moet je zowel op het werk als thuis een goede basis hebben Caroline och Susanne, vi har känt varandra i nästan 30 år. Tack för alla roliga studier tillsammans. Hoppas att det blir fler i framtiden Gamla vänner, nieuwe vrienden, thank you for being in my life! Mina paranimfer, Helga Gardarsdottir och Josefina Eikenaar. 14. Helga, samen in Uppsala, samen in Nederland, wie had dat ooit kunnen bedenken toen wij 15. elkaar net leerden kennen (ik kan mij nog steeds ons eerste telefoongesprek herinneren toen 16. ik dacht die jij iemand anders was). Ik ben blij dat het gelukt is om door de jaren heen contact 17. te houden. 18. Josefina, få är det förunnat att träffa någon som kan bli en så nära vän senare i livet. Tack för 19. alla mysiga stickstunder och för att du alltid förstår mig när jag saknar det svenska eller inte 20. förstår hur det funkar i Holland. Jag är så glad att vi har träffats! Mamma och pappa, tack för att ni alltid har uppmuntrat mig att göra det jag vill utan att ni 23. alltid har förstått varför. 24. Syster Maria, bror Mikael, moster Yvonne och resten av Björssonligan, tack för att ni finns! 25. Genom er vet jag var jag hör hemma! 26. Ängla, mitt kära gudbarn, jag är så glad att du finns! 27. Mormor, du var alltid så interesserad av min forskning. Jag är ledsen att du inte kan dela 28. denna dagen med mig Mijn nieuwe familie in Nederland, Henk, Jeannet en Annelies, dank dat jullie zo goed voor 31. mij zorgen Lieve Harold, jouw bijdrage is moeilijk in woorden uit te drukken. Zonder jou was dit nooit 34. mogelijk geweest! Ik kijk uit naar ons leven samen na de promotie

205 Publications Publications Pulications presented in this thesis 4. Härmark L, van Grootheest K. Web-based intensive monitoring: from passive to active drug surveillance. Expert Opin Drug Saf 2012; 11: Härmark L, van Puijenbroek E, van Grootheest K. Longitudinal monitoring of the safety of drugs by using 6. a web-based system: the case of pregabalin. Pharmacoepidemiol Drug Saf 2011; 20: Härmark L, van Puijenbroek E, Straus S, van Grootheest K. Intensive monitoring of pregabalin: results 8. from an observational, web-based, prospective cohort study in the Netherlands using patients as a source of information. Drug Saf 2011; 34: Härmark L, van Hunsel F, Hak E, van Grootheest K. Monitoring the safety of influenza A (H1N1) vaccines 10. using web-based intensive monitoring. Vaccine 2011; 29: Härmark L, van Grootheest AC. Pharmacovigilance: methods, recent developments and future perspectives. Eur J Clin Pharmacol 2008; 64: Härmark L, van Puijenbroek E, van Grootheest K. Intensive Monitoring of Duloxetine, Results from a webbased intensive monitoring study. Submitted Härmark L, Huls H, de Gier H, van Grootheest K. Non-response in a pharmacy and patient based intensive 15. monitoring system, a quantitative study on non-response bias and reasons for non-response. Submitted. 16. Härmark L, Lie-Kwie M, Berm L, de Gier H, van Grootheest K. Patients motives for participating in active post-marketing surveillance. Submitted. 17. Härmark L, Alberts S, Denig P, van Puijenbroek E, van Grootheest K. Representativeness of diabetes 18. patients participating in a web-based adverse drug reaction monitoring system. Submitted Other publications 21. Harrison-Woolrych M, Härmark L, Tan M, Maggo S, van Grootheest K. Epistaxis and other haemorrhagic events associated with the smoking cessation medicine varenicline: a case series from two national 22. pharmacovigilance centres. Eur J Clin Pharmacol 2012 [Epub ahead of print] 23. van Hunsel F, Härmark L, Pal S, Olsson S, van Grootheest K. Experiences with adverse drug reaction 24. reporting by patients: an 11-country survey. Drug Saf 2012; 35: Härmark L. Diabetes door furosemide. Pharm Weekbl 2011; 26. de Heus R, Mol BW, Erwich JJ, van Geijn HP, Gyselaers WJ, Hanssens M, Härmark L, van Holsbeke CD, Duvekot JJ, Schobben FF, Wolf H, Visser GH. Adverse drug reactions to tocolytic treatment for preterm 27. labour: prospective cohort study. BMJ 2009; 338:b Oosterhuis I, Härmark L, Hendriks J, van Puijenbroek EP. Vaak duizelig van pregabaline. Pharm Weekbl ; 6: Härmark L, van Grootheest AC. Actieve bewaking van nieuwe diabetesmiddelen. Patient Care 2008; 35: Gerritsen RF, Borgsteede SD, Härmark L. Fluticason en haematomen. Pharm Weekbl 2008; 143: Härmark L, van Grootheest AC. Hartklepafwijkingen door pergolide: Groepseffect uit een onverwachte 33. hoek. Pharm Weekbl 2007; 142: Härmark L, van der Wiel H, de Groot MCH, van Grootheest AC. Lastige diagnose. Bijwerking protonpompremmers: interstitiële nefritis. Pharm Weekbl 2007; 142: Härmark L, van der Wiel HE, de Groot MC, van Grootheest AC. Proton pump inhibitor-induced acute 36. interstitial nephritis. Br J Clin Pharmacol 2007; 64: van Puijenbroek EP, Härmark L. Statines en het risico op ernstige spierklachten; eenmaal veilig, altijd veilig? Pharm Weekbl 2006; 141:

206 206 Härmark L. Geen Arthrotec (diclofenac/misoprostol) in de zwangerschap. Geneesmiddelenbulletin 2006; 40: Abstracts Humrich J, Bermel C, Bünemann M, Härmark L, Frost R, Quitterer U, Lohse MJ. Phosducin-like protein regulates G-protein betagamma folding by interaction with tailless complex polypeptide-1alpha: dephosphorylation or splicing of PhLP turns the switch toward regulation of Gbetagamma folding. J Biol Chem 2005; 280: Lindblom J, Kask A, Hägg E, Härmark L, Bergström L, Wikberg J. Chronic infusion of a melanocortin receptor agonist modulates dopamine receptor binding in the rat brain. Pharmacol Res 2002; 45: van Grootheest AC, Härmark L, van Puijenbroek EP. Pharmacovigilance of contraceptives: Why does it take so long to take action? Drug Saf 2011; 34:901. Härmark L, van Hunsel F, Hak E, van Grootheest AC. Monitoring the Safety of the Influenza A H1N1 Vaccine: An Observational Cohort Study. Drug Saf 2010; 33: van Puijenbroek EP, Härmark L, van Grootheest AC. Monitoring Batch Related Safety of Vaccines During the Flu-Pandemic in the Netherlands. Drug Saf 2010; 33:917. van Puijenbroek EP, Härmark L, van Grootheest AC. Report Processing and Signal Management at the Netherlands Pharmacovigilance Centre. Drug Saf 2009; 32:897. van Puijenbroek E, Härmark L, van Grootheest AC. Web-Based Intensive Monitoring, a New Method for Active Surveillance of Drugs. Drug Saf 2008; 31:885. van Grootheest AC, Härmark L, Oosterhuis I, van Puijenbroek EP. Lareb intensive monitoring, a web based system for monitoring ADRs in the postmarketing phase. Pharmacoepidem Drug Saf 2007; 16:S252-S253. Oosterhuis I, Härmark L, van Puijenbroek EP, van Grootheest AC. Lareb Intensive monitoring: an interim analysis. Drug Saf. 2007; 30:960. Härmark L van Grootheest AC. Web-Based Intensive Monitoring, a New Patient Based Tool for Early Signal Detection. Drug Saf 2006;

207 About the author About the author Linda Härmark was born on January 25, She grew up in the small village of Källby, 4. Sweden. In 1997 she completed her pre-university education at the De la Gardiegymnaiset, 5. Lidköping. In the same year she started her pharmacy studies at Uppsala University. During 6. her pharmacy studies she spent one year abroad as an Erasmus exchange student at the 7. Bayerische Julius Maximilians Universiteit, Würzburg, Germany, where she wrote her master 8. thesis in the field of G-protein coupled receptors. After her year in Germany she attended the 9. Uppsala Graduate School in Biomedical Research for a year before graduating as a pharmacist 10. in After a short period working in community pharmacy in Uppsala she relocated to the Netherlands. She joined the Netherlands Pharmacovigilance Centre Lareb in November 2004 and is currently holding the position as head of the Reporting Department For the research in this thesis her work at the Netherlands Pharmacovigilance Center Lareb 17. was combined with a position as a part-time external PhD-student at the University of Groningen. During this period she followed the Master of Epidemiology programme at the EMGO institute, Vrije Universiteit in Amsterdam and in 2011 she registered as an epidemiologist

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209 SHARE dissertations Research Institute for Health Research SHARE This thesis is published within the Research Institute SHARE of the Graduate School of Medical Sciences (embedded in the University Medical Center Groningen / University of Groningen). More recent theses can be found in the list below. Further information regarding the institute and its research can be obtained from our internetsite: ((co-)supervisors are between brackets) 2012 Vegter S. The value of personalized approaches to improve pharmacotherapy in renal disease (prof MJ Postma, prof GJ Navis) Curtze C. Neuromechanics of movement in lower limb amputees (prof K Postema, prof E Otten, dr AL Hof ) Alma MA. Participation of the visually impaired elderly: determinants and intervention (prof ThPBM Suurmeijer, prof JW Groothoff, dr SF van der Mei) Muijzer A. The assessment of efforts to return to work (prof JW Groothoff, prof JHB Geertzen, dr S Brouwer) Ravera S. Psychotropic medications and traffic safety. Contributions to risk assessment and risk communication (prof JJ de Gier, prof LTW de Jong-van den Berg) De Lucia Rolfe E. The epidemiology of abdominal adiposity: validation and application of ultrasonographyy to estimate visceral and subcutaneous abdominal fat and to identify their early life determinants (prof RP Stolk, prof KK Ong) Tu HAT. Health economics of new and under-used vaccines in developing countries: state-of-the-art analyses for hepatitis and rotavirus in Vietnam (prof MJ Postma, prof HJ Woerdenbag) Opsteegh L. Return to work after hand injury (prof CK van der Sluis, prof K Postema, prof JW Groothoff, dr AT Lettinga, dr HA Reinders-Messelink) Lu W. Effectiveness of long-term follow-up of breast cancer (prof GH de Bock, prof T Wiggers) 2011 Boersma-Jentink J. Risk assessment of antiepileptic drugs in pregnancy (prof LTW de Jong-van den Berg, prof H Dolk) Zijlstra W. Metal-on-metal total hip arthroplasty; clinical results, metal ions and bone implications (prof SK Bulstra, dr JJAM van Raay, dr I van den Akker-Scheek) 209

210 210 Zuidersma M. Exploring cardiotoxic effects of post-myocardial depression 1. (prof P de Jonge, prof J Ormel) 2. Fokkens AS.Structured diabetes care in general practice 3. (prof SA Reijneveld, dr PA Wiegersma) 4. Lohuizen MT van. Student learning behaviours and clerkship outcomes 5. (prof JBM Kuks, prof J Cohen-Schotanus, prof JCC Borleffs) Jansen H. Determinants of HbA1c in non-diabetic children and adults (prof RP Stolk) Reininga IHF. Computer-navigated minimally invasive total hip arthroplasty; effectiveness, clinical outcome and gait performance 10. (prof SK Bulstra, prof JW Groothoff, dr M Stevens, dr W Zijlstra) 11. Vehof J. Personalized pharmacotherapy of psychosis; clinical and pharmacogenetic approaches 12. (prof H Snieder, prof RP Stolk, dr H Burger, dr R Bruggeman) Dorrestijn O. Shoulder complaints; indicence, prevalence, interventions and outcome (prof RL Diercks, prof K van der Meer, dr M Stevens, dr JC Winters) Lonkhuijzen LRCM van. Delay in safe motherhood (prof PP van den Berg, prof J van Roosmalen, prof AJJA Scherpbier, dr GG Zeeman) Bartels A. Auridory hallucinations in childhood 19. (prof D Wiersma, prof J van Os, dr JA Jenner) 20. Qin L. Physical activity and obesity-related metabolic impairments: estimating interaction from an additive 21. model (prof RP Stolk, dr ir E Corpeleijn) Tomčiková Z. Parental divorce and adolescent excessive drinking: role of parent adolescent relationship and other social and psychosocial factors 24. (prof SA Reijneveld, dr JP van Dijk, dr A Madarasova-Geckova) Mookhoek EJ. Patterns of somatic disease in residential psychiatric patients; surveys of dyspepsia, diabetes and skin disease 27. (prof AJM Loonen, prof JRBJ Brouwers, prof JEJM Hovens) 28. Netten JJ van. Use of custom-made orthopaedic shoes 29. (prof K Postema, prof JHB Geertzen, dr MJA Jannink) Koopmans CM. Management of gestational hypertension and mild pre-eclampsia at term (prof PP van den Berg, prof JG Aarnoudse, prof BWJ Mol, dr MG van Pampus, dr H Groen) For 2010 and earlier SHARE-theses see our website