Chapter 1. Scope and objectives of the thesis



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Transcription:

Chapter 1 Scope and objectives of the thesis

Chapter 1 Observational studies: focus on leflunomide The view that randomized controlled trials are the gold standard for evaluation and that observational methods have little additional value is widely accepted. According to some experts, the results of observational studies should not be used for defining evidence-based medical care. The major criticism of observational studies is that unrecognized confounding factors may influence the results [1]. However, results from a study comparing the results of observational and randomized, controlled studies in 19 different fields of medicine, suggest that observational studies usually do provide valid information [2]. One of the major reasons to conduct observational studies is the potentially limited external validity of the results of the randomized controlled trial. To what extent are the results of the trial generalisable to a population not treated in the setting of a specific trial? Three potential reasons for limited external validity can be recognized. The first may be that the health care providers in the setting of clinical trials are unrepresentative, for example because they are innovators. Secondly, the patients included in the trials may have characteristics different from the patients treated outside the setting of the trial. Thirdly, the treatment in the trial may be atypical. For example, patients included in trials may receive different care due to intensified follow-up [1]. These aspects may introduce bias in the results of the trial, resulting in limited external validity. In the treatment of rheumatoid arthritis a number of therapeutical options are available. The potential algorithms to prescribe these medications change rapidly. New medications enter the market, medication is prescribed in combination therapy, in higher doses and earlier in the disease process. In combination with the development of practical tools for evaluating disease activity and response to treatment [3], these changing algorithms provide the rationale for studying treatment outcomes in observational studies in rheumatoid arthritis. In the last few years, on the basis of results from large randomized controlled trials, leflunomide, the tumor-necrosis alpha antagonists and anakinra (interleukin-1 receptor antagonist) were registered for the treatment of rheumatoid arthritis (RA) [4-9]. To estimate the additional value in daily practice, critical evaluation of treatment effects in observational studies in the setting of day-to-day care, complementary to the results of randomized controlled trials, may be considered as essential. Chapter 2 highlights aspects of the use of leflunomide for the treatment of RA in daily rheumatological practice. Chapter 2.1 describes a long-term follow-up study of patients with RA starting leflunomide therapy in the first four years after registration. The objective is to 10

Scope and objectives of the thesis study the effectiveness, incidence of adverse drug reactions and withdrawal from leflunomide in an outpatient population with RA in the setting of care-as-usual. Shortly after the registration of leflunomide for the treatment of RA a number of reports of severe hepatotoxicity were published. Although in these reports, besides leflunomide exposure, other potential factors for hepatotoxicity were present, hepatotoxicity became an important safety issue concerning leflunomide. In chapter 2.2 the incidence and severity of hepatotoxicity in terms of elevations of plasma liver enzyme activities in patients on leflunomide treatment is studied. Information on predictors for better survival of leflunomide use, at the start of leflunomide therapy may offer opportunities for treatment optimization. In chapter 2.3 possible predictors for better leflunomide survival are studied. From the long term follow-up data of patients treated with leflunomide for RA in two regions in the Netherlands (Twente and Friesland) a set of patient-, disease- and treatment characteristics were analysed to detect potential predictors. Therapeutic drug monitoring: focus on A77 1726, the active metabolite of leflunomide From randomized controlled trials with leflunomide it is known that a large proportion (up to 47%) of patients withdraw leflunomide therapy due to adverse effects and inefficacy within 12 months after start of therapy [5,6]. Studies in clinical practice, outside the setting of randomized controlled trials, suggest even higher withdrawal rates [10-12]. For this reason optimization of leflunomide therapy is warranted. Therapeutic drug monitoring based on steady state serum concentrations of the active metabolite of leflunomide, A77 1726, may allow individualised dose adjustment and consequently increase clinical effectiveness. In phase II pharmacokinetic population modelling studies, a relationship between steady state A77 1726 serum concentrations < 13 mg/l and a reduced probability of clinical success is described [13]. However, information on A77 1726 serum concentrations is not incorporated in current clinical decision making in the rheumatological practice. For this reason, in chapter 3 the potential role of therapeutic drug monitoring in leflunomide treatment optimization is studied. In chapter 3.1 we describe the technical and clinical validation of a high-performance liquid chromatography method with ultraviolet detection for the analyses of A77 1726. Using this validated method, in chapter 3.2, the relationship between RA disease activity and the 11

Chapter 1 steady state serum concentrations of A77 1726 in patients treated with leflunomide is studied. Switching therapies: focus on parenteral gold therapy The market of rheumatoid arthritis treatment changes as new therapies are registered, and existing treatment options are withdrawn from the market. For patients using these withdrawn therapies, alternatives have to be found. A recent example is the withdrawal of aurothioglucose from the Dutch market due to insufficient quality of the raw material. Aurothiomalate was registered shortly after withdrawal of aurothioglucose and presented as the alternative preparation. Although never formally studied, some publications suggest that switching from aurothioglucose to aurothiomalate may be associated with the introduction of novel clinical problems [14,15]. To study earlier suggestions of negative safety of the aqueous aurothiomalate preparation, we monitored patients switching from the oily aurothioglucose preparation Auromyose to the aqueous aurothiomalate preparation Tauredon in a national case series study in the Netherlands. Chapter 4 describes the results of the follow-up of a cohort of patients during the first year after switching from aurothioglucose to aurothiomalate. Drug safety: focus on drug-drug interactions with disease-modifying antirheumatic drugs When prescribing and administering drugs, drug related problems may occur. Drug related problems include medication errors (involving an error in the process of prescribing, dispensing or administering a drug, whether there are adverse consequences or not) and adverse drug reactions (any response to a drug which is noxious and unintended, and which occurs at doses normally used in man for prophylaxis, diagnosis or therapy of disease, or the modification of physiological function) [16]. The possibility of drugs to influence each others safety or efficacy is known as a drugdrug interaction (DDI). DDI may increase morbidity and mortality and may lead to hospital admission [17-19]. Due to ageing and the presence of comorbidity in the population with RA, patients are prone to polypharmacy and therefore are at risk for the adverse reactions due to DDI. 12

Scope and objectives of the thesis Many sources for information of DDI are available for health care providers, ranging from the summaries of product characteristics and product leaflets to text books and internet sites [20,21]. However, knowledge of a DDI between two drugs is no guarantee for timely recognition of the DDI or for taking the appropriate action to prevent the risk of an adverse outcome. Computerized drug interaction surveillance systems may be helpful in detecting and preventing DDI with clinical significance. However, many pharmacists and doctors experience these systems to yield a large number of alerts with questionable or unclear clinical significance (suboptimal specificity), fail to provide identifiable patient and medication risk factors, fail to detect all relevant DDI (suboptimal sensitivity) and to include a variable set of DDI [22-25]. These problems stress the importance of transparency and selectivity in choosing the DDI to be included in computerized drug interaction surveillance systems on the basis of a structured assessment procedure. Chapter 5 concerns the DDI aspect of drug safety. Chapter 5.1 describes the procedures for structured assessment of DDI and the translation of this assessment to the computerized drug interaction surveillance system by the Working Group on Pharmacotherapy and Drug Information in the Netherlands. Further, this chapter presents results of the revision of the complete computerized drug interaction surveillance system of the Royal Dutch Association for the Advancement of Pharmacy on the basis of these assessments. In chapter 5.2 an overview is given of potential DDI with disease-modifying antirheumatic drugs (DMARD), to assess the clinical relevance of potential DDI with DMARDs and to study the uniformity in assessment of clinical relevance between rheumatologists and hospital pharmacists. Objectives of the thesis The objective of this thesis is to study aspects of safety and effectiveness of pharmacotherapy in the treatment of rheumatoid arthritis, with focus on leflunomide and parenteral gold. Furthermore, in this thesis the assessment of the clinical relevance of drugdrug interactions with DMARDs is studied. 13

Chapter 1 References 1. Black N. Why we need observational studies to evaluate the effectiveness of health care. BMJ 1996;312:1215-8. 2. Benson K, Hartz AJ. A comparison of observational studies and randomized, controlled trials. N Engl J Med 2000;342:1878-86. 3. Van Gestel AM, Prevoo MLL, Van t Hof MA, et al. Development and validation of the European League against Rheumatism response criteria for rheumatoid arthritis. Arthritis Rheum 1996;39:34-40. 4. Smolen JS, Kalden JR, Scott DL, et al. Efficacy and safety of leflunomide compared with placebo and sulphasalazine in active rheumatoid arthritis: a double-blind, randomised, multicentre trial. Lancet 1999;353:259-66. 5. Strand V, Cohen S, Schiff M, et al. Treatment of active rheumatoid arthritis with leflunomide compared with placebo and methotrexate. Arch Int Med 1999;159:2542-50. 6. Emery P, Breedveld FC, Lemmel EM, et al. A comparison of the efficacy and safety of leflunomide and methotrexate for the treatment of rheumatoid arthritis. Rheumatol 2000;39:655-65. 7. Moreland LW, Schiff MH, Baumgartner SW, et al. Etanercept therapy in rheumatoid arthritis. A randomized, controlled trial. Ann Intern Med 1999;130:478-86. 8. Maini R, St Clair EW, Breedveld F, et al. Infliximab (chimeric anti-tumour necrosis factor alpha monoclonal antibody) versus placebo in rheumatoid arthritis patients receiving concomitant methotrexate: a randomised phase III trial. ATTRACT Study Group. Lancet 1999;354:1932-9. 9. Bresnihan B, Alvaro-Gracia JM, Cobby M, et al. Treatment of rheumatoid arthritis with recombinant human interleukin-1 receptor antagonist. Arthritis Rheum 1998;41:2196-204. 10. Geborek P, Crnkic M, Petersson IF, et al. Etanercept, infliximab, and leflunomide in established rheumatoid arthritis: clinical experience using a structured follow-up programme in southern Sweden. Ann Rheum Dis 2002;61:793-8. 11. Siva C, Eisen SA, Shepherd R, et al. Leflunomide use during the first 33 months after food and drug administration approval: experience with a national cohort of 3,325 patients. Arthritis Rheum 2003; 49:745-51. 12. Wolfe F, Michaud K, Stephenson B, et al. Toward a definition and method of assessment of treatment failure and treatment effectiveness: the case of leflunomide versus methotrexate. J Rheumatol 2003;30:1725-32. 13. Weber W, Harnisch L. The population approach: measuring and managing variability in response, concentration and dose. Proceedings of conference, COST B1 medecine: European cooperation in the field of scientific and technical research. In Aaros L, Balant LP, Danhof M, Gex-Fabry M, Gundert-Remy UA, Karlsson MO (Eds). European Commission, Geneva/Brussels, 1997, pp. 238-44. 14. Lawrence JS. Comparative toxicity of gold preparations in treatment of rheumatoid arthritis. Ann Rheum Dis 1976;35:171-3. 14

Scope and objectives of the thesis 15. Rothermich NO, Philips VK, Bergen W, et al. Chrysotherapy. A prospective study. Arthritis Rheum 1976;19:1321-7. 16. Van den Bemt PM, Egberts TC, de Jong-van den Berg LT, et al. Drug-related problems in hospitalised patients. Drug Saf 2000;22:321-33. 17. Doucet J, Chassagne P, Trivalle C, et al. Drug-drug interactions related to hospital admissions in older adults: a prospective study of 1000 patients. J Am Geriatr Soc 1996;44:944-8. 18. McDonnell PJ, Jacobs MR. Hospital admissions resulting from preventable adverse drug reactions. Ann Pharmacother 2002;36:1331-6. 19. Juurlink DN, Mamdani M, Kopp A, et al. Drug-drug interactions among elderly patients hospitalized for drug toxicity. JAMA 2003;289:1652-8. 20. Stockley IH. Drug interactions. A source book of adverse interactions, their mechanisms, clinical importance and management. Oxford: Pharmaceutical Press; 2002. 21. Klasko RK, editor. DRUGDEX system. 1st ed. Greenwood Village (CO): Thomson MICROMEDEX; 2003. 22. Glassman PA, Simon B, Belperio P, et al. Improving recognition of drug interactions: benefits and barriers to using automated drug alerts. Med Care 2002;40:1161-71. 23. Magnus D, Rodgers S, Avery AJ. GPs' views on computerized drug interaction alerts: questionnaire survey. J Clin Pharm Ther 2002;27:377-82. 24. Hazlet TK, Lee TA, Hansten PD, et al. Performance of community pharmacy drug interaction software. J Am Pharm Assoc 2001;41:200-4. 25. Chrischilles EA, Fulda TR, Byrns PJ, et al. The role of pharmacy computer systems in preventing medication errors. J Am Pharm Assoc 2002;42:439-48. 15