Phalangeal BMD Measurement as a Method for Risk Evaluation in Fracture Prevention

Transcription

1 PhD-thesis Teresa Friis-Holmberg 2013 Phalangeal BMD Measurement as a Method for Risk Evaluation in Fracture Prevention Data from the Danish Health Examination Survey [0]

2 Phalangeal BMD Measurement as a Method for Risk Evaluation in Fracture Prevention Data from the Danish Health Examination Survey PhD Thesis Author: Teresa Friis-Holmberg Copyright 2013 by Teresa Friis-Holmberg, National Institute of Public Health, University of Southern Denmark, Copenhagen Publisher: National Institute of Public Health Faculty of Health Sciences University of Southern Denmark Øster Farimagsgade 5A DK-1353 Copenhagen K Denmark ISBN: E-ISBN: [I]

3 Academic advisers and assessment committee: Academic advisors: Professor, PhD Mickael Bech COHERE, Department of Business and Economics University of Southern Denmark Odense, Denmark Professor, PhD Kim Brixen Institute of Clinical Research University of Southern Denmark Odense, Denmark From December 2009 Marts 2011: Adjunct Professor, PhD Tine Curtis National Institute of Public Health University of Southern Denmark Copenhagen, Denmark Assessment Committee: Dr, PhD Emma Clark Musculoskeletal Research Unit University of Bristol Bristol, United Kingdom Professor, PhD Lars Bjerrum Department of Public Health University of Copenhagen Copenhagen, Denmark Clinical associate Professor, PhD Linda Kærlev Research Unit of Clinical Epidemiology Institute of Clinical Research University of Southern Denmark Odense, Denmark Defence: The defence will take place September 3 rd 2013 at the National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark [II]

4 The Thesis is based on the following papers: Paper I Teresa Holmberg, Mickael Bech, Tine Curtis, Knud Juel, Morten Grønbæk, Kim Brixen. Association between passive smoking in adulthood and phalangeal bone mineral density; results from the KRAM study the Danish Health Examination Survey Osteoporosis International 2011;22(12): Paper II Teresa Friis-Holmberg, Kim Brixen, Katrine Hass Rubin, Morten Grønbæk, Mickael Bech. Phalangeal bone mineral density predicts incident fractures; a prospective cohort study on men and women. Results from the Danish Health Examination Survey (DANHES ). Archives of Osteoporosis 2012; 7: Paper III Teresa Friis-Holmberg, Katrine Hass Rubin, Kim Brixen, Janne Schurmann Tolstrup, Mickael Bech. Fracture risk prediction using phalangeal bone mineral density or FRAX? Which is the best method in a Danish cohort of men and women. Journal of Clinical Densitometry: Assessment of Skeletal Health. Epub ahead of print (DOI /j.jocd ) Paper IV Teresa Friis-Holmberg, Mickael Bech, Jeppe Gram, Anne Pernille Hermann, Katrine Hass Rubin, Kim Brixen. Point-of-care phalangeal bone mineral density measurement can reduce the need of dual-energy X-ray absorptiometry scanning in women at risk of osteoporotic fractures. Submitted. [III]

5 Abbreviations Technical terms and abbreviations BMC Bone mineral content (g) BMD Bone mineral density (g/cm 2 ) BMI DANHES DXA FRAX HR LEF RA SD ROSE T-score Body mass index The Danish Health Examination Survey Dual energy x-ray absorptiometry Fracture risk assessments tool (10 year probability of fracture) Hazard Ratio Low energy fracture Radiographic absorptiometry Standard deviation The Risk-stratified Osteoporosis Strategy Evaluation study The number of standard deviations above or below the mean for a healthy young adult of the same sex [IV]

6 [V]

7 Preface Preface The academic work presented in this PhD thesis was carried out between December 2009 and April 2013 at the research Program for Health Promotion and Prevention, National Institute of Public Health, University of Southern Denmark in close collaboration with Institute of Clinical Research, University of Southern Denmark. The thesis was supported by grants from the Region of Southern Denmark and University of Southern Denmark. Moreover, BMD scans of women in the ROSE-study were supported by InterReg. First I would like to express my sincere gratitude to my academic supervisors Mickael Bech and Kim Brixen. Thank you for your wise and constructive comments, for your encouragements and your confidence in me, and for sharing your huge scientific insight and experience with me. Working with you both has been a pleasure and a privilege, and you were definitely the perfect supervisor-team. Moreover, a special thank should also be giving to Tine Curtis, who started it all. You hired me to be a part of DANHES, and saw the potential in me for this PhD-project. I am looking forward to collaborating with you again. I would also like to thank all my co-authors for their valuable and wise contributions to the paper included in this thesis. Special thanks to Morten Grønbæk and Janne Schurmann Tolstrup for discussing epidemiological and statistical issues with me, to Knud Juel for passing on knowledge related to passive smoking, and to Katrine Hass Rubin for helping me with FRAX-data and always taking the time to discuss all kind of issues with me I sincerely hope that our teamwork will precede in the future. Also I would like to thank Anne Pernille Hermann, Jeppe Gram and the rest of the ROSE-group for inspiring meetings and discussions, and for initiating me in the exciting world of osteoporosis and fracture prevention. Further, I wish to thank the staff at the Osteoporosis Clinics, Hospital of Southwest Jutland and Odense University Hospital for managing the RA scans of the ROSE-women, especially to Marianne Bøtcher and Anette Riis Madsen for your help and excellent assistance. Also thank to Claire Gudex for brilliant language support and comments to the thesis. My gratitude also goes to every participant in DANHES and the ROSE-study, and to Ola Ekholm at the National Institute of Public Health for helping me with any matter related to the DANHES dataset as well as for obtaining register data. Further I would like to thank all my great colleagues at the National institute of Public Health. I could not have asked for better colleagues, it has been a privilege to be part of such an inspiring and motivating scientific and social environment. Finally, my most sincere gratitude goes to my family and friends for their newer ending support, especially to Tom for bearing with me, for encouraging me and always being there for me. I could never have done this without you. Teresa Friis-Holmberg Copenhagen, Marts 2013 [VI]

8 [VII]

9 Table of contents Table of contents 1. Introduction Osteoporotic fractures, a public health issue Risk factors for osteoporosis and osteoporotic fractures Methods for identifying high risk persons Fracture prevention Current guidelines and recommendations Challenges in fracture prevention Aim of the thesis Methods and data sources The Danish Health Examination Survey (DANHES) Phalangeal BMD Passive smoking in adulthood home Clinical risk fractures for low BMD and fractures Register data and ascertainment of osteoporotic fractures Calculation of 10 year probability of fracture by FRAX Danish Risk-stratified Osteoporosis Strategy Evaluation study (ROSE) Dual-energy X-ray absorptiometry Statistical methods Findings Association between phalangeal BMD and passive smoking in adulthood home Fracture risk prediction using phalangeal BMD Phalangeal BMD versus the WHO fracture risk assessment tool (FRAX) and age alone in predicting osteoporotic fractures Correlation between phalangeal BMD and central BMD and application of a triage approach in preselection for DXA Discussion Passive smoking as a risk factor Performance of phalangeal BMD measured by RA Methodological considerations Conclusion and perspectives Perspectives Summary Resumé References Papers I IV [viii]

10 [ix]

11 Introduction 1. Introduction 1.1 Osteoporotic fractures, a public health issue Osteoporosis is a skeletal disorder characterised by decreased bone strength that results in increased risk of fractures (1;2), and osteoporotic fractures are the most important clinical complication of osteoporosis. Osteoporosis is especially prevalent in postmenopausal women and, however, it has historically been considered as a women s disease, it is increasingly recognized as a prevalent condition among men as well (3;4). Thus, about 46% of women and 26% of men will experience at least one osteoporotic fracture after the age of 50 years (5). Approximately 11,000 hip fractures (6), 7,000 forearm fractures and 2,000 clinical vertebral fractures occur every year in Denmark (7). It is has been shown that around 85% of all hip fracture cases also have osteoporosis, which increases the risk of new fractures (8). Although the incidence of hip fracture is decreasing in Denmark (9), in 2012 Denmark had the highest incidence of hip fracture in an international comparison (574 per 100,000 person-years in women and 290 per 100,000 person-years in men) (10). In Western populations until around 1980 it was a general trend that the incidence rates increased and thereafter the incidence rates stabilised or decreased. A recent review, however, concluded that in Asia incidence rates continues to increase (11). Societal costs attributable to osteoporotic fractures are high; this is especially due to the high cost per hip fracture patient. It is for example the one condition that is associated with the largest number of bed days in hospitals (12) and the total costs for treatment, care, and rehabilitation per hip fracture case is estimated to DKR (approx.16,446 USD) in the first years and DKR (approx.47,969 USD) in the first ten years after a hip fracture (8). Osteoporotic fractures can also have consequences for the individual in the form of chronic pain, reduced activities of daily living (13) and increased mortality (14-16). The excessive mortality persists for up to 10 years after hip fracture (15), but also after osteoporotic fractures in general (14). Health-related quality of life is also reduced after hip and vertebral fractures (17;18), to a level similar to or worse than that observed in women with other chronic diseases such as diabetes, arthritis and lung disease (17). Moreover, it have been calculated that the loss of disability-adjusted life years (DALY s) due to osteoporotic fractures in Europe is higher than that related to most cancer types, with exception of lung cancer (19). Thus, it is evident that osteoporosis through its association with osteoporotic fractures represents a major public health problem. In order to target public health measures regarding fracture prevention, it is important to identify individuals with increased risk of osteoporotic fracture. [1]

12 Introduction 1.2 Risk factors for osteoporosis and osteoporotic fractures In most cases, the aetiology of osteoporosis (defined by low bone mineral density, BMD) is multifactorial. Risk factors for osteoporosis include both non-modifiable, e.g. female gender, and modifiable factors, e.g. smoking (20-23). Osteoporosis in turn is a significant risk factor for fracture (24;25). Thus, risk factors for low BMD are also risk factors for fracture. Other risk factors, such as a tendency to falls, however, are related to fractures but not BMD (26;27). Furthermore, some risk factors, like smoking (28) and prior fracture (29), affect BMD but in addition have an independent effect on fracture risk. Some of the important risk factors for osteoporotic fractures and the estimated prevalence in Denmark are seen in Table 1. Table 1: Risk factors for osteoporotic fractures and estimated prevalence in the Danish population (%)* Prevalence Risk factor (Used definition to estimate prevalence) Women Men Age (5;30) (Age 60 years) (31) Female sex (5;21) (31) 50.4 Prior fracture (32;33) (Low energy fracture after age 40 years) (34) 11.5 (Low energy fracture after age 50 years) (35) 9.8 Tendency to falls/ history of frequent falls (26;36;37) ( 1 per year) a Inheritance / genetics (38-40) (Hip fracture in first degree relatives) a Low body mass index (41;42) (BMI <18.5) (43) Premature menopause (44;45) (<45 years) a 15.6 Smoking (28;46;47) (Current daily smoker) (43) Excessive alcohol intake (48;49) (>2 units a day) (43) (>3 units a day) (43) Physical inactivity (50;51) (Sedentary leisure time) (43) (Sedentary work life) (43) *Based on most reliable numbers available from Statistic Denmark or Danish health surveys a Based on unpublished results from the Danish Health Examination Survey A large number of medical disorders and medications are also associated with osteoporosis 1 and increased fracture risk. Some of these are endocrine disorders such as type 1-diabetes and thyroid disorders or gastrointestinal diseases such as chronic liver disease, inflammatory bowel disease and coeliac disease (1;29). Glucocorticoid use is the most common form of drug-related osteoporosis (52;53), but a Danish study mapping the prescriptiome to fractures in men revealed a large array of other medications also to be associated with fracture risk (54). Other risk factors have been suggested. One example is a potential detrimental effect of passive smoking (or second hand smoke) on BMD and fracture risk. Two animal studies have demonstrated that passive smoking significantly decreases BMD in rats after only two and four months of exposure, respectively (55;56). In the few human studies investigating this association (Table 2), most found a negative association between 1 Referred to as secondary osteoporosis, i.e. resulting from medications or other conditions. [2]

13 Introduction passive smoking and BMD, bone mineral content (BMC) or self-reported non-spine fractures. Most of these studies were relatively small, however, and two are only available as preliminary reports (57;58), making it difficult to compare the methodology and resulting data. Very different approaches to assess exposure to passive smoking appear to have been used and there is inconsistency between studies regarding the power of statistical methods. The largest study (n=14,060) using data from the Third National Health and Nutrition Examination Survey (NHANES-III) investigated the association between serum cotinine (as a marker for tobacco exposure) and BMC (59). Serum cotinine concentration reflects both passive and active smoking and as the regression analysis was not stratified or adjusted for smoking status, the results do not show the real effect of passive smoking. Further epidemiological studies investigating this potential association with more observations and allowing for confounder control are necessary, which will be one of the focuses in present thesis. [3]

14 Introduction Table 2: Previous studies of exposure to passive smoking on bone and fracture risk Author Year KIM KH et al a (60) Altunbayrak O et al b (57) Hsu YH et al b (58) Benson BW, Shulman JD 2005 (59) Afgahni A et al (61) Blum M et al (62) Country Korea Turkey China USA Cypress USA Study design Crosssectional Crosssectional Crosssectional Crosssectional Crosssectional Crosssectional Population (N) KHANES IV Postmenopausal women 55+ years (925) Postmenopausal women years Men and women years (13,376) NHANES III Men and women 20+ years (14,060) Boys and girls 12 years (466) Premenopausal women years (151) a Published after the publication of paper I in this thesis b Only published as abstracts Assessment of Passive Smoking Self-reported exposure among never-smokers: duration per day Cigarettes smoked by family members per day. Urinary cotinine concentration Self-reported exposure to smoking: active smoker, passive smoker, or neither Self-reported exposure: number of family members smoking daily Serum cotinine, as a marker for tobacco exposure Self-reported exposure: days or hours around smokers (in same room or vehicle) in last 7 days Self-reported history of exposure to household tobacco smoke at any age (10 years to present) Outcome BMD Femoral neck Lumbar spine By DXA BMD Femoral neck Lumbar spine By DXA BMD Hip By DXA Self-reported non-spine fractures BMC Femur By DXA BMD & BMC Forearm Heel By DXA BMD Hip Lumbar spine Total body By DXA Confounder control Age Height, weight Alcohol intake Physical activity Dietary calcium intake Not stated Age Height, weight Occupation Physical activity Education Age Height, weight Bone area Place of birth Oestrogen Ethnicity Activity level Diabetes Age Height Lean body mass Fat mass Sports team participation Active smoking Menarche (girls) Height, weight, Pack-years Education Daily calcium intake Findings OR=2.26 for femoral neck osteoporosis when exposed at home OR=2.02/2.74 for spine and femoral neck osteoporosis If >0 smoked cigarettes/day by cohabitants Association between urinary cotinine an selfreported passive smoking Lumbar spine and femoral neck T- scores lower among active and passive smokers Higher OR for osteoporosis and non-spine fracture in men/ premenopausal women with exposure to passive smoking Inverse relationship between serum cotinine and BMC (Men: β=-0.62, Women: β=-0.04) No association Subjects exposed to passive smoking had lower mean adjusted BMD at total hip and lumbar spine ( difference) [4]

15 Introduction 1.3 Methods for identifying high risk persons Dual-energy X-ray absorptiometry (DXA) is widely used to measure BMD at the hip and lumbar spine and is considered the gold standard for identifying persons at high risk for osteoporotic fracture, diagnosis and to monitor treatment (25). Since 1994 the diagnosis of osteoporosis has primarily been based on central DXA (at the hip or spine), by comparing the person s measured BMD with the mean BMD in healthy young adults of the same sex and ethnicity (1). Other scanners that measure BMD in the peripheral skeleton are also available (63) (Table 3). Table 3: Examples of peripheral BMD systems System Single-energy x-ray absorptiometry (SXA) Computed tomography (CT) Quantitative ultrasound (QUS) Digital x-ray radiogrammetry (DXR) Photodensitometry (PD) Radiographic absorptiometry (RA) Measurement site Forearm Forearm Calcaneus (heel) Phalanges of the hand and metacarpals Phalanges of the hand and metacarpals Phalanges of the hand and metacarpals The RA technique is more than 50 years old (64). Advantages of using the phalanges to measure BMD are the small amount of surrounding tissue and the easy access. Also, these tissues are relatively insensitive to ionising radiation. Earlier versions of RA scanners required analysis of the hand radiographs at a central reading facility and hence a slower response process (65). This is no longer necessary with the newer versions (66), such as the Alara MetriScan bone densitometer used in the studies presented in this thesis. This scanner is portable, easy to use, fast and exposes the patients to only low radiation doses (67). The validity and performance of peripheral BMD systems may be evaluated according to their ability to 1) predict osteoporotic fractures, 2) identify osteoporosis (as defined by low BMD at hip or lumbar spine), and 3) monitor treatment. Several studies have investigated the association between central and peripheral BMD and the risk of fracture. Both prospective studies (68-73), case-control studies (74-76) and a meta-analysis (25) have found that low BMD in finger, hand and forearm is related to increased risk of fracture. Siris et al. (2001) reported that low peripheral BMD (T-scores -2.5) in postmenopausal women was associated with a fracture rate around four times higher than normal BMD after 1-year of follow-up (77). None of these studies used the MetriScan system, however, nor tested the relationship in a population-based cohort that included men. Table 4 shows studies that have investigated the correlation between phalangeal BMD as measured with RA (MetriScan) and hip/lumbar spine BMD as measured with DXA, and assessed the ability of the scanner to identify osteoporosis. [5]

16 Introduction Table 4: Studies that have evaluated phalangeal densitometry (MetriScan) compared with DXA Author year Dhainaut et al (78) Buch et al (79) Hansen et al (80) Thorpe & Steel 2008 (66) / Blake et al (81) Boonen et al (82) Country Norway Denmark Denmark UK Belgium * Low energy fracture (LEF) Population (N) Women LEF* patients & recruited from general population years (355) Men and women LEF* Patients (74) Men Randomly selected years (218) Women Attending routine DXA years (170) Women Referred to Centre for metabolic bone diseases years (221) Assessment phalangeal BMD Arbitrary units (AU) Non-dominant hand T-score based on manufacturer s database AU Non-dominant hand T-score based on manufacturer s database AU Non-dominant hand AU Non-dominant & dominant hand T-score based on manufacturer s database AU Non-dominant hand T-score based on manufacturer s database Outcome DXA BMD Lumbar spine (L2 L4) Femoral neck Total hip T-score based on manufacturer s database Osteoporosis T-score -2.5 femoral neck BMD Lumbar spine (L2 L4) Femoral neck T-score based on manufacturer s database Osteoporosis T-score -2.5 hip or spine BMD Lumbar spine (L2 L4) Total Hip T-score based on local reference database Osteoporosis T-score -2.5 hip or spine BMD Lumbar spine (L2 L4) Femoral neck T-score based on manufacturer s database for lumbar spine and NHANES for total hip Osteoporosis T-score -2.5 hip or spine BMD Lumbar spine (L2 L4) Femoral neck T-score based on manufacturer s database Osteoporosis T-score -2.5 hip or spine Analyses Correlation coefficient AUC (osteoporosis) Triage thresholds (90% sensitivity/ 90% specificity) Correlation coefficient AUC (osteoporosis) Sensitivity 100%: number of DXA scans avoided Correlation coefficient AUC (osteoporosis) Sensitivity/ specificity Correlation coefficient Triage thresholds (90% sensitivity/ 90% specificity) Correlation coefficient AUC (osteoporosis) Sensitivity/ specificity Findings 28.5% osteoporotic R=0.65 femoral neck R=0.65 total hip R=0.59lumbar spine AUC=0.84 (all) AUC=0.83 (general population) AUC=0.83 (LEF* patients) Cut-off thresholds: <- 1.5 and < % referred for DXA 39% osteoporotic R=0.62 femoral neck R=0.68 lumbar spine AUC=0.85 (women) Cut-off: sensitivity = 100% Specificity = 30% 19% avoided DXA scans 7% osteoporotic R=0.47 total hip R=0.46 lumbar spine AUC=0.75 Ex.62 AU cut-off: sensitivity= 93% Specificity = 50% 41% osteoporotic Non-dominant hand: R=0.54 total hip R=0.31 lumbar spine Dominant hand: R=0.56 total hip R=0.56 lumbar spine Cut-off thresholds: Non-dominant hand <-0.62 and < % referred for DXA 19% osteoporotic R total hip not stated R=0.66 lumbar spine AUC=0.80 Ex.52 AU cut-off (Tscore <-1.3): sensitivity= 83% Specificity = 66% Increasing attention is being paid to the use of risk assessment algorithms (tools) to identify persons at high risk for osteoporotic fractures. In some studies clinical risk factors have been shown to have similar discriminatory power as BMD and to enhance prediction of facture risk (83). Several risk assessment tools have been developed to combine risk factors into a single estimate of fracture risk for an individual. In a [6]

17 Introduction recent systematic review we identified a total of 48 tools (84). The best validated tools and the included risk factors are shown in Table 5 (seven tools were developed to identify individuals at risk of low BMD (ABONE, BWC, ORAI, ORISIS, OST, NOF, SCORE) and four to identify individuals with an increased risk of fractures (FRAX, FRISC GARVAN, Qfracture, SOF)) (84). Table 5: Risk assessment tools and included clinical risk factors (modified from Rubin KH et al. (84)) Risk factors FRAX (85) FRISC (86) GARVAN (87) Qfracture (88) SOF (29) ABONE (89) BWC (90) ORAI (91) OSIRIS (92) OST(A) (93;94) Age X X X X X X X X X X X Weight X X X X X X X X X X X X Height X X Sex X X X Ethnicity X BMD X X X X Previous low energy fracture X X X X X X X Parental (hip) fracture, family history of fracture/osteoporosis X X X X Falls X X X Smoking X X X Alcohol X X Menopausal X Secondary osteoporosis (as defined in FRAX)* X X X X Rheumatoid arthritis X X X Type 2 diabetes X Asthma X Cardiovascular disease X Dementia X Glucocorticoid therapy X X Oestrogen therapy X X X X X Tricyclic antidepressants X Benzodiazepine use X Anticonvulsant drug use X Caffeine X Self-reported health X Pulse >80 beats/min X Physical inactivity X Back pain X Use arms to stand up from a chair X *These include type I (insulin dependent) diabetes, osteogenesis imperfecta in adults, untreated long-standing hyperthyroidism, hypogonadism or premature menopause (<45 years), chronic malnutrition, or malabsorption and chronic liver disease NOF (95) SCORE (96) As seen in table 5, the number of risk factors included in the different tools varies, with BWC being the simplest tool (includes only weight) and Qfracture the most complex. Although the tools have not yet found broad acceptance, the WHO Fracture Risk Assessment Tool (FRAX ), which predicts the 10-year probability of hip and major osteoporotic fractures (85;97), is increasingly used and has been incorporated into guidelines (98;99). Thus in the UK, FRAX is used for selecting patients to offer treatment (100). [7]

18 Introduction Some researchers have proposed combining the result of a peripheral densitometer and risk assessment tool in order to select persons to be referred for DXA or identify patients with high risk of osteoporotic fractures ( ). 1.4 Fracture prevention It is a general assumption that efforts to prevent osteoporotic fractures should focus both on achieving a high peak bone mass, maintaining or increasing bone mass and preventing falls. Prevention could target modifiable risk factors e.g. low body mass index (BMI), falls, smoking and excessive alcohol intake (previously mentioned in section 1.2). Studies have shown, for example, that smoking cessation increases BMD (47;106), and that different types of exercise can improve BMD, and reduce falls and fractures ( ). Several drugs can reduce the fracture risk. Randomized, placebo-controlled studies have thus demonstrated that treatment with vitamin D and calcium ( ), oestrogen (114), bisphosphonates (115), raloxifene (116), strontium ranelate (117), parathyroid hormone (118;119) and denosumab (120) reduce the incidence of fractures by 15 80% depending on the specific drug, skeletal site and study population. Most patients (approximately 90%) with osteoporosis can be treated with oral bisphosphonates (such as alendronate and risedronate) that are now available as generics. 1.5 Current guidelines and recommendations In Denmark (as in other countries), a case-finding strategy has been adopted, where general practitioners (GPs) are advised to refer persons with one or more risk factors to DXA scan. According the national Danish guidelines, reimbursement of anti-osteoporotic medication are determined by DXA results unless hip or spine fracture is present (121;122). In Denmark, drugs are reimbursed in case of 1) X-ray verified hip or spine fracture; 2) very low BMD (T-score <-4); 3) one or more risk factors for fracture and low BMD (T-score -2.5); and 4) planned or initiated supra-physiological doses of glucocorticoid (at least 5 mg per day for three or more months) and osteopenia (T-score <-1) (121;122). Recommendations issued by international medical societies and authorities differ somewhat. The U.S. Preventive Services Task Force (USPSTF) recommends screening with DXA in all women aged 65+ years and in women <65 years with increased risk of fracture (whose 10 year fracture risk is equal to or greater than that of a 65 year old white woman without additional risk factors; 9.3% based on FRAX calculation); diagnosis and treatment is determined from the DXA result (99). These US recommendations conclude that evidence is lacking about the optimal interval for repeated screening, and that Men most likely to benefit [8]

19 Introduction from screening have a 10-year risk for osteoporotic fracture equal to or greater than that of a 65-year-old white woman without risk factors. However, current evidence is insufficient to assess the balance of benefits and harms of screening for osteoporosis in men (99). The US National Osteoporosis Foundation (NOF) recommends DXA testing in women aged 65+ years and in men aged 70+ years as well as in postmenopausal women and men aged years with high risk factor profile. Moreover, in the newly updated 2013 version, they recommend vertebral imaging in various risk groups 2 to diagnose vertebral fractures (98). Treatment should be initiated in those with 1) hip or vertebral (clinical or asymptomatic) fractures, 2) low BMD at femoral neck, total hip and lumbar spine (T-score -2.5), and 3) in postmenopausal women and men aged 50+ years with T-score between -1.0 and -2.5 at the femoral neck, total hip or lumbar spine by DXA and a 10-year hip fracture probability 3% or a FRAX 10-year major osteoporotic fracture probability 20% (98). The International Osteoporosis Foundation (IOF) and European Society for Clinical and Economic Aspect of Osteoporosis and Osteoarthritis (ESCEO) recently updated their European guidance for the diagnosis and management of osteoporosis in postmenopausal women. It holds three assessment scenarios that depend on the access to DXA, and based on these specific guidelines can be developed. For example in countries with limited access to DXA it is recommended that women with fragility fracture should be considered for treatment. Women without fragility fracture, but with one or more clinical risk factors, the 10 year fracture probability by FRAX should be used to define intervention thresholds. These are age-specific recommending either no treatment, measure BMD and consider treatment (100). Peripheral BMD systems are generally not recommended for diagnosis of osteoporosis (2;98;121). NOF acknowledges that portable scanners can be used for community-based screening programmes, but the results are not equivalent to DXA and abnormal results should therefore be confirmed by physical examination, risk assessment and central DXA (98). The UK National Osteoporosis Society (NOS) has proposed the use of peripheral densitometers in the management of osteoporosis. In this approach, thresholds are set at 90% sensitivity and 90% specificity for identifying osteoporosis (T-score -2.5) at either hip or spine (123). If the BMD at a peripheral site is below the lower threshold, treatment is recommended; if the BMD is between the thresholds, the person should be referred to DXA of hip and spine; and if the BMD is above the higher threshold, no further action is required (123). 2 1) In women aged 65+ years and men aged 70+ years to diagnose vertebral fracture if T-score is -1.5, 2) In women aged 70+ years and men aged 80+ years regardless of T-score, 3) In postmenopausal women and men aged 50+ years with a low energy fracture, 4) In postmenopausal women and men aged if there is height loss of 4 cm (1.5 inches) or more, or recent or ongoing long-term glucocorticoid treatment. [9]

20 Introduction 1.6 Challenges in fracture prevention The identification of individuals with increased risk of osteoporotic fracture is an important challenge in the field of osteoporosis. Evidence suggests that the current strategy does not perform well. Indeed, osteoporosis is under-diagnosed and under-treated in Denmark and probably also elsewhere (7). In Denmark, it have been estimated that it is only around 25% of all persons with a high risk of osteoporotic fractures (defined as tree or more risk factors) that are referred to DXA examination, and controversy, a relatively high proportion of examinations are performed in persons with a low risk of osteoporotic fractures (34). This is supported by similar studies from other countries (124;125). Another challenge is that central DXA is inaccessible in many countries and regions, and furthermore, it has been found, that longer distances to DXA-facilities seem to be associated with lower use of DXA (34;35;126). Overall, there is a need of devising new strategies for identifying persons with high risk of fracture. [10]

21 Aim 2. Aim of the thesis The overall aim of this thesis was to investigate the concept of fracture risk prediction and approaches for measuring fracture risk. The primary objective was to evaluate a method for measuring BMD at the phalanges for its ability to predict fracture risk and pre-select individuals at high risk for osteoporotic fracture. Moreover, it was to investigate passive smoking as a possible new risk factor for osteoporosis that should be considered when evaluating fracture risk in men and women. The thesis is based on four studies with different aims: Paper I Paper II Paper III Paper IV To examine a potential association between phalangeal BMD and passive smoking in the adulthood home To examine the ability of phalangeal BMD to predict osteoporotic fractures in men and women To examine the use of phalangeal BMD versus the WHO Fracture Risk Assessment tool (FRAX) and age alone (and FRAX and BMD in combination in different risk strata) to predict osteoporotic fractures in men and women To investigate the correspondence between phalangeal BMD and central DXA BMD and to define triage thresholds to be used in pre-selection based on NOS recommendations in a cohort of Danish Women aged 65+ years [11]

22 Methods and data sources 3. Methods and data sources The thesis is primarily based on data from the Danish Health Examination Survey (DANHES) (Papers I, II and III) and from the Danish national registers (Papers II and III). Paper IV is based on data from the Danish Riskstratified Osteoporosis Strategy Evaluation study (ROSE). An overview of the aims, methods and data used is presented in Table 6. Further details are provided in the following sections. Table 6. Overview of aims, methods and data used in the four papers of this thesis Paper I Paper II Paper III Paper IV Aim To investigate an association between phalangeal BMD and passive smoking To investigate the ability of phalangeal BMD to predict osteoporotic fractures To investigate the ability of phalangeal BMD, FRAX (calculated 10 year fracture probability) and age as well as FRAX and BMD in combination in different risk strata to predict osteoporotic fractures To investigate the correspondence between phalangeal BMD measured with RA and BMD at lumbar spine and total hip measured with DXA Design Cross-sectional Prospective Prospective Cross-sectional Duration of NA Mean 3.2 years Mean 4.3 years NA follow-up [0.03 to 3.82] [0.03 to 4.94] Data source DANHES DANHES Danish national Registers DANHES Danish national registers ROSE Participants Exposure/ Independent variable(s) Men and women Aged 18+ years Residing in 12 Danish municipalities N= 15,038 Passive smoking in private residence during adulthood Men and women Aged 18+years Residing in 12 Danish municipalities N=15,542 Phalangeal BMD Men and women Aged years Residing in 12 Danish municipalities N=12,758 Phalangeal BMD 10 Year fracture probability (FRAX) Age Women Aged years Residing in the Region of Southern Denmark N=121 Phalangeal BMD Outcome Phalangeal BMD Incident fractures Incident fractures Lumbar spine and total hip BMD Confounders/ other variables Sex History of osteoporosis Statistical methods Sex Age Height and weight Smoking Physical activity Education Alcohol consumption Body fat percentage Parental hip fracture Sex Age Prevalent fractures Multiple regression Survival analysis Survival Analysis C statistics Correlation Bland Altman Sensitivity, specificity [12]

23 Methods and data sources 3.1 The Danish Health Examination Survey (DANHES) The Danish Health Examination Survey was the largest combined study on health in Denmark (127;128). Its aim was to improve knowledge on health and lifestyle in the Danish population, to increase the general focus on health and lifestyle (diet, smoking, alcohol and exercise) and to establish a research database for future studies (127;128). All 98 Danish municipalities were invited to apply for participation in the study and 13 were selected based on their application. During the month when the health examination survey took place the concerning municipality also had to initiate a range of activities and initiatives for their citizens aiming at improving health and promoting healthy lifestyles The health examination survey was conducted by the National Institute of Public Health, University of Southern Denmark, with input from other research groups, and funded by the Danish Ministry of Health and the Tryg Foundation. All adult citizens aged 18+ years in the 13 municipalities were invited by letter to complete a self-report (internet-based) questionnaire comprising 144 items on the following topics: sociodemographics; anthropometry; diet; alcohol consumption; smoking history; physical activity; health promotion and prevention; quality of life; health, morbidity, symptoms, medication and contact with health services; pregnancy, childbirths and menopause, and absence from work. People could also answer a supplementary food frequency questionnaire. If necessary, the person could request a paper version of the questionnaire. Of the 538,497 people invited to complete the questionnaire, 76,484 responded (Figure 1), corresponding to an overall response rate of 14%. The response rate ranged between 8% and 20% depending on municipality. A representative subsample was invited to participate in a health examination that included measurement of blood pressure, resting heart rate, height, weight, fat percentage, waist and hip circumference, blood and hair samples, spirometry, phalangeal BMD, physical performance, muscle strength and aerobic fitness (wattmax or sub watt-max). The invitation included a leaflet with general information about the health examination. The numbers invited to participate to cover all appointments were based on experience in the pilot study in Aalborg municipality and on estimates of the geographic and socio-demographic circumstances in the municipality. Of the 180,103 persons invited to the health examination, 18,065 participated giving a participation rate of 10.0% (range %) (Figure 1). The health examination began with oral information about the examination and then a screening interview to check for any medical condition that would exclude the person from the physical tests. Written informed consent was obtained. The examinations were performed by trained staff from the National Institute of Public Health and approved by the Danish Data Protection agency (J.nr ). [13]

24 Methods and data sources Figure 1. Flow chart showing inclusion of participants in DANHES Participants invited to answer questionnaire All residents in 13 municipalities without research protection N=538,497 Participants answered the questionnaire N= 76,484 (14.2%) Drop-out N= 462,013 (85.8%) Representative sample invited to participate in health examination N= 180,103 Participants participating in health examination N= 18,065 (10.0%) Participants with BMD scan N= 15,544 Drop-out N= (90%) Excluded, no BMDscan*, N=2,521 Participants both answered the questionnaire and had a BMD scan N=15,038 * BMD scan was not a part of the pilot study in Aalborg municipality [14]

25 Methods and data sources Phalangeal BMD Phalangeal BMD was measured at the middle phalanges of the 2 nd, 3 rd and 4 th fingers on the non-dominant hand using a compact radiographic absorptiometry (RA) system (Alara MetriScan, Alara Inc. Fremont, USA). X-ray exposure was <0.02 µsv per examination. All staffs were trained and capable of operating the scanner and the results appeared on the integrated screen after about one minute. Pregnant women were excluded. Participants were asked to remove any jewellery from the non-dominant hand (otherwise the scan was performed on the dominant hand) and to place the hand on the moulded support plate. BMD was expressed in arbitrary units (mineral mass/area), g/cm 2 and T-scores. The T-score compares measured BMD with the average BMD for a young healthy subject of the same sex ( ) and was derived from a reference database provided by the manufacturer. This database contained data on 1,500 healthy females aged years; the T-scores were calculated from the group aged years. We then used the WHO T-score cut-offs for osteoporosis and osteopenia (>-1 = normal, between -1 and 2.5 = osteopenia, -2.5 = and osteoporosis) (1). After the health examination, participants were informed on their result and patients with T-scores below -2.5 and with one or more risk factor were advised to consult their GP. For papers II and III, we calculated gender-specific T-scores using our own database, including men and women from DANHES aged years as reference Passive smoking in adulthood home The DANHES questionnaire included questions on current exposure to passive smoking (hours/day) and longterm exposure (in household and workplace). In Paper I we only investigated the effect of long-term exposure. Prior to the questions on passive smoking, the questionnaire stated: You are exposed to passive smoking when you spend time in rooms where people smoke or where smoke from other parts of the building is in the air. Smokers are also passive smokers when they spend time in rooms where smoke is in the air. The question in relation to adulthood passive smoking was: How many years have you been exposed to passive smoking daily or almost daily at home as an adult? Subjects were categorized as passive smokers if they had been exposed to passive smoking for one or more years. Duration of exposure to passive smoking was classified into four different intervals (unexposed, 1 9 years, years and 20+ years). [15]

26 Methods and data sources Clinical risk fractures for low BMD and fractures applied Smoking The subjects were also asked about current and past smoking status, whether they had formerly smoked daily and the average number of cigarettes, cigars and cheroots smoked per day. Smoking status included the following categories: daily, occasional, former and never smoker. We defined current smokers to only include daily smokers (used in paper III). Total pack-years of active smoking were calculated by multiplying the average number of packs smoked per day by the number of years of daily smoking and were divided into four intervals: 0, >0 9, and 20+ pack-years (paper I). Alcohol intake Alcohol intake was measured in units (10 ml or 8 grams of alcohol) per week and in paper I categorized as a binary variable, i.e. more/less than the recommended maximum intake of alcoholic beverages issued by the Danish Health and Medicines Authority 3 (129) (14 units/week for women; 21 units/week for men). In paper III, units per week were divided by seven to obtain the average daily consumption (more or less than three units per day). Physical activity The question on physical activity comprised the following categories: a) Heavy exercise and competitive sports (regularly and several times a week) or exercise or heavy gardening at least four hours a week; these were defined as vigorous or moderate physical activity in paper I; b) Walking, cycling or other light exercise at least four hours a week (including Sunday excursions, light gardening and cycling or walking to work); these were defined as light physical activity in paper I; c) Reading, watching TV or other sedentary activity; these were defined as sedentary physical activity in paper I. Body height, weight, BMI and fat percentage Height and weight were measured as part of the health examination. Height was measured with bare feet to the nearest cm using a portable stadiometer (Leicester Height Measure, Chasmors Ltd.). Body weight and fat percentage were measured without shoes, socks and outer garments with a BC 418 MA Segmental Body Composition Analyser from Tanita (MDD Approved/NAWI Class III). One kilogram was subtracted from the weight to compensate for clothes. BMI was calculated as weight/ height 2 (kg/m 2 ). Premature menopause Women were asked if their menstruation had stopped and if so how old were you, when you last had your period? Premature menopause was defined as menopause occurring before the age of 45 years. 3 Lower risk limits have since been defined by the Danish Health and Medicines Authority (7 units/week for women; 14 units/week for men) [16]

27 Methods and data sources Parental hip fracture In the questionnaire, subjects were asked if their biological mother, father or siblings had experienced a hip fracture after the age of 50 years. Hip fracture in first-degree relative was registered as a binary variable (yes/no) in paper I and as parental hip fracture (holding only information on mother and father) in paper III. Educational level Educational level was classified according to the International Standard Classification of Education (ISCED) combining (on-going or completed) school and vocational education based on information from four different questions and divided into four categories: <10, 10 12, 13 14, 15+ years. 3.3 Register data and ascertainment of osteoporotic fractures For papers II and III, participants in the health examination were followed up using the Danish national registers to identify fracture outcome. This is possible because all persons residing in Denmark are assigned a unique personal identification number, which is a ten-digit number including the date of birth and four other digits. This identification number is consistent throughout all national Danish registers and can be used to link data from all public registers at an individual level (130) and questionnaire data with register data. Data from DANHES were thus merged with information on fracture and surgical procedures from the National Patient Register (NPR) and information on death and emigration from the Civil Registration System. NPR contains data on all patients admitted to any Danish hospital since The register includes discharge diagnoses of hospitalized patients indicating the main medical reason for diagnostic procedures or treatment. Similarly, all outpatient visits and patients seen in emergency rooms are included since Discharge diagnoses are coded by physicians according to the tenth version of the International Classification of Diseases (ICD-10). Surgical procedures are registered by surgical codes according to the Danish version of the Nordic Classification of Surgical Procedures (131). We extracted data on prevalent and incident major osteoporotic fractures i.e. vertebral fractures plus fractures of the humerus, forearm and hip, as these are the most frequently seen fractures caused by osteoporosis (5). The corresponding ICD-10 codes are shown in Table 7. Incident fractures were defined as fractures occurring between the date of BMD measurement and the end of follow-up. Fracture events were calculated as number of persons with a fracture during the follow-up period. Prevalent fractures were defined as fractures occurring after the 1 st January 1994 (when ICD-10 codes were introduced into Denmark (131)) and before the date of BMD measurement in the health examination. Hip fractures were validated [17]

28 Methods and data sources using surgical codes of primary hip arthroplasty or osteosynthesis (NFB00 92 and NFJ00 92, respectively) and hip fractures without corresponding surgical procedures were excluded (132). Table 7. ICD-10 fracture codes used for data extration Hip fractures DS720, DS721A B, DS722 Vertebral fractures DS120, DS121A B, DS122A E, DS220A L DS320A E, DT08A Forearm fractures DS525A C, DS526 Humerus fractures DS422A C, DS423A Individuals were included in the cohort and observed from the date of the health examination with BMD scan. Follow-up in paper II ended on 1 st July 2011 and in paper III on 10 th August 2012, date of failure (fracture), date of death or migration as appropriate. 3.4 Calculation of 10 year probability of fracture by FRAX In paper III we calculated the 10 year fracture probability of fracture among participants in the DANHES. The FRAX calculation is based on the following risk factors: age, sex, height (cm), weight (kg), history of fracture, parental history of hip fracture, current smoking, three or more units of alcohol per day, use of glucocorticoids within the last 3 months, presence of rheumatoid arthritis, and other types of secondary osteoporosis ( ). The algorithm for the FRAX calculation is still not published, but it is possible to calculate the 10 year fracture probability on an individual level using the FRAX website (97). The FRAX value was thus calculated by individual risk scoring of the Danish version of FRAX (97) using a programmed call of the FRAX website (version 3.1) produced by a Danish It-company, Langtved Data, Odense, Denmark (136). Only persons between years can be scored by FRAX. Information on height and weight were obtained from the health examination. Information on smoking (daily smokers listed as current smokers in FRAX), alcohol consumption and parental history of hip fracture after the age of 50 years was extracted from the DANHES questionnaire. Information on fracture history (hip, forearm, vertebral and humerus), presence of rheumatoid arthritis and other types of secondary osteoporosis was extracted from NPR (the corresponding ICD-10 codes are listed in Table 8). Information on premature menopause, before the age of 45 years, was also extracted from the DANHES questionnaire and incorporated in FRAX as secondary osteoporosis. Unfortunately we had no information on glucocorticoid use. FRAX was not calculated if data on height or weight were missing, and these subjects were excluded from analyses (n=5). We adopted the high-risk threshold used by the National Osteoporosis Foundation (NOF): 10 year hip fracture probability 3% or a [18]