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Leslie WD, Burrell S, Morin SN. Fracture Risk Assessment in the 2023 Osteoporosis Canada Guideline. Can Assoc Radiol J 2025:8465371241307945. [PMID: 39797546 DOI: 10.1177/08465371241307945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2025] Open
Abstract
Radiologists and other diagnostic imaging specialists play a pivotal role in the management of osteoporosis, a highly prevalent condition of reduced bone strength and increased fracture risk. Bone mineral density (BMD) measurement with dual-energy X-ray absorptiometry (DXA) is a critical component of identifying individuals at high risk for fracture. Strategies to prevent fractures are consolidated in the Osteoporosis Canada clinical practice guideline which was updated in 2023. In this guideline, treatment recommendations are based upon a consideration of fracture history, 10-year major osteoporotic fracture (MOF) risk, and BMD T-score in conjunction with age. The current review aims to familiarize radiologists and other diagnostic imaging specialists with the reporting requirements needed to support implementation of this guideline using the FRAX™ risk calculation tool. Fortunately, for specialists already familiar with the Canadian Association of Radiologists and Osteoporosis Canada (CAROC) tool, the transition to FRAX-based reporting is readily accommodated in a radiology workflow.
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Affiliation(s)
| | - Steven Burrell
- Department of Radiology, Dalhousie University, Halifax, NS, Canada
| | - Suzanne N Morin
- Department of Medicine, McGill University, Montreal, QC, Canada
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Leslie WD. Effect of Race/Ethnicity on United States FRAX Calculations and Treatment Qualification: A Registry-Based Study. J Bone Miner Res 2023; 38:1742-1748. [PMID: 37548387 DOI: 10.1002/jbmr.4896] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/23/2023] [Accepted: 08/04/2023] [Indexed: 08/08/2023]
Abstract
Since 2008. the United States has had four race/ethnic fracture risk assessment tool (FRAX) calculators: White ("Caucasian"), Black, Asian, and Hispanic. The American Society for Bone and Mineral Research Task Force on Clinical Algorithms for Fracture Risk has been examining the implications of retaining race/ethnicity in the US FRAX calculators. To inform the Task Force, we computed FRAX scores according to each US calculator in 114,942 White, 485 Black, and 2816 Asian women (self-reported race/ethnicity) aged 50 years and older. We estimated treatment qualification based upon FRAX thresholds (3% for hip fracture, 20% for major osteoporotic fracture [MOF]). Finally, we examined measures for a hypothetical population-based FRAX calculator derived as the weighted mean for the US population based upon US Census Bureau statistics. With identical inputs, the highest FRAX measurements were found with the White FRAX calculator, lowest measurements with the Black calculator, and intermediate measurements for the Asian and Hispanic calculators. The percentage of women with FRAX scores exceeding the hip fracture treatment threshold was 32.0% for White, 1.9% for Black, and 19.7% for Asian women; the MOF treatment threshold was exceeded for 14.9% of White, 0.0% of Black, and 3.5% of Asian women. Disparities in treatment qualification were reduced after considering additional criteria (fracture history and dual-energy X-ray absorptiometry [DXA] T-score -2.5 or lower). When fracture risk was recalculated for non-White women using the White FRAX calculator, mean values for Asian women slightly exceeded those for White women but for Black women remained substantially below those for White women. When using a single population-based FRAX calculator, the mean probability of fracture and treatment qualification increased for non-White women across the age range. In summary, use of a single population-based FRAX calculator, rather than existing US race/ethnic FRAX calculators, will reduce differences in treatment qualification and may ultimately enhance equity and access to osteoporosis treatment. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- William D Leslie
- Department of Medicine, University of Manitoba, Winnipeg, Canada
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Kong XK, Zhao ZY, Zhang D, Xie R, Sun LH, Zhao HY, Ning G, Wang WQ, Liu JM, Tao B. Major osteoporosis fracture prediction in type 2 diabetes: a derivation and comparison study. Osteoporos Int 2022; 33:1957-1967. [PMID: 35583602 DOI: 10.1007/s00198-022-06425-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/04/2022] [Indexed: 10/18/2022]
Abstract
UNLABELLED The widely recommended fracture prediction tool FRAX was developed based on and for the general population. Although several adjusted FRAX methods were suggested for type 2 diabetes (T2DM), they still need to be evaluated in T2DM cohort. INTRODUCTION This study was undertaken to develop a prediction model for Chinese diabetes fracture risk (CDFR) and compare its performance with those of FRAX. METHODS In this retrospective cohort study, 1730 patients with T2DM were enrolled from 2009.08 to 2013.07. Major osteoporotic fractures (MOFs) during follow-up were collected from Electronic Health Records (EHRs) and telephone interviews. Multivariate Cox regression with backward stepwise selection was used to fit the model. The performances of the CDFR model, FRAX, and adjusted FRAX were compared in the aspects of discrimination and calibration. RESULTS 6.3% of participants experienced MOF during a median follow-up of 10 years. The final model (CDFR) included 8 predictors: age, gender, previous fracture, insulin use, diabetic peripheral neuropathy (DPN), total cholesterol, triglycerides, and apolipoprotein A. This model had a C statistic of 0.803 (95%CI 0.761-0.844) and calibration χ2 of 4.63 (p = 0.86). The unadjusted FRAX underestimated the MOF risk (calibration χ2 134.5, p < 0.001; observed/predicted ratio 2.62, 95%CI 2.17-3.08), and there was still significant underestimation after diabetes adjustments. Comparing FRAX, the CDFR had a higher AUC, lower calibration χ2, and better reclassification of MOF. CONCLUSION The CDFR model has good performance in 10-year MOF risk prediction in T2DM, especially in patients with insulin use or DPN. Future work is needed to validate our model in external cohort(s).
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Affiliation(s)
- Xiao-Ke Kong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhi-Yun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Deng Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rui Xie
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Li-Hao Sun
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong-Yan Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei-Qing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jian-Min Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Bei Tao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Heilmeier U, Hackl M, Schroeder F, Torabi S, Kapoor P, Vierlinger K, Eiriksdottir G, Gudmundsson EF, Harris TB, Gudnason V, Link TM, Grillari J, Schwartz AV. Circulating serum microRNAs including senescent miR-31-5p are associated with incident fragility fractures in older postmenopausal women with type 2 diabetes mellitus. Bone 2022; 158:116308. [PMID: 35066213 DOI: 10.1016/j.bone.2021.116308] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 12/06/2021] [Accepted: 12/20/2021] [Indexed: 12/15/2022]
Abstract
Fragility fractures are an important hallmark of aging and an increasingly recognized complication of Type 2 diabetes (T2D). T2D individuals have been found to exhibit an increased fracture risk despite elevated bone mineral density (BMD) by dual x-ray absorptiometry (DXA). However, BMD and FRAX-scores tend to underestimate fracture risk in T2D. New, reliable biomarkers are therefore needed. MicroRNAs (miRNAs) are secreted into the circulation from cells of various tissues proportional to local disease severity. Serum miRNA-classifiers were recently found to discriminate T2D women with and without prevalent fragility fractures with high specificity and sensitivity (AUC > 0.90). However, the association of circulating miRNAs with incident fractures in T2D has not been examined yet. In 168 T2D postmenopausal women in the AGES-Reykjavik cohort, miRNAs were extracted from baseline serum and a panel of 10 circulating miRNAs known to be involved in diabetic bone disease and aging was quantified by qPCR and Ct-values extracted. Unadjusted and adjusted Cox proportional hazard models assessed the associations between serum miRNAs and incident fragility fracture. Additionally, Receiver operating curve (ROC) analyses were performed. Of the included 168 T2D postmenopausal women who were on average 77.2 ± 5.6 years old, 70 experienced at least one incident fragility fracture during the mean follow-up of 5.8 ± 2.7 years. We found that 3 serum miRNAs were significantly associated with incident diabetic fragility fracture: while low expression of miR-19b-1-5p was associated with significantly lower risk of incident fragility fracture (HR 0.84 (95% CI: 0.71-0.99, p = 0.0323)), low expression of miR-203a and miR-31-5p was each significantly associated with a higher risk of incident fragility fracture per unit increase in Ct-value (miR-203a: HR 1.29 (95% CI: 1.12-1.49), p = 0.0004, miR-31-5p HR 1.27 (95% CI: 1.06-1.52), p = 0.009). Hazard ratios of the latter two miRNAs remained significant after adjustments for age, body mass index (BMI), areal bone mineral density (aBMD), clinical FRAX or FRAXaBMD. Women with miR-203a and miR-31-5p serum levels in the lowest expression quartiles exhibited a 2.4-3.4-fold larger fracture risk than women with miR-31-5p and miR-203a serum expressions in the highest expression quartile (0.002 ≤ p ≤ 0.039). Women with both miR-203a and miR-31-5p serum levels below the median had a significantly increased fracture risk (Unadjusted HR 3.26 (95% CI: 1.57-6.78, p = 0.001) compared to those with both expression levels above the median, stable to adjustments. We next built a diabetic fragility signature consisting of the 3 miRNAs that showed the largest associations with incident fracture (miR-203a, miR-31-5p, miR-19b-1-5p). This 3-miRNA signature showed with an AUC of 0.722 comparable diagnostic accuracy in identifying incident fractures to any of the clinical parameters such as aBMD, Clinical FRAX or FRAXaBMD alone. When the 3 miRNAs were combined with aBMD, this combined 4-feature signature performed with an AUC of 0.756 (95% CI: 0.680, 0.823) significantly better than aBMD alone (AUC 0.666, 95% CI: 0.585, 0.741) (p = 0.009). Our data indicate that specific serum microRNAs including senescent miR-31-5p are associated with incident fragility fracture in older diabetic women and can significantly improve fracture risk prediction in diabetics when combined with aBMD measurements of the femoral neck.
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Affiliation(s)
- Ursula Heilmeier
- Musculoskeletal Quantitative Imaging Research Group, University of California San Francisco, San Francisco, CA, USA; Department of Rheumatology and Clinical Immunology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | | | - Fabian Schroeder
- Department of Molecular Diagnostics, Austrian Institute of Technology, AIT, Vienna, Austria
| | - Soheyla Torabi
- Musculoskeletal Quantitative Imaging Research Group, University of California San Francisco, San Francisco, CA, USA
| | - Puneet Kapoor
- Musculoskeletal Quantitative Imaging Research Group, University of California San Francisco, San Francisco, CA, USA
| | - Klemens Vierlinger
- Department of Molecular Diagnostics, Austrian Institute of Technology, AIT, Vienna, Austria
| | | | | | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, USA
| | - Vilmundur Gudnason
- The Icelandic Heart Association, Kopavogur, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Thomas M Link
- Musculoskeletal Quantitative Imaging Research Group, University of California San Francisco, San Francisco, CA, USA
| | - Johannes Grillari
- Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria; Austrian Cluster for Tissue Regeneration, Vienna, Austria; Christian Doppler Laboratory of Biotechnology of Skin Aging, Vienna, Austria; Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, Vienna, Austria
| | - Ann V Schwartz
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
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Leslie WD, Kanis JA. Calibration of FRAX: A Journey, not a Destination. Calcif Tissue Int 2021; 109:597-599. [PMID: 34304290 DOI: 10.1007/s00223-021-00891-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 07/05/2021] [Indexed: 10/20/2022]
Affiliation(s)
- William D Leslie
- Department of Medicine (C5121), University of Manitoba, 409 Tache Avenue, Winnipeg, Manitoba, Canada.
| | - John A Kanis
- Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield, UK
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
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Leslie WD, Morin SN, Lix LM, Binkley N. Comparison of treatment strategies and thresholds for optimizing fracture prevention in Canada: a simulation analysis. Arch Osteoporos 2019; 15:4. [PMID: 31858278 DOI: 10.1007/s11657-019-0660-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 10/02/2019] [Indexed: 02/03/2023]
Abstract
UNLABELLED This comparison of osteoporosis treatment strategies and intervention thresholds highlights tradeoffs in terms of number of individuals qualifying for treatment and estimated fractures prevented. PURPOSE The current analysis was performed to inform the following key question as part of the Osteoporosis Canada's Osteoporosis Guidelines Update: "What is the best strategy to identify those at high fracture risk for pharmacotherapy in order to prevent the most fractures, considering both population and patient perspectives?" METHODS The study population consisted of 66,878 women age 50 years and older (mean age 66.0 ± 9.7 years) with documented fracture probability assessment (FRAX) and fracture outcomes. Fractures over the next 5 years were identified through linked administrative healthcare data. We estimated the fraction of the population that would warrant treatment and the number of fractures avoided per 1000 person-years according to multiple strategies and thresholds. Strategies were then rank ordered using 19 metrics. RESULTS During mean 4.4 years, 863 (3.5%) sustained one or more major osteoporotic fractures (MOF), 212 (0.8%) sustained a hip fracture, and 1210 (4.9%) sustained any incident fracture. For woman age 50-64 years, the highest ranked strategy was treatment based upon total hip T score ≤ -2.5, but several other strategies fell within 0.5 overall ranking. For women age 65 years and older, MOF > 20% was the highest ranked strategy with no closely ranked strategies. Pooling both age subgroups gave MOF > 20% as the highest ranked strategy, with several other strategies within 0.5 overall ranking. CONCLUSIONS Choice of treatment strategy and threshold for osteoporosis management strongly influences the number of individuals for whom pharmacologic treatment would be recommended and on estimated fracture rates in the population. This evidence-based approach to comparing these strategies will help to inform guidelines development in Canada and may be on interest elsewhere.
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Affiliation(s)
- William D Leslie
- Department of Medicine, University of Manitoba, C5121-409 Tache Avenue, Winnipeg, Manitoba, R2H 2A6, Canada.
| | | | - Lisa M Lix
- Department of Medicine, University of Manitoba, C5121-409 Tache Avenue, Winnipeg, Manitoba, R2H 2A6, Canada
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Leslie WD, Lix LM, Majumdar SR, Morin SN, Johansson H, Odén A, McCloskey EV, Kanis JA. Total Hip Bone Area Affects Fracture Prediction With FRAX® in Canadian White Women. J Clin Endocrinol Metab 2017; 102:4242-4249. [PMID: 29092086 DOI: 10.1210/jc.2017-01327] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Accepted: 09/11/2017] [Indexed: 01/17/2023]
Abstract
CONTEXT Areal bone mineral density (BMD) measurements are confounded by skeletal size. Hip BMD is an input to the FRAX® tool (Centre for Metabolic Bone Diseases, University of Sheffield, United Kingdom), but it is unknown whether performance is affected by hip area. OBJECTIVE To examine whether fracture prediction by FRAX® is affected by hip area. DESIGN AND SETTING Cohort study using a population-based BMD registry. PATIENTS A total of 58,108 white women aged ≥40 years. MAIN OUTCOME MEASURES Incident major osteoporotic fracture (MOF; n = 4913) and hip fracture (n = 1369), stratified by total hip area quintile, before and after adjustment for hip axis length (HAL). RESULTS Smaller hip area was associated with younger age and lower FRAX® scores, whereas incident fractures were greater in those with larger hip area (P for trend < 0.001). Larger hip area quintile increased risk for MOF and hip fracture when adjusted for FRAX® score with BMD (P for trend < 0.001). Each standard deviation increase in hip area was associated with greater risk for incident MOF [adjusted hazard ratio (HR), 1.08; 95% confidence interval (CI), 1.05 to 1.11] and hip fracture (HR, 1.16; 95% CI, 1.11 to 1.21), but not after adjustment for HAL. FRAX® with BMD underestimated MOF risk in the largest hip area quintile and underestimated hip fracture risk in the three largest hip area quintiles. CONCLUSIONS In Canadian white women, skeletal size based on hip area affects fracture risk assessment based on FRAX® score with BMD, with risk underestimated in those with larger hip areas. Including HAL in the risk assessment compensates for this confounding by skeletal size and provides for more accurate assessment of fracture risk.
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Affiliation(s)
- William D Leslie
- Department of Medicine, University of Manitoba, Winnipeg, Manitoba R3E 3P5, Canada
| | - Lisa M Lix
- Department of Medicine, University of Manitoba, Winnipeg, Manitoba R3E 3P5, Canada
| | - Sumit R Majumdar
- Department of Medicine, University of Alberta, Edmonton, Alberta T6G 2G3, Canada
| | - Suzanne N Morin
- Department of Medicine, McGill University, Montreal, Quebec H4A 3J1, Canada
| | - Helena Johansson
- Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield S10 2RX, United Kingdom
- Institute for Health and Aging, Catholic University of Australia, Melbourne, Victoria 3000, Australia
| | - Anders Odén
- Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield S10 2RX, United Kingdom
| | - Eugene V McCloskey
- Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield S10 2RX, United Kingdom
| | - John A Kanis
- Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield S10 2RX, United Kingdom
- Institute for Health and Aging, Catholic University of Australia, Melbourne, Victoria 3000, Australia
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Abstract
The substantial increase in the burden of non-communicable diseases in general and osteoporosis in particular, necessitates the establishment of efficient and targeted diagnosis and treatment strategies. This chapter reviews and compares different tools for osteoporosis screening and diagnosis; it also provides an overview of different treatment guidelines adopted by countries worldwide. While access to dual-energy X-ray absorptiometry to measure bone mineral density (BMD) is limited in most areas in the world, the introduction of risk calculators that combine risk factors, with or without BMD, have resulted in a paradigm shift in osteoporosis screening and management. To-date, forty eight risk assessment tools that allow risk stratification of patients are available, however only few are externally validated and tested in a population-based setting. These include Osteoporosis Self-Assessment Tool; Osteoporosis Risk Assessment Instrument; Simple Calculated Osteoporosis Risk Estimation; Canadian Association of Radiologists and Osteoporosis Canada calculator; Fracture Risk Assessment Calculator (FRAX); Garvan; and QFracture. These tools vary in the number of risk factors incorporated. We present a detailed analysis of the development, characteristics, validation, performance, advantages and limitations of these tools. The World Health Organization proposes a dual-energy X-ray absorptiometry-BMD T-score ≤ -2.5 as an operational diagnostic threshold for osteoporosis, and many countries have also adopted this cut-off as an intervention threshold in their treatment guidelines. With the introduction of the new fracture assessment calculators, many countries chose to include fracture risk as one of the major criteria to initiate osteoporosis treatment. Of the 52 national guidelines identified in 36 countries, 30 included FRAX derived risk in their intervention threshold and 22 were non-FRAX based. No universal tool or guideline approach will address the needs of all countries worldwide. Osteoporosis screening and management guidelines are best tailored according to the needs and resources of individual counties. While few countries have succeeded in generating valuable epidemiological data on osteoporotic fractures, to validate their risk calculators and base their guidelines, many have yet to find the resources to assess variations and secular trends in fractures, the performance of various calculators, and ultimately adopt the most convenient care pathway algorithms.
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Affiliation(s)
- Ghada El-Hajj Fuleihan
- Calcium Metabolism and Osteoporosis Program, WHO Collaborating Center for Metabolic Bone Disorders, Division of Endocrinology and Metabolism, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon.
| | - Marlene Chakhtoura
- Calcium Metabolism and Osteoporosis Program, WHO Collaborating Center for Metabolic Bone Disorders, Division of Endocrinology and Metabolism, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon
| | - Jane A Cauley
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nariman Chamoun
- Calcium Metabolism and Osteoporosis Program, WHO Collaborating Center for Metabolic Bone Disorders, Division of Endocrinology and Metabolism, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon
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Bolton JM, Morin SN, Majumdar SR, Sareen J, Lix LM, Johansson H, Odén A, McCloskey EV, Kanis JA, Leslie WD. Association of Mental Disorders and Related Medication Use With Risk for Major Osteoporotic Fractures. JAMA Psychiatry 2017; 74:641-648. [PMID: 28423154 PMCID: PMC5539842 DOI: 10.1001/jamapsychiatry.2017.0449] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
IMPORTANCE Osteoporotic fractures are a leading cause of disability, costs, and mortality. FRAX is a tool used to assess fracture risk in the general population. Mental disorders and medications to treat them have been reported to adversely affect bone health, but, to date, they have not been systematically studied in relation to osteoporotic fractures. OBJECTIVE To examine the association of mental disorders and psychotropic medication use with osteoporotic fracture risk in routine clinical practice. DESIGN, SETTING, AND PARTICIPANTS In this population-based cohort study, bone mineral density and risk factors were used to calculate FRAX scores using data from the Manitoba Bone Density Program database of all women and men 40 years of age or older in Manitoba, Canada, referred for a baseline dual-energy x-ray absorptiometry scan from January 1, 1996, to March 28, 2013. Population-based health services data were used to identify primary mental disorders during the 3 prior years, psychotropic medication use during the prior year, and incident fractures. Cox proportional hazards regression models estimated the risk for incident fractures based on mental disorders and use of psychotropic medications. Data analysis was conducted from November 25, 2013, to October 15, 2016. MAIN OUTCOMES AND MEASURES Incident nontraumatic major osteoporotic fractures (MOFs) and hip fractures. RESULTS Of the 68 730 individuals (62 275 women and 6455 men; mean age, 64.2 [11.2] years) in the study, during 485 322 person-years (median, 6.7 years) of observation, 5750 (8.4%) sustained an incident MOF, 1579 (2.3%) sustained an incident hip fracture, and 8998 (13.1%) died. In analyses adjusted for FRAX score, depression was associated with MOF (adjusted hazard ratio [aHR], 1.39; 95% CI, 1.27-1.51; P < .05) and hip fracture (aHR, 1.43; 95% CI, 1.22-1.69; P < .05) before adjustment for medication use, but these associations were not significant after adjustment for medication use. In contrast, the use of selective serotonin reuptake inhibitors (aHR for MOF, 1.43; 95% CI, 1.27-1.60; P < .05; aHR for hip fracture, 1.48; 95% CI, 1.18-1.85; P < .05), antipsychotics (aHR for MOF, 1.43; 95% CI, 1.15-1.77; P < .05; aHR for hip fracture, 2.14; 95% CI, 1.52-3.02; P < .05), and benzodiazepines (aHR for MOF, 1.15; 95% CI, 1.04-1.26; P < .05; aHR for hip fracture, 1.24; 95% CI, 1.05-1.47; P < .05) were each independently associated with significantly increased risk for both MOF and hip fracture. FRAX significantly underestimated the 10-year risk of MOF by 29% and of hip fracture by 51% for those with depression. It also underestimated the 10-year risk of MOF by 36% for use of selective serotonin reuptake inhibitors, by 63% for use of mood stabilizers, by 60% for use of antipsychotics, and by 13% for use of benzodiazepines. FRAX underestimated the 10-year risk of hip fracture by 57% for use of selective serotonin reuptake inhibitors, by 98% for use of mood stabilizers, by 171% for use of antipsychotics, and by 31% for use of benzodiazepines. FRAX correctly estimated fracture risk in people without mental disorders and those not taking psychotropic medications. CONCLUSIONS AND RELEVANCE Mental disorders and medication use were associated with an increased risk for fracture, but in simultaneous analyses, only medication use was independently associated with fracture. Depression and psychotropic medication use are potential risk indicators that are independent of FRAX estimates.
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Affiliation(s)
- James M. Bolton
- Department of Psychiatry, University of Manitoba, Winnipeg, Manitoba, Canada,Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada,Manitoba Centre for Health Policy, Winnipeg, Manitoba, Canada,Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Suzanne N. Morin
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| | - Sumit R. Majumdar
- Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Jitender Sareen
- Department of Psychiatry, University of Manitoba, Winnipeg, Manitoba, Canada,Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada,Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Lisa M. Lix
- Manitoba Centre for Health Policy, Winnipeg, Manitoba, Canada,Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | | | - Anders Odén
- Centre for Metabolic Bone Diseases, Sheffield, England
| | | | - John A. Kanis
- Centre for Metabolic Bone Diseases, Sheffield, England,Institute for Health and Aging, Catholic University of Australia, Melbourne, Australia
| | - William D. Leslie
- Department of Internal Medicine, University of Manitoba, Winnipeg, Manitoba, Canada,Department of Radiology, University of Manitoba, Winnipeg, Manitoba, Canada
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Majumdar SR, Leslie WD, Lix LM, Morin SN, Johansson H, Oden A, McCloskey EV, Kanis JA. Longer Duration of Diabetes Strongly Impacts Fracture Risk Assessment: The Manitoba BMD Cohort. J Clin Endocrinol Metab 2016; 101:4489-4496. [PMID: 27603908 PMCID: PMC5095256 DOI: 10.1210/jc.2016-2569] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
CONTEXT Type 2 diabetes is associated with a higher risk for major osteoporotic fracture (MOF) and hip fracture than predicted by the World Health Organization fracture risk assessment (FRAX) tool. OBJECTIVE The objective of the study was to examine the impact of diabetes duration on fracture risk. METHODS Using a clinical dual-energy x-ray absorptiometry registry linked with the Manitoba administrative databases, we identified all women age 40 years or older with 10 or more years of prior health care coverage undergoing hip dual-energy x-ray absorptiometry measurements (1996-2013). Incident MOF and incident hip fractures were each studied over 7 years. Cox proportional hazards models were adjusted for FRAX (FRAX adjusted) and then FRAX plus comorbidity, falls, osteoporosis therapy, or insulin (fully adjusted). FRAX calibration was assessed comparing observed vs predicted probabilities. RESULTS There were 49 098 women without and 8840 women with diabetes (31.4% >10 y duration; 20.1% 5-10 y; 23.7% <5 y; 24.8% new onset). In FRAX-adjusted analyses, only duration longer than 10 years was associated with a higher risk for MOF (hazard ratio [HR] 1.47, 95% confidence interval [CI] 1.30-1.66), and this was similar in the fully adjusted models (HR 1.34, 95% CI 1.17-1.54). In contrast, a higher risk for hip fracture was seen for all durations in a dose-dependent fashion (eg, FRAX adjusted HR 2.10, 95% CI 1.71-2.59 for duration >10 y vs HR 1.32, 95% CI 1.03-1.69 for new onset). FRAX significantly underestimated the MOF risk (calibration ratio 1.24, 95% CI 1.08-1.39) and hip fracture risk (1.93, 95% CI 1.50-2.35) in those with a diabetes duration longer than 10 years. CONCLUSION Diabetes is a FRAX-independent risk factor for MOF only in women with a long duration of diabetes, but diabetes increases hip fracture risk, regardless of duration. Those with diabetes longer than 10 years are at particularly high risk of fracture, and this elevated risk is currently underestimated by FRAX.
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Affiliation(s)
- Sumit R Majumdar
- Department of Medicine (S.R.M.), University of Alberta, Edmonton, Alberta, Canada T6G 2H7; Departments of Medicine (W.D.L.) and Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2; Department of Medicine (S.N.M.), McGill University, Montréal, Québec, Canada H9X 3V9; Centre for Metabolic Bone Diseases (H.J., A.O., E.V.M., J.A.K.), University of Sheffield Medical School, Sheffield S10 2JF, United Kingdom; and Institute for Health and Ageing (J.A.K.), Catholic University of Australia, 3065 Melbourne, Australia
| | - William D Leslie
- Department of Medicine (S.R.M.), University of Alberta, Edmonton, Alberta, Canada T6G 2H7; Departments of Medicine (W.D.L.) and Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2; Department of Medicine (S.N.M.), McGill University, Montréal, Québec, Canada H9X 3V9; Centre for Metabolic Bone Diseases (H.J., A.O., E.V.M., J.A.K.), University of Sheffield Medical School, Sheffield S10 2JF, United Kingdom; and Institute for Health and Ageing (J.A.K.), Catholic University of Australia, 3065 Melbourne, Australia
| | - Lisa M Lix
- Department of Medicine (S.R.M.), University of Alberta, Edmonton, Alberta, Canada T6G 2H7; Departments of Medicine (W.D.L.) and Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2; Department of Medicine (S.N.M.), McGill University, Montréal, Québec, Canada H9X 3V9; Centre for Metabolic Bone Diseases (H.J., A.O., E.V.M., J.A.K.), University of Sheffield Medical School, Sheffield S10 2JF, United Kingdom; and Institute for Health and Ageing (J.A.K.), Catholic University of Australia, 3065 Melbourne, Australia
| | - Suzanne N Morin
- Department of Medicine (S.R.M.), University of Alberta, Edmonton, Alberta, Canada T6G 2H7; Departments of Medicine (W.D.L.) and Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2; Department of Medicine (S.N.M.), McGill University, Montréal, Québec, Canada H9X 3V9; Centre for Metabolic Bone Diseases (H.J., A.O., E.V.M., J.A.K.), University of Sheffield Medical School, Sheffield S10 2JF, United Kingdom; and Institute for Health and Ageing (J.A.K.), Catholic University of Australia, 3065 Melbourne, Australia
| | - Helena Johansson
- Department of Medicine (S.R.M.), University of Alberta, Edmonton, Alberta, Canada T6G 2H7; Departments of Medicine (W.D.L.) and Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2; Department of Medicine (S.N.M.), McGill University, Montréal, Québec, Canada H9X 3V9; Centre for Metabolic Bone Diseases (H.J., A.O., E.V.M., J.A.K.), University of Sheffield Medical School, Sheffield S10 2JF, United Kingdom; and Institute for Health and Ageing (J.A.K.), Catholic University of Australia, 3065 Melbourne, Australia
| | - Anders Oden
- Department of Medicine (S.R.M.), University of Alberta, Edmonton, Alberta, Canada T6G 2H7; Departments of Medicine (W.D.L.) and Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2; Department of Medicine (S.N.M.), McGill University, Montréal, Québec, Canada H9X 3V9; Centre for Metabolic Bone Diseases (H.J., A.O., E.V.M., J.A.K.), University of Sheffield Medical School, Sheffield S10 2JF, United Kingdom; and Institute for Health and Ageing (J.A.K.), Catholic University of Australia, 3065 Melbourne, Australia
| | - Eugene V McCloskey
- Department of Medicine (S.R.M.), University of Alberta, Edmonton, Alberta, Canada T6G 2H7; Departments of Medicine (W.D.L.) and Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2; Department of Medicine (S.N.M.), McGill University, Montréal, Québec, Canada H9X 3V9; Centre for Metabolic Bone Diseases (H.J., A.O., E.V.M., J.A.K.), University of Sheffield Medical School, Sheffield S10 2JF, United Kingdom; and Institute for Health and Ageing (J.A.K.), Catholic University of Australia, 3065 Melbourne, Australia
| | - John A Kanis
- Department of Medicine (S.R.M.), University of Alberta, Edmonton, Alberta, Canada T6G 2H7; Departments of Medicine (W.D.L.) and Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2; Department of Medicine (S.N.M.), McGill University, Montréal, Québec, Canada H9X 3V9; Centre for Metabolic Bone Diseases (H.J., A.O., E.V.M., J.A.K.), University of Sheffield Medical School, Sheffield S10 2JF, United Kingdom; and Institute for Health and Ageing (J.A.K.), Catholic University of Australia, 3065 Melbourne, Australia
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Klop C, Welsing PMJ, Leufkens HGM, Elders PJM, Overbeek JA, van den Bergh JP, Bijlsma JWJ, de Vries F. The Epidemiology of Hip and Major Osteoporotic Fractures in a Dutch Population of Community-Dwelling Elderly: Implications for the Dutch FRAX® Algorithm. PLoS One 2015; 10:e0143800. [PMID: 26633011 PMCID: PMC4669166 DOI: 10.1371/journal.pone.0143800] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2015] [Accepted: 11/10/2015] [Indexed: 11/18/2022] Open
Abstract
Background Incidence rates of non-hip major osteoporotic fractures (MOF) remain poorly characterized in the Netherlands. The Dutch FRAX® algorithm, which predicts 10-year probabilities of hip fracture and MOF (first of hip, humerus, forearm, clinical vertebral), therefore incorporates imputed MOF rates. Swedish incidence rate ratios for hip fracture to MOF (Malmo 1987–1996) were used to perform this imputation. However, equality of these ratios between countries is uncertain and recent evidence is scarce. Aims were to estimate incidence rates of hip fracture and MOF and to compare observed MOF rates to those predicted by the imputation method for the Netherlands. Methods Using hospitalisation and general practitioner records from the Dutch PHARMO Database Network (2002–2011) we calculated age-and-sex-specific and age-standardized incidence rates (IRs) of hip and other MOFs (humerus, forearm, clinical vertebral) and as used in FRAX®. Observed MOF rates were compared to those predicted among community-dwelling individuals ≥50 years by the standardized incidence ratio (SIR; 95% CI). Results Age-standardized IRs (per 10,000 person-years) of MOF among men and women ≥50 years were 25.9 and 77.0, respectively. These numbers were 9.3 and 24.0 for hip fracture. Among women 55–84 years, observed MOF rates were significantly higher than predicted (SIR ranged between 1.12–1.50, depending on age). In men, the imputation method performed reasonable. Conclusion Observed MOF incidence was higher than predicted for community-dwelling women over a wide age-range, while it agreed reasonable for men. As miscalibration may influence treatment decisions, there is a need for confirmation of results in another data source. Until then, the Dutch FRAX® output should be interpreted with caution.
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Affiliation(s)
- Corinne Klop
- Utrecht Institute for Pharmaceutical Sciences, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, Netherlands
| | - Paco M. J. Welsing
- Department of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, Netherlands
| | - Hubert G. M. Leufkens
- Utrecht Institute for Pharmaceutical Sciences, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, Netherlands
| | - Petra J. M. Elders
- Department of General Practice and Elderly Care, VU University Medical Centre, Amsterdam, Netherlands
| | | | - Joop P. van den Bergh
- Department of Internal Medicine, Viecuri Medical Centre, Venlo, Netherlands
- Department of Internal Medicine, Maastricht University Medical Centre+, Maastricht, Netherlands
- Biomedical Research Institute, University Hasselt, Hasselt, Belgium
| | - Johannes W. J. Bijlsma
- Department of Rheumatology and Clinical Immunology, University Medical Center, Utrecht, Netherlands
| | - Frank de Vries
- Utrecht Institute for Pharmaceutical Sciences, Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, Netherlands
- Department of Clinical Pharmacy and Toxicology, Maastricht University Medical Centre+, Maastricht, Netherlands
- MRC Lifecourse Epidemiology Unit, Southampton General Hospital, Southampton, United Kingdom
- * E-mail:
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Lam A, Leslie WD, Lix LM, Yogendran M, Morin SN, Majumdar SR. Major osteoporotic to hip fracture ratios in canadian men and women with Swedish comparisons: a population-based analysis. J Bone Miner Res 2014; 29:1067-73. [PMID: 24243719 DOI: 10.1002/jbmr.2146] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2013] [Revised: 10/21/2013] [Accepted: 11/12/2013] [Indexed: 12/17/2022]
Abstract
Fracture Risk Assessment (FRAX) tools are calibrated from country-specific fracture epidemiology. Although hip fracture data are usually available, data on non-hip fractures for most countries are often lacking. In such cases, rates are often estimated by assuming similar non-hip to hip fracture ratios from historical (1987 to 1996) Swedish data. Evidence that countries share similar fracture ratios is limited. Using data from Manitoba, Canada (2000 to 2007, population 1.2 million), we identified 21,850 incident major osteoporotic fractures (MOF) in men and women aged >50 years. Population-based age- and sex-specific ratios of clinical vertebral, forearm, and humerus fractures to hip fractures were calculated, along with odds ratios (ORs) and 95% confidence intervals (CIs). All ratios showed decreasing trends with increasing age for both men and women. Men and women showed similar vertebral/hip fracture ratios (all p > 0.1, with ORs 0.86 to 1.25). Forearm/hip and humerus/hip fracture ratios were significantly lower among men than women (forearm/hip ratio: p < 0.01 for all age groups, with ORs 0.29 to 0.53; humerus/hip ratio: p < 0.05 for all age groups [except 80 to 84 years] with ORs 0.46 to 0.86). Ratios for any MOF/hip fracture were also significantly lower among men than women in all but two subgroups (p < 0.05 for all age groups [except 80 to 84 and 90+ years] with ORs 0.48 to 0.87). Swedish vertebral/hip fracture ratios were similar to the Canadian fracture ratios (within 7%) but significantly lower for other sites (men and women: 46% and 35% lower for forearm/hip ratios, 19% and 15% lower for humerus/hip ratios, and 19% and 23% lower for any MOF/hip ratios). These differences have implications for updating and calibrating FRAX tools, fracture risk estimation, and intervention rates. Moreover, wherever possible, it is important that countries try to collect accurate non-hip fracture data.
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Affiliation(s)
- Anna Lam
- University of Manitoba, Winnipeg, Canada
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Leslie WD, Brennan SL, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA. Direct comparison of eight national FRAX® tools for fracture prediction and treatment qualification in Canadian women. Arch Osteoporos 2013; 8:145. [PMID: 23929269 DOI: 10.1007/s11657-013-0145-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2013] [Accepted: 07/01/2013] [Indexed: 02/03/2023]
Abstract
SUMMARY We compared the calibration of FRAX tools from Canada, the US (white), UK, Sweden, France, Australia, New Zealand, and China when used to assess fracture risk in 36,730 Canadian women. Our data underscores the importance of applying country-specific FRAX tools that are based upon high-quality national fracture epidemiology. PURPOSE A FRAX® model for Canada was constructed for prediction of hip fracture and major osteoporotic fracture (MOF) using national hip fracture and mortality data. We examined the calibration of this model in Canadian women and compared it with seven other FRAX tools. METHODS In women aged ≥50 years with baseline bone mineral density (BMD) measures identified from the Manitoba Bone Density Program, Canada (n = 36,730), 10-year fracture probabilities were calculated with and without BMD using selected country-specific FRAX tools. FRAX risk estimates were compared with observed fractures ≤10 years (506 hip, 2,380 MOF). Ten-year fracture risk was compared with predicted probabilities, and proportions exceeding specific treatment thresholds contrasted. RESULTS For hip fracture prediction, good calibration was observed for FRAX Canada and most other country-specific FRAX tools, excepting Sweden (risk overestimated) and China (risk underestimated). For MOF prediction, greater between-country differences were seen; FRAX Sweden and FRAX China showed the largest over- and underestimation in this Canadian population. Relative to treatment qualification based upon FRAX Canada, treatment of high-hip fracture probability (≥3%) was greater by FRAX Sweden (ratio 1.41 without and 1.55 with BMD), and markedly less by FRAX China (ratio 0.09 without and 0.11 with BMD). Greater between-country differences were observed for treatment of high MOF (≥20%); FRAX Sweden again greatly increased (ratio 1.76 without and 1.83 with BMD), and FRAX China severely reduced treatment qualification (ratio 0.00 without and 0.01 with BMD). CONCLUSIONS The use of country-specific FRAX tools, accurately calibrated to the target population, is essential. Relatively small calibration differences can have large effects on high-risk categorization and treatment qualification.
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Affiliation(s)
- W D Leslie
- Department of Medicine (C5121), University of Manitoba, 409 Tache Avenue, St Boniface General Hospital, Winnipeg R2H 2A6, Canada.
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Stepan JJ, Vaculik J, Pavelka K, Zofka J, Johansson H, Kanis JA. Hip fracture incidence from 1981 to 2009 in the Czech Republic as a basis of the country-specific FRAX model. Calcif Tissue Int 2012; 90:365-72. [PMID: 22399225 DOI: 10.1007/s00223-012-9582-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2011] [Accepted: 02/10/2012] [Indexed: 10/28/2022]
Abstract
The aim of this study was to calculate rates of hospitalization for hip fracture and the incidence of hip fractures in the Czech Republic over a period of 29 years. A second aim was to use the most recent data to populate a FRAX(®) model for the assessment of fracture probability in individual patients. Data on hospitalizations for hip fracture (1981-2009) and number of women and men with hip fractures (2000-2009) were obtained, and incidences were computed for the entire population ≥50 years of age. Incidence of hospitalization for hip fracture in the Czech population aged ≥50 years increased progressively by calendar year. Age-standardized incidence of hip fractures increased to 2004 but leveled off thereafter and decreased after 2005. Data for hip fracture risk in 2008 and 2009 and the death hazard were used to populate a Czech-specific FRAX model for the computation of 10-year fracture probability. The customized FRAX model, using the verified epidemiological data, will be used to identify patients at increased fracture risk.
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Affiliation(s)
- Jan J Stepan
- Institute of Rheumatology, Prague, and Department of Rheumatology, Charles University, Prague, Czech Republic.
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Abstract
Osteoporosis-related fractures (low-trauma, fragility fractures) are associated with significant morbidity, mortality, and health care expenditure worldwide. In the absence of a defining fracture, the diagnosis of osteoporosis is based on the World Health Organization's T-score criteria using central dual-energy x-ray absorptiometry (DXA). Paradoxically, the majority of those patients who will sustain a low-trauma fracture do not meet the T-score definition of osteoporosis. Conversely, younger individuals with bone density in the osteoporotic range but no other risk factors have relatively low fracture rates and yet are frequently considered candidates for osteoporosis therapies. The limited accuracy of bone density testing alone to predict fractures has led to the development of a variety of fracture assessment tools that utilize the combination of bone density and clinical risk factors to improve the prediction of low-trauma fractures. These fracture assessment tools quantitatively predict the 10-year fracture probability of hip and major osteoporosis-related fractures, and can be used to define cost-effective intervention strategies for primary and secondary fracture prevention.
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Affiliation(s)
- Sanford Baim
- Division of Endocrinology, Miller School of Medicine, University of Miami, 1400 NW 10th Avenue, Dominion Towers, Suite 809, Miami, FL 33136, USA.
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Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA. A comparative study of using non-hip bone density inputs with FRAX®. Osteoporos Int 2012; 23:853-60. [PMID: 22008881 DOI: 10.1007/s00198-011-1814-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2011] [Accepted: 09/22/2011] [Indexed: 10/16/2022]
Abstract
UNLABELLED Use of lumbar spine T-score or minimum T-score as a bone mineral density (BMD) input to the FRAX® algorithm led to miscalibration compared with the recommended femoral neck input. Use of a weighted mean between the lumbar spine and femoral neck T-scores was found to provide an arithmetically equivalent result to a previously described offset adjustment. INTRODUCTION FRAX assumes that the BMD input, when used in the calculation, is from the femoral neck. Use of other BMD inputs is not recommended, but there are no studies describing how this affects the performance of FRAX. METHODS Ten-year probabilities of a major osteoporotic fracture were calculated with different BMD inputs for 20,477 women and men aged 50 years and older from Manitoba, Canada. FRAX probability calculated with femoral neck BMD was designated the reference method. We also derived FRAX probabilities where the BMD input was based upon the lumbar spine T-score, minimum T-score (lumbar spine or femoral neck), weighted mean T-score (lumbar spine or femoral neck), or used an adjustment for the spine-hip T-score difference (offset). Fracture outcomes were assessed using a population-based administrative data repository. RESULTS All FRAX models showed good risk stratification with minimal differences. There was no consistent improvement in FRAX performance when lumbar spine or minimum T-score were used as inputs, but calibration was adversely affected due to higher mean fracture probabilities compared with the femoral neck. The weighted mean T-score was found to be equivalent to the spine-hip T-score offset adjustment, and both slightly improved risk classification without a change in calibration. CONCLUSIONS The choice of BMD input to the FRAX model has a large effect on performance. The lumbar spine T-score or minimum T-score should not be used as inputs to the FRAX algorithm. Use of a weighted mean between the lumbar spine and femoral neck T-scores slightly improves risk classification.
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Affiliation(s)
- W D Leslie
- University of Manitoba, Winnipeg, Canada.
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