Comparison of treatment strategies and thresholds for optimizing fracture prevention in Canada: a simulation analysis



This comparison of osteoporosis treatment strategies and intervention thresholds highlights tradeoffs in terms of number of individuals qualifying for treatment and estimated fractures prevented.


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?”


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.


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.


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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  1. 1.

    Compston JE, McClung MR, Leslie WD (2019) Osteoporosis. Lancet 393(10169):364–376

    CAS  PubMed  Google Scholar 

  2. 2.

    Brown JP, Josse RG (2002) Scientific Advisory Council of the Osteoporosis Society of C. 2002 clinical practice guidelines for the diagnosis and management of osteoporosis in Canada. CMAJ. 167(10 Suppl):S1–S34

    PubMed  PubMed Central  Google Scholar 

  3. 3.

    Papaioannou A, Morin S, Cheung AM, Atkinson S, Brown JP, Feldman S, Hanley DA, Hodsman A, Jamal SA, Kaiser SM, Kvern B, Siminoski K, Leslie WD, Scientific Advisory Council of Osteoporosis Canada (2010) 2010 clinical practice guidelines for the diagnosis and management of osteoporosis in Canada: summary. CMAJ. 182(17):1864–1873

    PubMed  PubMed Central  Google Scholar 

  4. 4.

    Kanis JA, Oden A, Johnell O, Johansson H, De Laet C, Brown J et al (2007) The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women. Osteoporos Int 18(8):1033–1046

    CAS  PubMed  Google Scholar 

  5. 5.

    Kanis JA (2007) Assessment of osteoporosis at the primary health-care level. Technical Report. Accessible at Published by the University of Sheffield

  6. 6.

    Siminoski K, Leslie WD, Frame H, Hodsman A, Josse RG, Khan A, Lentle BC, Lévesque J, Lyons DJ, Tarulli G, Brown JP, Canadian Association of Radiologists (2005) Recommendations for bone mineral density reporting in Canada. Can Assoc Radiol J 56(3):178–188

    PubMed  Google Scholar 

  7. 7.

    Tosteson AN, Melton LJ 3rd, Dawson-Hughes B, Baim S, Favus MJ, Khosla S et al (2008) Cost-effective osteoporosis treatment thresholds: the United States perspective. Osteoporos Int 19(4):437–447

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Kanis JA, Harvey NC, Cooper C, Johansson H, Oden A, McCloskey EV et al (2016) A systematic review of intervention thresholds based on FRAX : a report prepared for the National Osteoporosis Guideline Group and the International Osteoporosis Foundation. Arch Osteoporos 11(1):25

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    Kanis JA, McCloskey EV, Harvey NC, Johansson H, Leslie WD (2015) Intervention thresholds and the diagnosis of osteoporosis. J Bone Miner Res 30(10):1747–1753

    PubMed  Google Scholar 

  10. 10.

    Johansson H, Azizieh F, Al Ali N, Alessa T, Harvey NC, McCloskey E et al (2017) FRAX- vs. T-score-based intervention thresholds for osteoporosis. Osteoporos Int 28:3099–3105

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    McCloskey E, Kanis JA, Johansson H, Harvey N, Oden A, Cooper A et al (2015) FRAX-based assessment and intervention thresholds--an exploration of thresholds in women aged 50 years and older in the UK. Osteoporos Int 26(8):2091–2099

    CAS  PubMed  Google Scholar 

  12. 12.

    Kanis JA, McCloskey EV, Johansson H, Strom O, Borgstrom F, Oden A, National Osteoporosis Guideline Group (2008) Case finding for the management of osteoporosis with FRAX--assessment and intervention thresholds for the UK. Osteoporos Int 19(10):1395–1408

    CAS  PubMed  Google Scholar 

  13. 13.

    Kanis JA, Borgstrom F, Zethraeus N, Johnell O, Oden A, Jonsson B (2005) Intervention thresholds for osteoporosis in the UK. Bone. 36(1):22–32

    PubMed  Google Scholar 

  14. 14.

    Kanis JA, Oden A, Johnell O, Jonsson B, de Laet C, Dawson A (2001) The burden of osteoporotic fractures: a method for setting intervention thresholds. Osteoporos Int 12(5):417–427

    CAS  PubMed  Google Scholar 

  15. 15.

    National Institute for Health and Care Excellence (NICE) (2017) Bisphosphonates for treating osteoporosis. Technical appraisal guidance TA464

  16. 16.

    Leslie WD, Metge C (2003) Establishing a regional bone density program: lessons from the Manitoba experience. J Clin Densitom 6(3):275–282

    PubMed  Google Scholar 

  17. 17.

    Leslie WD, Caetano PA, Macwilliam LR, Finlayson GS (2005) Construction and validation of a population-based bone densitometry database. J Clin Densitom 8(1):25–30

    PubMed  Google Scholar 

  18. 18.

    Looker AC, Wahner HW, Dunn WL, Calvo MS, Harris TB, Heyse SP et al (1998) Updated data on proximal femur bone mineral levels of US adults. Osteoporos Int 8(5):468–489

    CAS  PubMed  Google Scholar 

  19. 19.

    Kanis JA, Oden A, Johansson H, Borgstrom F, Strom O, McCloskey E (2009) FRAX and its applications to clinical practice. Bone. 44(5):734–743

    PubMed  Google Scholar 

  20. 20.

    Leslie WD, Lix LM, Langsetmo L, Berger C, Goltzman D, Hanley DA, Adachi JD, Johansson H, Oden A, McCloskey E, Kanis JA (2011) Construction of a FRAX(R) model for the assessment of fracture probability in Canada and implications for treatment. Osteoporos Int 22(3):817–827

    CAS  PubMed  Google Scholar 

  21. 21.

    Bisson EJ, Finlayson ML, Ekuma O, Marrie RA, Leslie WD (2019) Accuracy of FRAX(R) in people with multiple sclerosis. J Bone Miner Res 34:1095–1100

    CAS  PubMed  Google Scholar 

  22. 22.

    Leslie WD, Morin SN, Lix LM, Niraula S, McCloskey EV, Johansson H, Harvey NC, Kanis JA (2019) Performance of FRAX in women with breast cancer initiating aromatase inhibitor therapy: a registry-based cohort study. J Bone Miner Res 34(8):1428–1435

    CAS  PubMed  Google Scholar 

  23. 23.

    Peschken CA, Hitchon CA, Garland A, Bernstein CN, Chen H, Fransoo R et al (2016) A population-based study of intensive care unit admissions in rheumatoid arthritis. J Rheumatol 43(1):26–33

    PubMed  Google Scholar 

  24. 24.

    Yang S, Leslie WD, Yan L, Walld R, Roos LL, Morin SN, Majumdar SR, Lix LM (2016) Objectively verified parental hip fracture is an independent risk factor for fracture: a linkage analysis of 478,792 Parents and 261,705 Offspring. J Bone Miner Res 31(9):1753–1759

    PubMed  Google Scholar 

  25. 25.

    Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA et al (2010) Independent clinical validation of a Canadian FRAX tool: fracture prediction and model calibration. J Bone Miner Res 25(11):2350–2358

    PubMed  Google Scholar 

  26. 26.

    Fraser LA, Langsetmo L, Berger C, Ioannidis G, Goltzman D, Adachi JD, Papaioannou A, Josse R, Kovacs CS, Olszynski WP, Towheed T, Hanley DA, Kaiser SM, Prior J, Jamal S, Kreiger N, Brown JP, Johansson H, Oden A, McCloskey E, Kanis JA, Leslie WD, CaMos Research Group (2011) Fracture prediction and calibration of a Canadian FRAX(R) tool: a population-based report from CaMos. Osteoporos Int 22(3):829–837

    PubMed  Google Scholar 

  27. 27.

    Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA, Manitoba Bone Density Program (2012) Does osteoporosis therapy invalidate FRAX for fracture prediction? J Bone Miner Res 27(6):1243–1251

    CAS  PubMed  Google Scholar 

  28. 28.

    Lix LM, Azimaee M, Osman BA, Caetano P, Morin S, Metge C et al (2012) Osteoporosis-related fracture case definitions for population-based administrative data. BMC Public Health 12:301

    PubMed  PubMed Central  Google Scholar 

  29. 29.

    Epp R, Alhrbi M, Ward L, Leslie WD (2018) Radiological validation of fracture definitions from administrative data. J Bone Miner Res 33(Supp 1):S275

    Google Scholar 

  30. 30.

    Compston J, Bowring C, Cooper A, Cooper C, Davies C, Francis R, Kanis JA, Marsh D, McCloskey E, Reid DM, Selby P, National Osteoporosis Guideline Group (2013) Diagnosis and management of osteoporosis in postmenopausal women and older men in the UK: National Osteoporosis Guideline Group (NOGG) update 2013. Maturitas. 75(4):392–396

    CAS  PubMed  Google Scholar 

  31. 31.

    Chakhtoura M, Leslie WD, McClung M, Cheung AM, Fuleihan GE (2017) The FRAX-based Lebanese osteoporosis treatment guidelines: rationale for a hybrid model. Osteoporos Int 28(1):127–137

    CAS  PubMed  Google Scholar 

  32. 32.

    Cosman F, de Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S et al (2014) Clinician's guide to prevention and treatment of osteoporosis. Osteoporos Int 25(10):2359–2381

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Mackey DC, Black DM, Bauer DC, McCloskey EV, Eastell R, Mesenbrink P, Thompson JR, Cummings SR (2011) Effects of antiresorptive treatment on nonvertebral fracture outcomes. J Bone Miner Res 26(10):2411–2418

    CAS  PubMed  Google Scholar 

  34. 34.

    Abrahamsen B, Eiken P, Prieto-Alhambra D, Eastell R (2016) Risk of hip, subtrochanteric, and femoral shaft fractures among mid and long term users of alendronate: nationwide cohort and nested case-control study. BMJ. 353:i3365

    PubMed  PubMed Central  Google Scholar 

  35. 35.

    Kanis JA, Johansson H, Oden A, McCloskey EV (2009) Bazedoxifene reduces vertebral and clinical fractures in postmenopausal women at high risk assessed with FRAX. Bone. 44(6):1049–1054

    CAS  PubMed  Google Scholar 

  36. 36.

    McCloskey EV, Johansson H, Oden A, Vasireddy S, Kayan K, Pande K, Jalava T, Kanis JA (2009) Ten-year fracture probability identifies women who will benefit from clodronate therapy--additional results from a double-blind, placebo-controlled randomised study. Osteoporos Int 20(5):811–817

    CAS  PubMed  Google Scholar 

  37. 37.

    McCloskey EV, Johansson H, Oden A, Austin M, Siris E, Wang A et al (2012) Denosumab reduces the risk of osteoporotic fractures in postmenopausal women, particularly in those with moderate to high fracture risk as assessed with FRAX. J Bone Miner Res 27(7):1480–1486

    CAS  PubMed  Google Scholar 

  38. 38.

    Cosman F, Crittenden DB, Ferrari S, Lewiecki EM, Jaller-Raad J, Zerbini C, Milmont CE, Meisner PD, Libanati C, Grauer A (2018) Romosozumab FRAME Study: a post hoc analysis of the role of regional background fracture risk on nonvertebral fracture outcome. J Bone Miner Res 33(8):1407–1416

    CAS  PubMed  Google Scholar 

  39. 39.

    McCloskey E, Johansson H, Harvey NC, Shepstone L, Lenaghan E, Fordham R, Harvey I, Howe A, Cooper C, Clarke S, Gittoes N, Heawood A, Holland R, Marshall T, O'Neill TW, Peters TJ, Redmond N, Torgerson D, Kanis JA, the SCOOP Study Team (2018) Management of patients with high baseline hip fracture risk by FRAX reduces hip fractures-a post hoc analysis of the SCOOP Study. J Bone Miner Res 33:1020–1026

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Kanis JA, Johansson H, Oden A, McCloskey EV (2010) A meta-analysis of the efficacy of raloxifene on all clinical and vertebral fractures and its dependency on FRAX. Bone. 47(4):729–735

    CAS  PubMed  Google Scholar 

  41. 41.

    Donaldson MG, Palermo L, Ensrud KE, Hochberg MC, Schousboe JT, Cummings SR (2012) Effect of alendronate for reducing fracture by FRAX score and femoral neck bone mineral density: the Fracture Intervention Trial. J Bone Miner Res 27(8):1804–1810

    CAS  PubMed  Google Scholar 

  42. 42.

    McCloskey EV, Johansson H, Oden A, Harvey NC, Jiang H, Modin S et al (2017) The Effect of Abaloparatide-SC on fracture risk is independent of baseline FRAX fracture probability: a post hoc analysis of the ACTIVE Study. J Bone Miner Res 32(8):1625–1631

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Harvey NC, Kanis JA, Oden A, Nakamura T, Shiraki M, Sugimoto T et al (2015) Efficacy of weekly teriparatide does not vary by baseline fracture probability calculated using FRAX. Osteoporos Int 26(9):2347–2353

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Harvey NC, Kanis JA, Oden A, Burge RT, Mitlak BH, Johansson H et al (2015) FRAX and the effect of teriparatide on vertebral and non-vertebral fracture. Osteoporos Int 26(11):2677–2684

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Kanis JA, Johansson H, Oden A, McCloskey EV (2011) A meta-analysis of the effect of strontium ranelate on the risk of vertebral and non-vertebral fracture in postmenopausal osteoporosis and the interaction with FRAX((R)). Osteoporos Int 22(8):2347–2355

    CAS  PubMed  Google Scholar 

  46. 46.

    Shepstone L, Lenaghan E, Cooper C, Clarke S, Fong-Soe-Khioe R, Fordham R, Gittoes N, Harvey I, Harvey N, Heawood A, Holland R, Howe A, Kanis J, Marshall T, O'Neill T, Peters T, Redmond N, Torgerson D, Turner D, McCloskey E, SCOOP Study Team (2018) Screening in the community to reduce fractures in older women (SCOOP): a randomised controlled trial. Lancet. 391(10122):741–747

    PubMed  Google Scholar 

  47. 47.

    Blagus R, Goeman JJ (2018) What (not) to expect when classifying rare events. Brief Bioinform 19(2):341–349

    PubMed  Google Scholar 

  48. 48.

    Crandall CJ, Schousboe JT, Morin SN, Lix LM, Leslie W (2019) Performance of FRAX and FRAX-based treatment thresholds in women aged 40 years and older: The Manitoba BMD Registry. J Bone Miner Res 34(8):1419–1427

    PubMed  Google Scholar 

  49. 49.

    Crandall CJ, Larson J, Manson JE, Cauley JA, LaCroix AZ, Wactawski-Wende J, Datta M, Sattari M, Schousboe JT, Leslie WD, Ensrud KE (2019) A comparison of US and Canadian osteoporosis screening and treatment strategies in postmenopausal women. J Bone Miner Res 34(4):607–615

    PubMed  PubMed Central  Google Scholar 

  50. 50.

    Crandall CJ, Larson J, LaCroix A, Cauley JA, LeBoff MS, Li W et al (2019) Predicting fracture risk in younger postmenopausal women: comparison of the Garvan and FRAX risk calculators in the Women's Health Initiative Study. J Gen Intern Med 34(2):235–242

  51. 51.

    Leslie WD, Morin SN, Lix LM, Martineau P, Bryanton M, McCloskey EV et al (2019) Fracture prediction from self-reported falls in routine clinical practice: a registry-based cohort study. Osteoporos Int 30:2195–2203

    CAS  PubMed  Google Scholar 

  52. 52.

    Harvey NC, Oden A, Orwoll E, Lapidus J, Kwok T, Karlsson MK et al (2018) Falls predict fractures independently of FRAX probability: a meta-analysis of the osteoporotic fractures in Men (MrOS) Study. J Bone Miner Res 33(3):510–516

  53. 53.

    McCloskey EV, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H et al (2016) A meta-analysis of trabecular bone score in fracture risk prediction and its relationship to FRAX. J Bone Miner Res 31(5):940–948

    PubMed  Google Scholar 

  54. 54.

    Leslie WD, Lix LM (2011) Manitoba bone density P. Effects of FRAX((R)) model calibration on intervention rates: a simulation study. J Clin Densitom 14(3):272–278

    PubMed  Google Scholar 

  55. 55.

    Berry SD, Kiel DP, Donaldson MG, Cummings SR, Kanis JA, Johansson H, Samelson EJ (2010) Application of the National Osteoporosis Foundation Guidelines to postmenopausal women and men: the Framingham Osteoporosis Study. Osteoporos Int 21(1):53–60

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2008) Development of prognostic nomograms for individualizing 5-year and 10-year fracture risks. Osteoporos Int 19(10):1431–1444

    CAS  PubMed  Google Scholar 

  57. 57.

    Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2007) Development of a nomogram for individualizing hip fracture risk in men and women. Osteoporos Int 18(8):1109–1117

    CAS  PubMed  Google Scholar 

  58. 58.

    Hippisley-Cox J, Coupland C (2011) Validation of QFracture compared with FRAX: analysis prepared for NICE 2011

  59. 59.

    Hippisley-Cox J, Coupland C (2012) Derivation and validation of updated QFracture algorithm to predict risk of osteoporotic fracture in primary care in the United Kingdom: prospective open cohort study. BMJ. 344:e3427

    PubMed  Google Scholar 

  60. 60.

    Kahneman D (2011) Thinking, fast and slow. Macmillan

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The authors thank the Osteoporosis Canada Guidelines Update Fracture Risk Assessment Working Group for guidance as this work evolved. The authors acknowledge the Manitoba Centre for Health Policy for use of data contained in the Population Health Research Data Repository (HIPC 2016/2017-29).


The results and conclusions are those of the authors and no official endorsement by the Manitoba Centre for Health Policy, Manitoba Health, Seniors and Active Living, or other data providers is intended or should be inferred. This article has been reviewed and approved by the members of the Manitoba Bone Density Program Committee.


No funding was reserved for this research. SNM is chercheur-boursier des Fonds de Recherche du Québec en Santé. LML is supported by a Tier I Canada Research Chair.

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Conception, design, analysis, drafting the article (WDL), interpretation of data (All Authors); critically revising the article for important intellectual content (All Authors); final approval of the version to be published (All Authors); and agreement to be accountable for all aspects of the work (All Authors). WDL had full access to all the data in the study and takes the responsibility for the integrity of the data and the accuracy of the data analysis.

Corresponding author

Correspondence to William D. Leslie.

Ethics declarations

The study was approved by the Health Research Ethics Board for the University of Manitoba.

Conflict of interest

William Leslie and Lisa Lix: No conflicts of interest.

Suzanne Morin: Nothing to declare for the context of this paper, but has received research grants: Amgen.

Neil Binkley: Nothing to declare for the context of this paper, but has received research support (paid to institution) from Radius, RTI Health Solutions, GE Healthcare; consultant/advisory board fees from Amgen.

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Leslie, W.D., Morin, S.N., Lix, L.M. et al. Comparison of treatment strategies and thresholds for optimizing fracture prevention in Canada: a simulation analysis. Arch Osteoporos 15, 4 (2020).

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  • Osteoporosis
  • Fractures
  • Clinical practice guidelines
  • Dual-energy x-ray absorptiometry
  • FRAX