Osteoporosis International

, Volume 20, Issue 10, pp 1767–1774 | Cite as

Prediction of hip and other osteoporotic fractures from hip geometry in a large clinical cohort

  • W. D. Leslie
  • P. S. Pahlavan
  • J. F. Tsang
  • L. M. Lix
  • for the Manitoba Bone Density Program
Original Article

Abstract

Summary

Incident hip fractures and non-hip osteoporotic fractures were studied in 30,953 women during mean 3.7 years of observation. Hip axis length (HAL) and strength index (SI) made a small but statistically significant contribution to hip fracture prediction that was independent of age and hip bone density.

Introduction

It is uncertain whether bone geometric measures improve fracture prediction independent of conventional areal bone mineral density (BMD).

Methods

Women aged ≥50 years with hip dual-energy x-ray absorptiometry were identified from the regionally based database in the Province of Manitoba, Canada. Scans were reprocessed to derive parameters of hip bone geometry. Incident hip fractures (N = 270) and non-hip osteoporotic fractures (N = 1,347) were identified during mean 3.7 years of observation.

Results

HAL was greater in both hip and non-hip fracture cases than in non-fracture cases, whereas cross-sectional moment of inertia, cross-sectional area, and femoral SI were all significantly less. After adjustment for total hip BMD, HAL [hazard ratio (HR) 1.22 per SD increase, 95% CI 1.07–1.38] and SI (HR 1.21 per SD decrease, 95% CI 1.07–1.37) were independent predictors of hip fractures but not of non-hip fractures. When both HAL and SI were added to a model containing age and total hip BMD, there was a small improvement in hip fracture prediction (ROC area under the curve 0.832 ± 0.013 vs 0.823 ± 0.013; P = 0.001).

Conclusions

HAL and SI made a small but statistically significant contribution to hip fracture prediction that was independent of age and BMD measurement.

Keywords

Bone geometry Bone mineral density Dual energy X-ray absorptiometry Fractures Hip axis length Hip structure analysis 

Notes

Acknowledgments

We are indebted to Manitoba Health and Healthy Living for providing data (HIPC no. 2003/2004-26). The results and conclusions are those of the authors, and no official endorsement by Manitoba Health and Healthy Living is intended or should be inferred. This article has been reviewed and approved by the members of the Manitoba Bone Density Program Committee. This study is funded in part by an unrestricted educational grant from the CHAR/GE Healthcare Development Awards Programme.

Disclosures

William D. Leslie:

Honoraria or speaker’s fees: Merck Frosst Canada, Sanofi-Aventis, Genzyme Canada Ltd. Research support and unrestricted educational grants: Merck Frosst Canada, Procter & Gamble Pharmaceuticals, Amgen Canada, Genzyme Canada Ltd.

Payam Pahlavan, James F. Tsang, Lisa M. Lix:

No conflicts.

References

  1. 1.
    Tenenhouse A, Joseph L, Kreiger N et al (2000) Estimation of the prevalence of low bone density in Canadian women and men using a population-specific DXA reference standard: the Canadian Multicentre Osteoporosis Study (CaMos). Osteoporos Int 11:897–904PubMedCrossRefGoogle Scholar
  2. 2.
    Papadimitropoulos EA, Coyte PC, Josse RG et al (1997) Current and projected rates of hip fracture in Canada. CMAJ 157:1357–1363PubMedGoogle Scholar
  3. 3.
    Browner WS, Pressman AR, Nevitt MC et al (1996) Mortality following fractures in older women. The study of osteoporotic fractures. Arch Intern Med 156:1521–1525PubMedCrossRefGoogle Scholar
  4. 4.
    Hannan EL, Magaziner J, Wang JJ et al (2001) Mortality and locomotion 6 months after hospitalization for hip fracture: risk factors and risk-adjusted hospital outcomes. JAMA 285:2736–2742PubMedCrossRefGoogle Scholar
  5. 5.
    Adachi JD, Loannidis G, Berger C et al (2001) The influence of osteoporotic fractures on health-related quality of life in community-dwelling men and women across Canada. Osteoporos Int 12:903–908PubMedCrossRefGoogle Scholar
  6. 6.
    Hallberg I, Rosenqvist AM, Kartous L et al (2004) Health-related quality of life after osteoporotic fractures. Osteoporos Int 15:834–841PubMedCrossRefGoogle Scholar
  7. 7.
    Johnell O, Kanis JA (2006) An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int 17:1726–1733PubMedCrossRefGoogle Scholar
  8. 8.
    Melton LJ III (2003) Epidemiology worldwide. Endocrinol Metab Clin North Am 32:1–13PubMedCrossRefGoogle Scholar
  9. 9.
    Kanis JA, McCloskey EV, Johansson H et al (2008) A reference standard for the description of osteoporosis. Bone 42:467–475PubMedCrossRefGoogle Scholar
  10. 10.
    Kanis JA, Borgstrom F, De Laet C et al (2005) Assessment of fracture risk. Osteoporos Int 16:581–589PubMedCrossRefGoogle Scholar
  11. 11.
    Kanis JA, Johnell O, Oden A et al (2006) The use of multiple sites for the diagnosis of osteoporosis. Osteoporos Int 17:527–534PubMedCrossRefGoogle Scholar
  12. 12.
    Stone KL, Seeley DG, Lui LY et al (2003) BMD at multiple sites and risk of fracture of multiple types: long-term results from the study of osteoporotic fractures. J Bone Miner Res 18:1947–1954PubMedCrossRefGoogle Scholar
  13. 13.
    Beck TJ, Ruff CB, Warden KE et al (1990) Predicting femoral neck strength from bone mineral data. A structural approach. Invest Radiol 25:6–18PubMedCrossRefGoogle Scholar
  14. 14.
    Bouxsein ML, Karasik D (2006) Bone geometry and skeletal fragility. Curr Osteoporos Rep 4:49–56PubMedCrossRefGoogle Scholar
  15. 15.
    Faulkner KG, Wacker WK, Barden HS et al (2006) Femur strength index predicts hip fracture independent of bone density and hip axis length. Osteoporos Int 17:593–599PubMedCrossRefGoogle Scholar
  16. 16.
    Rivadeneira F, Zillikens MC, De Laet CE et al (2007) Femoral neck BMD is a strong predictor of hip fracture susceptibility in elderly men and women because it detects cortical bone instability: the Rotterdam Study. J Bone Miner Res 22:1781–1790PubMedCrossRefGoogle Scholar
  17. 17.
    Kaptoge S, Beck TJ, Reeve J et al (2008) Prediction of incident hip fracture risk by femur geometry variables measured by hip structural analysis in the study of osteoporotic fractures. J Bone Miner Res 23:1892–1904PubMedCrossRefGoogle Scholar
  18. 18.
    Leslie WD, Metge C (2003) Establishing a regional bone density program: lessons from the Manitoba experience. J Clin Densitom 6:275–282PubMedCrossRefGoogle Scholar
  19. 19.
    Leslie WD, MacWilliam L, Lix L et al (2005) A population-based study of osteoporosis testing and treatment following introduction of a new bone densitometry service. Osteoporos Int 16:773–782PubMedCrossRefGoogle Scholar
  20. 20.
    Leslie WD, Caetano PA, MacWilliam LR et al (2005) Construction and validation of a population-based bone densitometry database. J Clin Densitom 8:25–30PubMedCrossRefGoogle Scholar
  21. 21.
    Roos NP, Shapiro E (1999) Revisiting the Manitoba Centre for Health Policy and Evaluation and its population-based health information system. Med Care 37:JS10–JS14PubMedCrossRefGoogle Scholar
  22. 22.
    Binkley N, Kiebzak GM, Lewiecki EM et al (2005) Recalculation of the NHANES database SD improves T-score agreement and reduces osteoporosis prevalence. J Bone Miner Res 20:195–201PubMedCrossRefGoogle Scholar
  23. 23.
    Boudousq V, Goulart DM, Dinten JM et al (2005) Image resolution and magnification using a cone beam densitometer: optimizing data acquisition for hip morphometric analysis. Osteoporos Int 16:813–822PubMedCrossRefGoogle Scholar
  24. 24.
    Leslie WD (2006) The importance of spectrum bias on bone density monitoring in clinical practice. Bone 39:361–368PubMedCrossRefGoogle Scholar
  25. 25.
    Leslie WD, Tsang JF, Caetano PA et al (2007) Effectiveness of bone density measurement for predicting osteoporotic fractures in clinical practice. J Clin Endocrinol Metab 92:77–81PubMedCrossRefGoogle Scholar
  26. 26.
    Kanis JA, Johnell O, Oden A et al (2001) Ten year probabilities of osteoporotic fractures according to BMD and diagnostic thresholds. Osteoporos Int 12:989–995PubMedCrossRefGoogle Scholar
  27. 27.
    Kanis JA, Johnell O, Oden A et al (2008) FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int 19:385–397PubMedCrossRefGoogle Scholar
  28. 28.
    Leslie WD, Tsang JF, Caetano PA et al (2007) Effectiveness of bone density measurement for predicting osteoporotic fractures in clinical practice. J Clin Endocrinol Metab 92:77–81PubMedCrossRefGoogle Scholar
  29. 29.
    Singer JD, Willet JB (eds) (2003) Applied longitudinal data analysis: Modeling change and event occurrence. Oxford University Press, New YorkGoogle Scholar
  30. 30.
    DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845PubMedCrossRefGoogle Scholar
  31. 31.
    Blake GM, Patel R, Knapp KM et al (2003) Does the combination of two BMD measurements improve fracture discrimination? J Bone Miner Res 18:1955–1963PubMedCrossRefGoogle Scholar
  32. 32.
    Szulc P, Duboeuf F, Schott AM et al (2006) Structural determinants of hip fracture in elderly women: re-analysis of the data from the EPIDOS study. Osteoporos Int 17:231–236PubMedCrossRefGoogle Scholar
  33. 33.
    Nevitt MC, Ettinger B, Black DM et al (1998) The association of radiographically detected vertebral fractures with back pain and function: a prospective study. Ann Intern Med 128:793–800PubMedGoogle Scholar

Copyright information

© International Osteoporosis Foundation and National Osteoporosis Foundation 2009

Authors and Affiliations

  • W. D. Leslie
    • 1
    • 2
    • 3
    • 5
  • P. S. Pahlavan
    • 2
  • J. F. Tsang
    • 3
  • L. M. Lix
    • 4
  • for the Manitoba Bone Density Program
  1. 1.Department of MedicineUniversity of ManitobaWinnipegCanada
  2. 2.Department of Nuclear MedicineSt. Boniface General HospitalWinnipegCanada
  3. 3.Department of RadiologyUniversity of ManitobaWinnipegCanada
  4. 4.School of Public HealthUniversity of SaskatchewanSaskatoonCanada
  5. 5.Department of Medicine (C5121)St. Boniface General HospitalWinnipegCanada

Personalised recommendations