Osteoporosis International

, Volume 18, Issue 8, pp 1033–1046

The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women

  • J. A. Kanis
  • A. Oden
  • O. Johnell
  • H. Johansson
  • C. De Laet
  • J. Brown
  • P. Burckhardt
  • C. Cooper
  • C. Christiansen
  • S. Cummings
  • J. A. Eisman
  • S. Fujiwara
  • C. Glüer
  • D. Goltzman
  • D. Hans
  • M.-A. Krieg
  • A. La Croix
  • E. McCloskey
  • D. Mellstrom
  • L. J. MeltonIII
  • H. Pols
  • J. Reeve
  • K. Sanders
  • A-M. Schott
  • A. Silman
  • D. Torgerson
  • T. van Staa
  • N. B. Watts
  • N. Yoshimura
Original Article

DOI: 10.1007/s00198-007-0343-y

Cite this article as:
Kanis, J.A., Oden, A., Johnell, O. et al. Osteoporos Int (2007) 18: 1033. doi:10.1007/s00198-007-0343-y

Abstract

Summary

BMD and clinical risk factors predict hip and other osteoporotic fractures. The combination of clinical risk factors and BMD provide higher specificity and sensitivity than either alone.

Introduction and hypotheses

To develop a risk assessment tool based on clinical risk factors (CRFs) with and without BMD.

Methods

Nine population-based studies were studied in which BMD and CRFs were documented at baseline. Poisson regression models were developed for hip fracture and other osteoporotic fractures, with and without hip BMD. Fracture risk was expressed as gradient of risk (GR, risk ratio/SD change in risk score).

Results

CRFs alone predicted hip fracture with a GR of 2.1/SD at the age of 50 years and decreased with age. The use of BMD alone provided a higher GR (3.7/SD), and was improved further with the combined use of CRFs and BMD (4.2/SD). For other osteoporotic fractures, the GRs were lower than for hip fracture. The GR with CRFs alone was 1.4/SD at the age of 50 years, similar to that provided by BMD (GR = 1.4/SD) and was not markedly increased by the combination (GR = 1.4/SD). The performance characteristics of clinical risk factors with and without BMD were validated in eleven independent population-based cohorts.

Conclusions

The models developed provide the basis for the integrated use of validated clinical risk factors in men and women to aid in fracture risk prediction.

Keywords

Bone mineral densityHip fractureMeta-analysisOsteoporotic fractureRisk assessment

Copyright information

© International Osteoporosis Foundation and National Osteoporosis Foundation 2007

Authors and Affiliations

  • J. A. Kanis
    • 1
  • A. Oden
    • 2
  • O. Johnell
    • 3
  • H. Johansson
    • 2
  • C. De Laet
    • 4
  • J. Brown
    • 5
  • P. Burckhardt
    • 6
  • C. Cooper
    • 7
  • C. Christiansen
    • 8
  • S. Cummings
    • 9
  • J. A. Eisman
    • 10
  • S. Fujiwara
    • 11
  • C. Glüer
    • 12
  • D. Goltzman
    • 13
  • D. Hans
    • 14
  • M.-A. Krieg
    • 15
  • A. La Croix
    • 16
  • E. McCloskey
    • 1
  • D. Mellstrom
    • 17
  • L. J. MeltonIII
    • 18
  • H. Pols
    • 19
  • J. Reeve
    • 20
  • K. Sanders
    • 21
  • A-M. Schott
    • 22
  • A. Silman
    • 23
  • D. Torgerson
    • 24
  • T. van Staa
    • 25
  • N. B. Watts
    • 26
  • N. Yoshimura
    • 27
  1. 1.WHO Collaborating Centre for Metabolic Bone DiseasesUniversity of Sheffield Medical SchoolSheffieldUK
  2. 2.Consulting StatisticianGothenburgSweden
  3. 3.Department of OrthopaedicsMalmö General HospitalMalmoSweden
  4. 4.Scientific Institute of Public HealthBrusselsBelgium
  5. 5.Department of RheumatologySans Ospedale University de QuebecQuebecCanada
  6. 6.Department of MedicineCHUV University HospitalLausanneSwitzerland
  7. 7.MRC Epidemiology UnitSouthampton General HospitalSouthamptonUK
  8. 8.CCBRBallerupDenmark
  9. 9.SF Coordinating CenterSan FranciscoUSA
  10. 10.Bone and Mineral Research Program, Garvan Institute of Medical ResearchSt Vincent’s, Hospital and University of New South WalesSydneyAustralia
  11. 11.Department of Clinical StudiesRadiation Effects Research FoundationHiroshimaJapan
  12. 12.Medizinische PhysikUniversitas Klinikum Schleswig-HosteinKeilGermany
  13. 13.Department of MedicineMcGill UniversityMontrealCanada
  14. 14.Nuclear Medicine DivisionGeneva University HospitalGenevaSwitzerland
  15. 15.CHUV University HospitalLausanneSwitzerland
  16. 16.Fred Hutchinson Cancer Research CenterSeattleUSA
  17. 17.Department of Geriatric MedicineGoteborg UniversityGothenburgSweden
  18. 18.Division of EpidemiologyMayo ClinicRochesterUSA
  19. 19.Department of Internal MedicineErasmus Medical Centre RotterdamRotterdamThe Netherlands
  20. 20.Strangeway’s Research LaboratoryWort’s CausewayCambridgeUK
  21. 21.Department of Clinical and Biomedical SciencesUniversity of MelbourneBarwon HealthAustralia
  22. 22.INSERM U831Hospices Civils de LyonLyonFrance
  23. 23.ARC Epidemiology UnitUniversity of ManchesterManchesterUK
  24. 24.Department of Health SciencesUniversity of YorkYorkshireUK
  25. 25.Department of Pharmaco-epidemiology and PharmacotherapyUniversity of UtrechtHollandThe Netherlands
  26. 26.University of Cincinnati College of MedicineCincinnatiUSA
  27. 27.Joint Disease Research, Graduate School of MedicineUniversity of TokyoTokyoJapan