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Archives of Osteoporosis

, 12:91 | Cite as

Comparison of fracture risk assessment tools in older men without prior hip or spine fracture: the MrOS study

  • Margaret L. GourlayEmail author
  • Victor S. Ritter
  • Jason P. Fine
  • Robert A. Overman
  • John T. Schousboe
  • Peggy M. Cawthon
  • Eric S. Orwoll
  • Tuan V. Nguyen
  • Nancy E. Lane
  • Steven R. Cummings
  • Deborah M. Kado
  • Jodi A. Lapidus
  • Susan J. Diem
  • Kristine E. Ensrud
  • for the Osteoporotic Fractures in Men (MrOS) Study Group
Original Article

Abstract

Summary

Femoral neck bone mineral density (BMD), age plus femoral neck BMD T score, and three externally generated fracture risk tools had similar accuracy to identify older men who developed osteoporotic fractures. Risk tools with femoral neck BMD performed better than those without BMD. The externally developed risk tools were poorly calibrated.

Introduction

We compared the performance of fracture risk assessment tools in older men, accounting for competing risks including mortality.

Methods

A comparative ROC curve analysis assessed the ability of the QFracture, FRAX® and Garvan fracture risk tools, and femoral neck bone mineral density (BMD) T score with or without age to identify incident fracture in community-dwelling men aged 65 years or older (N = 4994) without hip or clinical vertebral fracture or antifracture treatment at baseline.

Results

Among risk tools calculated with BMD, the discriminative ability to identify men with incident hip fracture was similar for FRAX (AUC 0.77, 95% CI 0.73, 0.81), the Garvan tool (AUC 0.78, 95% CI 0.74, 0.82), age plus femoral neck BMD T score (AUC 0.79, 95% CI 0.75, 0.83), and femoral neck BMD T score alone (AUC 0.76, 95% CI 0.72, 0.81). Among risk tools calculated without BMD, the discriminative ability to identify hip fracture was similar for QFracture (AUC 0.69, 95% CI 0.66, 0.73), FRAX (AUC 0.70, 95% CI 0.66, 0.73), and the Garvan tool (AUC 0.71, 95% CI 0.67, 0.74). Correlated ROC curve analyses revealed better diagnostic accuracy for risk scores calculated with BMD compared with QFracture (P < 0.0001). Calibration was good for the internally generated BMD T score predictor with or without age and poor for the externally developed risk tools.

Conclusion

In untreated older men without fragility fractures at baseline, an age plus femoral neck BMD T score classifier identified men with incident hip fracture as accurately as more complicated fracture risk scores.

Keywords

Bone density Fractures Male Osteoporosis Risk assessment 

Notes

Acknowledgments

We acknowledge Carrie Gartland for her assistance with manuscript preparation.

Funding information

The project described was funded by grant number R01 AG046294 (Gourlay, Ritter, Overman, Fine), grant number UL1TR001111 from the National Center for Advancing Translational Sciences, and grant number K24 AR048841 (Lane) from the National Institute of Arthritis and Musculoskeletal and Skin Diseases. The work of Dr. Ensrud was supported in part with resources and use of facilities at the Minneapolis VA Medical Center. The Osteoporotic Fractures in Men Study is supported by NIH funding. The following institutes provide support: the National Institute on Aging, the National Institute of Arthritis and Musculoskeletal and Skin Diseases, the National Center for Advancing Translational Sciences, and National Institutes of Health Roadmap for Medical Research under the following grant numbers: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128.

Compliance with ethical standards

Conflict of interest

The content is solely the responsibility of the authors and does not necessarily reflect the official views of the funding agencies. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or in the decision to submit the manuscript for publication. Dr. Cawthon reports research grants from GlaxoSmithKline. Dr. Orwoll has received research and consulting support from Merck, Eli Lilly, and Amgen. Dr. Lane has received research and or consulting support from Merck, Amgen, and Regeneron. Dr. Kado has received consultant support from Kalytera Therapeutics, Takeda Pharmaceuticals, and Amgen. No other financial disclosures were reported by the authors of this paper.

Supplementary material

11657_2017_389_MOESM1_ESM.docx (171 kb)
ESM 1 (DOCX 171 kb)

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Copyright information

© International Osteoporosis Foundation and National Osteoporosis Foundation 2017

Authors and Affiliations

  • Margaret L. Gourlay
    • 1
    Email author
  • Victor S. Ritter
    • 2
  • Jason P. Fine
    • 2
  • Robert A. Overman
    • 3
  • John T. Schousboe
    • 4
    • 5
  • Peggy M. Cawthon
    • 6
  • Eric S. Orwoll
    • 7
  • Tuan V. Nguyen
    • 8
    • 9
  • Nancy E. Lane
    • 10
  • Steven R. Cummings
    • 6
  • Deborah M. Kado
    • 11
    • 12
  • Jodi A. Lapidus
    • 13
  • Susan J. Diem
    • 14
    • 15
  • Kristine E. Ensrud
    • 14
    • 15
    • 16
  • for the Osteoporotic Fractures in Men (MrOS) Study Group
  1. 1.Department of Family MedicineUniversity of North CarolinaChapel HillUSA
  2. 2.Department of BiostatisticsUniversity of North CarolinaChapel HillUSA
  3. 3.NoviSci, LLCDurhamUSA
  4. 4.Department of RheumatologyPark Nicollet Health ServicesMinneapolisUSA
  5. 5.Division of Health Policy and ManagementUniversity of MinnesotaMinneapolisUSA
  6. 6.Research InstituteCalifornia Pacific Medical CenterSan FranciscoUSA
  7. 7.Bone and Mineral UnitOregon Health and Science UniversityPortlandUSA
  8. 8.Garvan Institute of Medical ResearchUNSW School of Public Health and Community MedicineKensingtonAustralia
  9. 9.Centre for Health TechnologiesUniversity of TechnologySydneyAustralia
  10. 10.Division of Rheumatology, Department of Medicine, Center for Musculoskeletal HealthUC Davis Health SystemSacramentoUSA
  11. 11.Department of Family Medicine and Public HealthUniversity of California, San DiegoLa JollaUSA
  12. 12.Department of MedicineUniversity of California, San DiegoLa JollaUSA
  13. 13.School of Public HealthOregon Health and Science UniversityPortlandUSA
  14. 14.Department of MedicineUniversity of MinnesotaMinneapolisUSA
  15. 15.Division of Epidemiology and Community Health, School of Public HealthUniversity of MinnesotaMinneapolisUSA
  16. 16.Center for Chronic Disease Outcomes ResearchVA Health Care SystemMinneapolisUSA

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