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Which model to predict fracture risk?

Nature Reviews Endocrinology volume 10, pages 194195 (2014) | Download Citation

Prediction of fracture risk is increasingly used to guide clinical use of antiosteoporosis drugs. Data from a large primary care prospective study in 10 countries has now been used to generate an empirical composite 5-year fracture risk model based on clinical data (excluding BMD). This model performed better than current widely used models.

Key points

  • Osteoporotic fractures are an increasing health and societal burden worldwide

  • Low BMD and/or several clinical risk factors can be modelled into a 5–10-year empirical fracture risk predictor model; such models are already used to guide clinical treatment

  • Existing predictor models enable an accurate prediction in about 70% of patients. An extensive long-term observational study (GLOW) shows that such predictions can be further improved on the basis of extensive clinical data

  • Further improvement of predictor models seems to be possible by combining existing clinical predictor models with improved measurements of bone mass and quality and complex genetic analysis

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  1. 1.

    et al. Evaluation of the FRAX and Garvan fracture risk calculators in older women. J. Bone Miner. Res. 26, 420–427 (2011).

  2. 2.

    New horizons in fracture risk assessment. Age Ageing 42, 548–554 (2013).

  3. 3.

    , , & Performance of risk assessment instruments for predicting osteoporotic fracture risk: a systematic review. Osteoporos. Int. 25, 23–49 (2014).

  4. 4.

    et al. Empirically based composite fracture prediction model from the Global Longitudinal Study of Osteoporosis in Postmenopausal Women (GLOW). J. Clin. Endocrinol. Metabol. .

  5. 5.

    et al. The Global Longitudinal Study of Osteoporosis in Women (GLOW): rationale and study design. Osteoporos. Int. 20, 1107–1116 (2009).

  6. 6.

    , , , & Evaluating the yield of medical tests. JAMA 247, 2543–2546 (1982).

  7. 7.

    et al. 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, 1033–1046 (2007).

  8. 8.

    et al. FRAX provides robust fracture prediction regardless of socioeconomic status. Osteoporos. Int. 25, 61–69 (2014).

  9. 9.

    , , , & Development of prognostic nomograms for individualizing 5-year and 10-year fracture risks. Osteoporos. Int. 19, 1431–1444 (2008).

  10. 10.

    et al. Risk factors for treatment failure with antiosteoporosis medication: the Global Longitudinal Study of Osteoporosis in Women (GLOW). J. Bone Miner. Res. 29, 260–267 (2014).

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We join the authors of the FitzGerald et al. manuscript in dedicating these comments to our friend Steven Boonen.

Author information


  1. Clinical and Experimental Endocrinology, KU Leuven, Herestraat 49 ON1 Box 902, 3000 Leuven, Belgium.

    • Roger Bouillon
    •  & Dirk Vanderschueren


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Competing interests

The authors declare no competing financial interests.

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Correspondence to Roger Bouillon.

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