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Predicting risk of osteoporotic fracture

Last reviewed dd mmm yyyy. Last edited dd mmm yyyy

Authoring team

A risk prediction utility to identify accurately the individuals at high risk of osteoporotic fracture who might benefit from a therapeutic or preventive intervention has been a necessity since identifying people at high risk will help in reducing the morbidity associated with osteoporotic fractures (1)

  • several guidelines recommend an approach which identifies high risk patients who are likely to benefit from interventions based on a 10 year absolute fracture risk (1).

The traditionally used approach has been to use the bone mineral density (BMD) measurements

  • this method is not suitable for population screening due to the cost and low sensitivity
  • most fractures are seen in women with normal BMD
  • it has been shown that risk prediction algorithms that do not include BMD are almost as good as those that include BMD

Risk prediction algorithms tend to perform best when they are developed in a clinical setting in which they will be applied (1).

Available fracture risk assessment tools include:

  • WHO risk calculator (FRAX)
  • QFracture score (1)

Reference:

  • 1. International Osteoporosis Foundation and National Osteoporosis Foundation 2011. Osteoporosis: burden, health care provision and opportunities in the EU. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA)

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