Ten-year fracture probability identifies women who will benefit from clodronate therapy--additional results from a double-blind, placebo-controlled randomised study

Artikel i vetenskaplig tidskrift, 2009

Fracture risk prediction can be enhanced by the concurrent assessment of other clinical risk factors. This study demonstrates that the estimation of an individual's 10-year probability of fracture by the FRAX algorithm identifies patients at high risk of fracture who will respond to bisphosphonate therapy. INTRODUCTION: Treatments for osteoporosis are targeted largely to patients with low bone density (BMD) or a prior fragility fracture. Fracture risk prediction can be enhanced by the concurrent assessment of other clinical risk factors, but it is important to determine whether the risk so identified can be reduced by intervention. We determined the effect of a bisphosphonate on fracture rates when risk was calculated using a new risk algorithm (FRAX). METHODS: Women aged 75 years or more were recruited to a randomised, double-blind controlled trial of 800 mg oral clodronate (Bonefos) daily over 3 years. Baseline clinical risk factors were entered in the FRAX model to compute the 10-year probability of major osteoporotic fractures with or without input of femoral neck BMD. The interaction between fracture probability and treatment efficacy was examined by Poisson regression. RESULTS: In 3,974 women, the interaction between fracture probability and treatment efficacy was significant when probability was assessed without BMD (p = 0.043), but not when BMD was included (p = 0.10). Efficacy was more evident in those deemed at highest risk. For example women lying at the 75th percentile of fracture probability in the absence of BMD (10-year probability 24%) treatment reduced fracture risk by 27% (HR 0.73, 95%CI 0.58-0.92). In those with a fracture probability of 30% (90th percentile), the fracture risk reduction was 38% (HR 0.62, 0.46-0.84). CONCLUSIONS: The estimation of an individual's 10-year probability of fracture by the FRAX algorithm identifies patients at high risk of fracture who will respond to bisphosphonate therapy.