Selection for treatment of patients at high risk of fracture by the short versus long term prediction models - data from the Belgian FRISBEE cohort.

Abstract

Our imminent model was less sensitive but more selective than FRAX® in the choice of treatment to prevent imminent fractures. This new model decreased NNT by 30%, which could reduce the treatment costs. In the Belgian FRISBEE cohort, the effect of recency further decreased the selectivity of FRAX®. We analyzed the selection for treatment of patients at high risk of fracture by the Belgian FRISBEE imminent model and the FRAX® tool. We identified in the FRISBEE cohort subjects who sustained an incident MOF (mean age 76.5 ± 6.8 years). We calculated their estimated 10-year risk of fracture using FRAX® before and after adjustment for recency and the 2-year probability of fracture using the FRISBEE model. After 6.8 years of follow-up, we validated 480 incident and 54 imminent MOFs. Of the subjects who had an imminent fracture, 94.0% had a fracture risk estimated above 20% by the FRAX® before correction for recency and 98.1% after adjustment, with a specificity of 20.2% and 5.9%, respectively. The sensitivity and specificity of the FRISBEE model at 2 years were 72.2% and 55.4%, respectively, for a threshold of 10%. For these thresholds, 47.3% of the patients were identified at high risk in both models before the correction, and 17.2% of them had an imminent MOF. The adjustment for recency did not change this selection. Before the correction, 34.2% of patients were selected for treatment by FRAX® only, and 18.8% would have had an imminent MOF. This percentage increased to 47% after the adjustment for recency, but only 6% of those would suffer a MOF within 2 years. In our Belgian FRISBEE cohort, the imminent model was less sensitive but more selective in the selection of subjects in whom an imminent fracture should be prevented, resulting in a lower NNT. The correction for recency in this elderly population further decreased the selectivity of FRAX®. These data should be validated in additional cohorts before using them in everyday practice.