The accuracy of XXXX risk prediction tools: a systematic review and meta-analysis.

@entity1 @entity3604 @entity174
OBJECTIVES: To identify and synthesise the best available evidence on the accuracy of the currently available tools for predicting @entity174 risk. METHODS: We systematically searched PubMed MEDLINE, Embase and Cochrane databases to 2014. Two reviewers independently selected articles, collected data from studies, and carried out a hand search of the references of the included studies. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist was used, and the primary outcome was the area under the curve (AUC) and 95% CIs, obtained from receiver operating characteristic (ROC) analyses. We excluded tools if they had not been externally validated or were designed for specific disease populations. Random effects meta-analyses were performed with the selected tools. RESULTS: Forty-five studies met inclusion criteria, corresponding to 13 different tools. Only three tools had been tested more than once in a population-based setting: FRAX (26 studies in 9 countries), GARVAN (6 studies in 3 countries) and QFracture (3 studies in the UK, 1 also including Irish @entity1 ). Twenty studies with these three tools were included in a total of 17 meta-analyses (for hip or major @entity3604 ; @entity1 or @entity1 ; with or without bone mineral density). CONCLUSIONS: Most of the 13 tools are feasible in clinical practice. FRAX has the largest number of externally validated and independent studies. The overall accuracy of the different tools is satisfactory (>0.70), with QFracture reaching 0.89 (95% CI 0.88 to 0.89). Significant methodological limitations were observed in many studies, suggesting caution when comparing tools based solely on the AUC.
