Rheumatology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal Health Sciences Research Unit: Nursing (UICiSA:E), Coimbra, Portugal.
Instituto de Salud Musculoesquelética-InMusc, Madrid, Spain.
Ann Rheum Dis. 2015 Nov;74(11):1958-67. doi: 10.1136/annrheumdis-2015-207907. Epub 2015 Aug 6.
To identify and synthesise the best available evidence on the accuracy of the currently available tools for predicting fracture risk.
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.
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 participants). Twenty studies with these three tools were included in a total of 17 meta-analyses (for hip or major osteoporotic fractures; men or women; with or without bone mineral density).
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.
识别和综合目前可用于预测骨折风险的工具的准确性的最佳可用证据。
我们系统地检索了 PubMed MEDLINE、Embase 和 Cochrane 数据库,检索时间截至 2014 年。两名审查员独立选择文章,从研究中收集数据,并对手头包含研究的参考文献进行了搜索。使用了诊断准确性研究的质量评估工具(QUADAS)检查表,主要结果是来自受试者工作特征(ROC)分析的曲线下面积(AUC)和 95%置信区间(CI)。如果工具未经过外部验证或专为特定疾病人群设计,则将其排除在外。对选定的工具进行了随机效应荟萃分析。
45 项研究符合纳入标准,对应 13 种不同的工具。只有三种工具在基于人群的环境中进行了不止一次的测试:FRAX(9 个国家的 26 项研究)、GARVAN(3 个国家的 6 项研究)和 QFracture(英国的 3 项研究,其中 1 项也包括爱尔兰参与者)。这三种工具中有 20 项研究被纳入了总共 17 项荟萃分析(涉及髋部或主要骨质疏松性骨折;男性或女性;有或没有骨密度)。
13 种工具中的大多数在临床实践中是可行的。FRAX 拥有最多经过外部验证和独立研究的工具。不同工具的整体准确性令人满意(>0.70),其中 QFracture 达到 0.89(95%CI 0.88 至 0.89)。许多研究中观察到了明显的方法学局限性,这表明仅根据 AUC 来比较工具时需要谨慎。