Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews
Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews
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DOI：
10.1016/j.jclinepi.2005.02.022
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发表时间：
2005-10-01
影响因子：
7.2
通讯作者：
Zwinderman, AH
中科院分区：
文献类型：
--
作者：
Reitsma, JB;Glas, AS;Zwinderman, AH
Background and Objectives: Studies of diagnostic accuracy most often report pairs of sensitivity and specificity. We demonstrate the advantage of using bivariate meta-regression models to analyze such data.Methods: We discuss the methodology of both the summary Receiver Operating Characteristic (sROC) and the bivariate approach by reanalyzing the data of a published meta-analysis.Results: The sROC approach is the standard method for meta-analyzing diagnostic studies reporting pairs of sensitivity and specificity. This method uses the diagnostic odds ratio as the main outcome measure, which removes the effect of a possible threshold but at the same time loses relevant clinical information about test performance. The bivariate approach preserves the two-dimensional nature of the original data. Pairs of sensitivity and specificity are jointly analyzed, incorporating any correlation that might exist between these two measures using a random effects approach. Explanatory variables can be added to the bivariate model and lead to separate effects on sensitivity and specificity, rather than a net effect on the odds ratio scale as in the sROC approach. The statistical properties of the bivariate model are sound and flexible.Conclusion: The bivariate model can be seen as an improvement and extension of the traditional sROC approach. (c) 2005 Elsevier Inc. All rights reserved.
