Abstract
BackgroundIn meta-analyses of diagnostic test accuracy, routinely only one pair of sensitivity and specificity per study is used. However, for tests based on a biomarker or a questionnaire often more than one threshold and the corresponding values of true positives, true negatives, false positives and false negatives are known.MethodsWe present a new meta-analysis approach using this additional information. It is based on the idea of estimating the distribution functions of the underlying biomarker or questionnaire within the non-diseased and diseased individuals. Assuming a normal or logistic distribution, we estimate the distribution parameters in both groups applying a linear mixed effects model to the transformed data. The model accounts for across-study heterogeneity and dependence of sensitivity and specificity. In addition, a simulation study is presented.ResultsWe obtain a summary receiver operating characteristic (SROC) curve as well as the pooled sensitivity and specificity at every specific threshold. Furthermore, the determination of an optimal threshold across studies is possible through maximization of the Youden index. We demonstrate our approach using two meta-analyses of B type natriuretic peptide in heart failure and procalcitonin as a marker for sepsis.ConclusionsOur approach uses all the available information and results in an estimation not only of the performance of the biomarker but also of the threshold at which the optimal performance can be expected.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-016-0196-1) contains supplementary material, which is available to authorized users.
Highlights
In meta-analyses of diagnostic test accuracy, routinely only one pair of sensitivity and specificity per study is used
Results of the simulation study Sensitivity and specificity: bias and mean squared error The bias of sensitivity and specificity increased with increasing heterogeneity
Conclusions our new approach can still be improved in some aspects, it accounts for the heterogeneity of the studies and the bivariate character of the data and includes multiple thresholds of studies, possibly differing in number
Summary
In meta-analyses of diagnostic test accuracy, routinely only one pair of sensitivity and specificity per study is used. For tests based on a biomarker or a questionnaire often more than one threshold and the corresponding values of true positives, true negatives, false positives and false negatives are known. Systematic reviews of diagnostic test accuracy (DTA) studies give an overview of the performance of a diagnostic test, e.g. based on a biomarker or a questionnaire. Each study contributes a two by two table, containing the numbers of true positives (TP), false positives (FP), true negatives (TN) and false negatives (FN). If varying thresholds were used in the studies, a summary receiver operating characteristic (SROC) curve is estimated to describe the change in sensitivity and specificity while varying the threshold [1]
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