Dukic V, Gatsonis C
Department of Health Studies, University of Chicago, Chicago, Illinois, USA.
Biometrics. 2003 Dec;59(4):936-46. doi: 10.1111/j.0006-341x.2003.00108.x.
Current meta-analytic methods for diagnostic test accuracy are generally applicable to a selection of studies reporting only estimates of sensitivity and specificity, or at most, to studies whose results are reported using an equal number of ordered categories. In this article, we propose a new meta-analytic method to evaluate test accuracy and arrive at a summary receiver operating characteristic (ROC) curve for a collection of studies evaluating diagnostic tests, even when test results are reported in an unequal number of nonnested ordered categories. We discuss both non-Bayesian and Bayesian formulations of the approach. In the Bayesian setting, we propose several ways to construct summary ROC curves and their credible bands. We illustrate our approach with data from a recently published meta-analysis evaluating a single serum progesterone test for diagnosing pregnancy failure.
当前用于诊断试验准确性的Meta分析方法通常适用于仅报告敏感性和特异性估计值的一系列研究,或者至多适用于那些使用相同数量的有序类别报告结果的研究。在本文中,我们提出了一种新的Meta分析方法来评估试验准确性,并为评估诊断试验的一系列研究得出汇总的受试者工作特征(ROC)曲线,即使试验结果是用不同数量的非嵌套有序类别报告的。我们讨论了该方法的非贝叶斯和贝叶斯形式。在贝叶斯框架下,我们提出了几种构建汇总ROC曲线及其可信区间的方法。我们用最近发表的一项Meta分析中的数据说明了我们的方法,该分析评估了一种用于诊断妊娠失败的血清孕酮单项检测。