Bayesian meta-analysis of diagnostic tests allowing for imperfect reference standards
Bayesian meta-analysis of diagnostic tests allowing for imperfect reference standards
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DOI：
10.1002/sim.5959
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发表时间：
2013-12-30
影响因子：
2
通讯作者：
Lesaffre, E.
中科院分区：
文献类型：
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作者：
Menten, J.;Boelaert, M.;Lesaffre, E.
传染病快速诊断试验(RDT)的荟萃分析越来越受到人们的关注。为了避免光谱偏差，这些荟萃分析应侧重于在目标人群中进行的第四阶段研究。对于许多传染病，这些目标人群在资源有限的环境中前往初级卫生保健中心，在那里很难进行黄金标准的诊断测试。因此，IV期诊断研究经常使用不完善的参考标准，这可能导致对新型RDT诊断准确性的偏倚荟萃分析。我们扩展了诊断研究的荟萃分析的标准双变量模型，以修正初步研究中不同和不完美的参考标准，并容纳那些试图通过使用潜在类别分析来克服缺乏真正的黄金标准的研究的数据。使用贝叶斯方法，可以改进灵敏度和特异度的估计，特别是当参考测试的诊断准确性的先验信息可用时。在这种分析中，可以使用偏差信息准则来检测先验信息和观测数据之间的冲突。当将该模型应用于RDT对内脏利什曼病诊断准确性的数据集时，标准的荟萃分析方法似乎低估了RDT的特异性。版权所有(C)2013 John Wiley&Sons，Ltd.
There is an increasing interest in meta-analyses of rapid diagnostic tests (RDTs) for infectious diseases. To avoid spectrum bias, these meta-analyses should focus on phase IV studies performed in the target population. For many infectious diseases, these target populations attend primary health care centers in resource-constrained settings where it is difficult to perform gold standard diagnostic tests. As a consequence, phase IV diagnostic studies often use imperfect reference standards, which may result in biased meta-analyses of the diagnostic accuracy of novel RDTs. We extend the standard bivariate model for the meta-analysis of diagnostic studies to correct for differing and imperfect reference standards in the primary studies and to accommodate data from studies that try to overcome the absence of a true gold standard through the use of latent class analysis. Using Bayesian methods, improved estimates of sensitivity and specificity are possible, especially when prior information is available on the diagnostic accuracy of the reference test. In this analysis, the deviance information criterion can be used to detect conflicts between the prior information and observed data. When applying the model to a dataset of the diagnostic accuracy of an RDT for visceral leishmaniasis, the standard meta-analytic methods appeared to underestimate the specificity of the RDT. Copyright (c) 2013 John Wiley & Sons, Ltd.