Menten J, Boelaert M, Lesaffre E
Clinical Trials Unit, Institute of Tropical Medicine, Antwerp, Belgium; L-Biostat, KULeuven, Leuven, Belgium.
Stat Med. 2013 Dec 30;32(30):5398-413. doi: 10.1002/sim.5959. Epub 2013 Sep 4.
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.
对传染病快速诊断检测（RDT）的荟萃分析越来越受到关注。为避免谱偏倚，这些荟萃分析应聚焦于在目标人群中开展的IV期研究。对于许多传染病而言，这些目标人群就诊于资源有限环境下的初级卫生保健中心，在那里进行金标准诊断检测存在困难。因此，IV期诊断研究常常使用不完善的参考标准，这可能导致对新型RDT诊断准确性的荟萃分析出现偏倚。我们扩展了用于诊断研究荟萃分析的标准双变量模型，以校正初级研究中不同且不完善的参考标准，并纳入那些试图通过使用潜在类别分析来克服缺乏真正金标准这一问题的研究数据。使用贝叶斯方法，可以得到更好的灵敏度和特异度估计值，尤其是当参考检测的诊断准确性有先验信息可用时。在该分析中，偏差信息准则可用于检测先验信息与观测数据之间的冲突。当将该模型应用于内脏利什曼病RDT诊断准确性的数据集时，标准荟萃分析方法似乎低估了RDT的特异度。
