Meta-analysis of dichotomous and ordinal tests with an imperfect gold standard.
Meta-analysis of dichotomous and ordinal tests with an imperfect gold standard.
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DOI：
10.1002/jrsm.1567
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发表时间：
2022-09
影响因子：
9.8
通讯作者：
Sutton, Alex J.
中科院分区：
文献类型：
--
作者：
Cerullo, Enzo;Jones, Hayley E.;Carter, Olivia;Quinn, Terry J.;Cooper, Nicola J.;Sutton, Alex J.
医学试验Meta分析的标准方法，不假设金标准，仅限于二分数据。多元概率模型用于分析相关的二分数据，并可以扩展到有序数据模型。在不完美的金标准背景下，它们以前曾用于分析来自单个研究的二分和有序检验数据，以及用于二分检验的Meta分析。然而，它们之前未用于有序检验的Meta分析。在这篇文章中，我们开发了一个贝叶斯多变量概率单位潜在类模型，用于同时进行有序和二分检验的Meta分析，而无需假设金标准，这也允许人们获得联合检验准确度的汇总估计。我们使用Stan软件拟合模型，该软件使用最先进的Hamilton Monte Carlo算法，并将模型应用于数据集，其中研究评估了深静脉血栓形成测试和测试组合的准确性。我们证明了在存在不完美的金标准的情况下，二分有序检验准确性数据的问题，然后应用和比较我们提出的模型的几个变化，这些变化不需要对数据进行二分。提出的模型将允许研究人员在没有金标准的情况下更适当地对有序和二分测试进行Meta分析，可能导致测试准确性的偏倚估计。这可能会导致更好地了解哪些测试和测试组合应该用于任何给定的医疗条件。
Standard methods for the meta‐analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal data. Within the context of an imperfect gold standard, they have previously been used for the analysis of dichotomous and ordinal test data from a single study, and for the meta‐analysis of dichotomous tests. However, they have not previously been used for the meta‐analysis of ordinal tests. In this article, we developed a Bayesian multivariate probit latent class model for the simultaneous meta‐analysis of ordinal and dichotomous tests without assuming a gold standard, which also allows one to obtain summary estimates of joint test accuracy. We fitted the models using the software Stan, which uses a state‐of‐the‐art Hamiltonian Monte Carlo algorithm, and we applied the models to a dataset in which studies evaluated the accuracy of tests, and test combinations, for deep vein thrombosis. We demonstrate the issues with dichotomising ordinal test accuracy data in the presence of an imperfect gold standard, before applying and comparing several variations of our proposed model which do not require the data to be dichotomised. The models proposed will allow researchers to more appropriately meta‐analyse ordinal and dichotomous tests without a gold standard, potentially leading to less biased estimates of test accuracy. This may lead to a better understanding of which tests, and test combinations, should be used for any given medical condition.
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