Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas
Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas
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DOI：
10.1002/sim.5909
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发表时间：
2014-01-15
影响因子：
2
通讯作者：
Solms, Alexander
中科院分区：
文献类型：
--
作者：
Kuss, Oliver;Hoyer, Annika;Solms, Alexander
在对诊断准确性研究的数据进行荟萃分析时仍然存在挑战。这主要是由于反应的双变量性质，其中必须总结敏感性和特异性的信息，同时说明它们在单个试验中的相关性。在本文中，我们提出了一个新的统计模型的荟萃分析诊断准确性的研究。该模型使用β-二项分布的真阳性和真阴性的边缘数，并通过二元copula分布将这些边缘联系起来。新模型具有当前标准模型的所有特征，即具有随机效应的二元逻辑回归模型，但具有封闭似然函数的额外优势以及灵敏度和特异性相关结构的更大灵活性。在一项模拟研究中，比较了三种Copula模型和标准模型的两种实现，Plackett和Gauss Copula的表现很少比标准模型差，但往往比标准模型好。我们使用一个荟萃分析的例子来判断端粒酶（一种泌尿系肿瘤标志物）诊断原发性膀胱癌的准确性。版权所有（c）2013约翰威利父子有限公司
There are still challenges when meta-analyzing data from studies on diagnostic accuracy. This is mainly due to the bivariate nature of the response where information on sensitivity and specificity must be summarized while accounting for their correlation within a single trial. In this paper, we propose a new statistical model for the meta-analysis for diagnostic accuracy studies. This model uses beta-binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution. The new model comes with all the features of the current standard model, a bivariate logistic regression model with random effects, but has the additional advantages of a closed likelihood function and a larger flexibility for the correlation structure of sensitivity and specificity. In a simulation study, which compares three copula models and two implementations of the standard model, the Plackett and the Gauss copula do rarely perform worse but frequently better than the standard model. We use an example from a meta-analysis to judge the diagnostic accuracy of telomerase (a urinary tumor marker) for the diagnosis of primary bladder cancer for illustration. Copyright (c) 2013 John Wiley & Sons, Ltd.