A Model for Evaluating Sensitivity and Specificity for Correlated Diagnostic Tests in Efficacy Studies with an Imperfect Reference Test
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参考检验不完美时相关诊断检验的灵敏度与特异度评估模型
- 研究问题
- 当诊断检验在疾病状态给定后仍相关，且参考检验存在误判甚至缺失时，如何比较各检验的灵敏度、特异度及协变量影响？
- 方法与思路
- 作者提出包含连续与二元两个潜变量的广义线性混合模型，用 EM 与 Newton–Raphson 混合算法进行极大似然估计。
- 材料陈述的贡献
- 摘要称模型可处理不完美或缺失的参考检验，并提供模型检查以及个体条件和总体平均灵敏度、特异度的估计比较方法。
- 阅读关注点
- 应核对无准确参考检验时的可识别性、潜变量如何表达检验相关性，以及个体条件指标与总体平均指标的计算和解释。
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- 仅据 OpenAlex 索引摘要，稿件版本未注明；摘要未列出识别条件、算法收敛保证或应用数值，不能判断所有诊断组合均适用。
原文摘要
The purpose of a diagnostic efficacy study is to evaluate and compare the sensitivities and specificities of several diagnostic tests. Usually the diagnostic tests are correlated conditional on disease status, and the reference test is subject to error. In the Chlamydia trachomatis study, five screening tests for detecting chlamydia in endocervical specimens were compared. The five tests are correlated, and the reference test (the cell culture test) has less than 100% sensitivity. The conventional method ignores both the correlations between the tests and the misclassification of the reference test and thus cannot provide a valid analysis. We propose a model to evaluate and compare the sensitivities and specificities of correlated diagnostic tests when there is either an imperfect reference test or even no reference test. The model also can estimate the effects of covariates. It is a generalized linear mixed model with two unobserved variables, one continuous and one dichotomous. We use a hybrid algorithm, which consists of the EM algorithm and the Newton–Raphson method, for obtaining its maximum likelihood estimation. Methods for model checking and for estimating and comparing both subject-specific and population-averaged sensitivities and specificities are given.