Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, Tampa, Florida.
Stat Med. 2022 Oct 30;41(24):4838-4859. doi: 10.1002/sim.9540. Epub 2022 Aug 5.
Positive and negative predictive values of a diagnostic test are two important measures of test accuracy, which are more relevant in clinical settings than sensitivity and specificity. Statistical methods have been well-developed to compare the predictive values of two binary diagnostic tests when test results and disease status fully observed for all study patients. In practice, however, it is common that only a subset of study patients have the disease status verified due to ethical or cost considerations. Methods applied directly to the verified subjects may lead to biased results. A bias-corrected method has been developed to compare two predictive values in the presence of verification bias. However, the complexity of the existing method and the computational difficulty in implementing it has restricted its use. A simple and easily implemented statistical method is therefore needed. In this paper, we propose a weighted generalized score (WGS) test statistic for comparing two predictive values in the presence of verification bias. The proposed WGS test statistic is intuitive and simple to compute, only involving some minor modification of the WGS test statistic when disease status is verified for each study patient. Simulations demonstrate that the proposed WGS test statistic preserves type I error much better than the existing Wald statistic. The method is illustrated with data from a study of methods for the diagnosis of coronary artery disease.
诊断试验的阳性和阴性预测值是衡量试验准确性的两个重要指标，与敏感度和特异度相比，它们在临床环境中更为相关。已经有成熟的统计方法来比较两种二分类诊断试验的预测值，这些方法需要所有研究患者的试验结果和疾病状态都完全被观察到。然而，在实际中，由于伦理或成本方面的考虑，通常只有一部分研究患者的疾病状态被验证。直接应用于已验证患者的方法可能会导致有偏的结果。已经开发了一种校正偏倚的方法来比较存在验证偏倚时的两种预测值。然而，现有方法的复杂性和在实施过程中的计算难度限制了它的使用。因此，需要一种简单且易于实现的统计方法。在本文中，我们提出了一种加权广义得分（WGS）检验统计量，用于在存在验证偏倚的情况下比较两种预测值。所提出的 WGS 检验统计量直观且易于计算，仅涉及在为每个研究患者验证疾病状态时对 WGS 检验统计量进行一些微小的修改。模拟研究表明，与现有的 Wald 统计量相比，所提出的 WGS 检验统计量更好地保持了Ⅰ类错误率。该方法通过冠状动脉疾病诊断方法研究的数据进行了说明。
