Methods for Assessing Improvement in Specificity When a Biomarker is Combined With a Standard Screening Test
Methods for Assessing Improvement in Specificity When a Biomarker is Combined With a Standard Screening Test
复制标题
DOI：
10.1198/sbr.2009.0002
复制
发表时间：
2009-02-01
影响因子：
1.8
通讯作者：
Etzioni, Ruth
中科院分区：
文献类型：
--
作者：
Shaw, Pamela A.;Pepe, Margaret S.;Etzioni, Ruth
可与已建立的筛选试验结合使用以减少假阳性率的生物标志物的需求相当大。在这篇文章中，我们提出了评估除了标准筛选试验外，还需要生物标志物试验阳性的联合试验的诊断性能的方法。这些方法依赖于相对的真阳性率和假阳性率来衡量与标准测试相关的组合的灵敏度损失和特异性增加。关于相对比率的推论来自于将其解释为条件概率。通过引入一个新的统计实体，即相对受试者工作特征（rROC）曲线，这些方法被扩展到评估与连续生物标志物试验的组合。rROC曲线绘制了阳性生物标志物阈值变化时的相对真阳性率与相对假阳性率。运用现有的ROC方法进行推断。我们用两个例子来说明这些方法：一个是早期检测研究网络（EDRN）提出的乳腺癌生物标志物研究，另一个是前列腺癌病例对照研究，研究游离前列腺特异性抗原（PSA）提高标准PSA检测特异性的能力。
Biomarkers that can be used in combination with established screening tests to reduce false positive rates are in considerable demand. In this article, we present methods for evaluating the diagnostic performance of combination tests that require positivity on a biomarker test in addition to a standard screening test. These methods rely on relative true-and false-positive rates to measure the loss in sensitivity and gain in specificity associated with the combination relative to the standard test. Inference about the relative rates follows from noting their interpretation as conditional probabilities. These methods are extended to evaluate combinations with continuous biomarker tests by introducing a new statistical entity, the relative receiver operating characteristic (rROC) curve. The rROC curve plots the relative true positive rate versus the relative false positive rate as the biomarker threshold for positivity varies. Inference can be made by applying existing ROC methodology. We illustrate the methods with two examples: a breast cancer biomarker study proposed by the Early Detection Research Network (EDRN) and a prostate cancer case-control study examining the ability of free prostate-specific antigen (PSA) to improve the specificity of the standard PSA test.