Perkins Neil J, Schisterman Enrique F
Division of Epidemiology, Statistics and Prevention Research, National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA.
Biom J. 2005 Aug;47(4):428-41. doi: 10.1002/bimj.200410133.
Random measurement error can attenuate a biomarker's ability to discriminate between diseased and non-diseased populations. A global measure of biomarker effectiveness is the Youden index, the maximum difference between sensitivity, the probability of correctly classifying diseased individuals, and 1-specificity, the probability of incorrectly classifying health individuals. We present an approach for estimating the Youden index and associated optimal cut-point for a normally distributed biomarker that corrects for normally distributed random measurement error. We also provide confidence intervals for these corrected estimates using the delta method and coverage probability through simulation over a variety of situations. Applying these techniques to the biomarker thiobarbituric acid reaction substance (TBARS), a measure of sub-products of lipid peroxidation that has been proposed as a discriminating measurement for cardiovascular disease, yields a 50% increase in diagnostic effectiveness at the optimal cut-point. This result may lead to biomarkers that were once naively considered ineffective becoming useful diagnostic devices.
随机测量误差会削弱生物标志物区分患病和未患病群体的能力。生物标志物有效性的一个综合衡量指标是约登指数，即灵敏度（正确分类患病个体的概率）与1-特异度（错误分类健康个体的概率）之间的最大差值。我们提出了一种方法，用于估计服从正态分布的生物标志物的约登指数及相关最优切点，并对正态分布的随机测量误差进行校正。我们还使用德尔塔方法为这些校正后的估计值提供置信区间，并通过在各种情况下进行模拟来计算覆盖概率。将这些技术应用于生物标志物硫代巴比妥酸反应物质（TBARS），这是一种脂质过氧化副产物的测量指标，已被提议作为心血管疾病的鉴别测量指标，结果在最优切点处诊断有效性提高了50%。这一结果可能会使曾经被天真地认为无效的生物标志物成为有用的诊断工具。
