Adjusting the generalized ROC curve for covariates
Adjusting the generalized ROC curve for covariates
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DOI：
10.1002/sim.1908
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发表时间：
2004-11-15
影响因子：
2
通讯作者：
Reiser, B
中科院分区：
文献类型：
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作者：
Schisterman, EF;Faraggi, D;Reiser, B
受试者工作特征 (ROC) 曲线，特别是曲线下面积 (AUC)，被广泛用于检查诊断标志物的有效性。诊断标记物及其相应的 ROC 曲线可能会受到协变量的强烈影响。当多个诊断标志物可用时，它们可以通过最佳线性组合来组合，使得该组合的ROC曲线下的面积在所有可能的线性组合中最大化。在本文中，我们讨论了这种线性组合的协变量效应，假设多个标记（可能经过转换）遵循多元正态分布。当标记物针对协变量进行调整时，估计该线性组合的 ROC 曲线，并导出相应 AUC 的近似置信区间。使用可获取年龄和性别协变量信息的两种冠心病生物标志物的示例来说明该方法。版权所有 (C) 2004 John Wiley Sons, Ltd.
Receiver operating characteristic (ROC) curves and in particular the area under the curve (AUC), are widely used to examine the effectiveness of diagnostic markers. Diagnostic markers and their corresponding ROC curves can be strongly influenced by covariate variables. When several diagnostic markers are available, they can be combined by a best linear combination such that the area under the ROC curve of the combination is maximized among all possible linear combinations. In this paper we discuss covariate effects on this linear combination assuming that the multiple markers, possibly transformed, follow a multivariate normal distribution. The ROC curve of this linear combination when markers are adjusted for covariates is estimated and approximate confidence intervals for the corresponding AUC are derived. An example of two biomarkers of coronary heart disease for which covariate information on age and gender is available is used to illustrate this methodology. Copyright (C) 2004 John Wiley Sons, Ltd.