4.5 Article

Using the ROC curve for gauging treatment effect in clinical trials

Journal

STATISTICS IN MEDICINE
Volume 25, Issue 4, Pages 575-590

Publisher

WILEY
DOI: 10.1002/sim.2345

Keywords

AUC regression; covariate adjustment; effect modification; non-parametric; Wilcoxon-Mann-Whitney test

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Non-parametric procedures such as the Wilcoxon rank-sum test, or equivalently the Mann-Whitney test, are often used to analyse data from clinical trials. These procedures enable testing for treatment effect, but traditionally do not account for covariates. We adapt recently developed methods for receiver operating characteristic (ROC) curve regression analysis to extend the Mann-Whitney test to accommodate covariate adjustment and evaluation of effect modification. Our approach naturally extends use of the Mann-Whitney statistic in a fashion that is analogous to how linear models extend the t-test. We illustrate the methodology with data from clinical trials of a therapy for Cystic Fibrosis. Copyright (c) 2005 John Wiley & Sons, Ltd.

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