Using the ROC curve for gauging treatment effect in clinical trials.
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.
Brumback
Lyndia C
LC
Department of Biostatistics, University of Washington, Box 357232, Seattle, Washington 98195-7232, USA. lynb@u.washington.edu
Pepe
Margaret S
MS
Alonzo
Todd A
TA
D000280:Administration, Inhalation; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D002648:Child; D017326:Clinical Trials, Phase III as Topic / Q000379:methods*; D003550:Cystic Fibrosis / Q000188:drug therapy; D003627:Data Interpretation, Statistical; D005260:Female; D005541:Forced Expiratory Volume / Q000187:drug effects; D006801:Humans; D008297:Male; D015337:Multicenter Studies as Topic; D012372:ROC Curve; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D018709:Statistics, Nonparametric; D014031:Tobramycin / Q000627:therapeutic use; D016896:Treatment Outcome
D000900:Anti-Bacterial Agents; D014031:Tobramycin