title: Two new covariate adjustment methods for non-inferiority assessment of binary clinical trials data.
abstract: In clinical trials, examining the adjusted treatment difference has become the preferred way to establish non-inferiority (NI) in cases involving a binary endpoint. However, current methods are inadequate in the area of covariate adjustment. In this paper, we introduce two new methods, nonparametric and parametric, of using the probability and probability (P-P) curve to address the issue of unadjusted categorical covariates in the traditional assessment of NI in clinical trials. We also show that the area under the P-P curve is a valid alternative for assessing NI using the adjusted treatment difference, and we compute this area using Mann-Whitney nonparametric statistics. Our simulation studies demonstrate that our proposed methods can not only control type I error at a predefined significance level but also achieve higher statistical power than those of traditional parametric and nonparametric methods that overlook covariate adjustment, especially when covariates are unbalanced in the two treatment groups. We illustrate the effectiveness of our methodology with data from clinical trials of a therapy for coronary heart disease.
authors.affiliation: Department of Biostatistics, Harbin Medical University, Harbin, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Hou
authors.forename: Victoria
authors.initials: V
authors.lastname: Ding
authors.forename: Kang
authors.initials: K
authors.lastname: Li
authors.forename: Xiao-Hua
authors.initials: XH
authors.lastname: Zhou
mesh_terms: D019540:Area Under Curve; D015982:Bias; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D017326:Clinical Trials, Phase III as Topic; D003198:Computer Simulation; D016001:Confidence Intervals; D003327:Coronary Disease / Q000188:drug therapy; D003627:Data Interpretation, Statistical; D015987:Effect Modifier, Epidemiologic; D006801:Humans; D015233:Models, Statistical; D008517:Phytotherapy; D028321:Plant Preparations / Q000627:therapeutic use; D011336:Probability; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012107:Research Design / Q000706:statistics & numerical data; D018709:Statistics, Nonparametric; D016896:Treatment Outcome
chemical_list: D028321:Plant Preparations