Affiliations: [a] Division of Biometrics IV, Office of Biometrics/OTS/CDER/FDA, Silver Spring, MD, USA | [b] Division of Antiviral Drug Products, Office of Antimicrobial Product/OND/CDER/FDA, Silver Spring, MD, USA | Division of Biostatistics, Food and Drug Administration, Rockville, MD, USA
Abstract: The traditional fixed margin approach for evaluating an experimental treatment through an active-controlled noninferiority trial is simple and straightforward. However its utility is highly dependent on the ability of the experimental data to satisfy the constancy assumption. If the constancy assumption is violated, other approaches must be used. One such approach is the recently described covariate-adjustment methodology. This approach permits more flexibility and improved discriminatory capacity compared to the fixed margin approach. However, the absence of a declared pre-determined noninferiority margin during the planning stage can lead to data analysis disputes between clinical trial sponsors and regulatory agencies. In this article, we present an adaptive noninferiority margin and sample size adjustment strategy implementing the covariate adjustment approach. We will demonstrate that the covariate-adjusted approach not only provides improved decision making quality, but also maintains implementation simplicity.
Keywords: Noninferiority margin, adaptive adjustment, constancy assumption, fixed margin approach, generalized linear model