Covariate Effect on Constancy Assumption in Noninferiority Clinical Trials

• Activity Number: 355
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Siyan Xu*+ and Kerry Barker and Sandeep Menon and Ralph D'Agostino, Sr.
• Companies: Boston University and Pfizer Inc. and Pfizer Inc. and Boston University
• Keywords: Non-inferiority ; Constancy assumption ; Covariate ; Fixed margin method ; Synthesis method ; Sensitivity analysis

Abstract

Non-inferiority (NI) clinical trials are getting a lot of attention of late due to its direct application in biosimilar studies. NI is an indirect approach to demonstrate efficacy of a test treatment. One of the key assumptions on the NI test is constancy assumption, i.e., the effect of reference treatment is the same in current NI trials as in historical superiority trials. However, if a covariate interacts with the treatment arms, then changes in distribution of this covariate will likely result in violation of constancy assumption. In this paper, we propose four new NI methods and compare them with two existing methods to evaluate the change of background constancy assumption on the performance of these six methods. To achieve this goal, we study the impact of three elements: 1) Strength of covariate; 2) Degree of interaction between covariate and treatment and; 3) Differences in distribution between historical and current trials have on both the type I error rate and power using three different measures of association: difference, log relative risk and log odds ratio. Based on this research, we recommend using a modified covariate-adjustment fixed margin method.