R Functions for Sample Size and Probability Calculations for Assessing Consistency of Treatment Effects in Multi-Regional Clinical Trials

• Activity Number: 580
• Type: Contributed
• Date/Time: Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Mingyu Li*+ and Hui Quan and Joshua Chen and Yoko Tanaka and Peter Ouyang and Xiaolong Luo and Gang Li
• Companies: Celgene Corporation and sanofi-aventis and Merck & Co., Inc. and Eli Lilly and Company and Celgene Corporation and Celgene Corporation and Johnson & Johnson Pharmaceutical R&D, LLC
• Keywords: similarity ; random effect ; unconditional and conditional probability ; interaction test

Abstract

Multi-regional clinical trials have been widely used for efficient global new drug developments. Due to potential heterogeneity of patient populations, it is critical to evaluate consistency of treatment effects across different regions in a multi-regional trial in order to determine the applicability of the overall treatment effect to the patients in individual regions. Quan et al. (2010) proposed definitions for the assessments of consistency of treatment effects in multi-regional trials. To facilitate the application of their ideas to design multi-regional trials, in this paper, we provide the corresponding R functions for calculating the unconditional and conditional probabilities for demonstrating consistency in relationship with the overall/regional sample sizes and the anticipated treatment effects. Detailed step by step instructions and trial examples are also provided to illustrate the applications of these R functions.