R functions for sample size and probability calculations for assessing consistency of treatment effects in multi-regional clinical trials

4Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Li, M., Quan, H., Chen, J., Tanaka, Y., Ouyang, P., Luo, X., & Li, G. (2012). R functions for sample size and probability calculations for assessing consistency of treatment effects in multi-regional clinical trials. Journal of Statistical Software, 47. https://doi.org/10.18637/jss.v047.c01

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free