Statistical monitoring of clinical trials with multiple co-primary endpoints using multivariate B-value

Cheng, Y., Ray, S. , Chang, M. and Menon, S. (2014) Statistical monitoring of clinical trials with multiple co-primary endpoints using multivariate B-value. Statistics in Biopharmaceutical Research, 6(3), pp. 241-250. (doi: 10.1080/19466315.2014.923324)

Abstract

This article develops methods of statistical monitoring of clinical trials with multiple co-primary endpoints, where success is defined as meeting both endpoints simultaneously. In practice, a group sequential design (GSD) method is used to stop trials early for promising efficacy, and conditional power (CP) is used for futility stopping rules. In this article, we show that stopping boundaries for the GSD with multiple co-primary endpoints should be the same as those for studies with single endpoints. Lan and Wittes proposed the B-value tool to calculate the CP of single endpoint trials and we extend this tool to calculate the CP for studies with multiple co-primary endpoints. We consider the cases of two-arm studies with co-primary normal and provide an example of implementation with simulated trial. A fixed-weight sample size reestimation approach based on CP is introduced.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ray, Professor Surajit
• Authors: Cheng, Y., Ray, S., Chang, M., and Menon, S.
• Subjects: H Social Sciences > HA Statistics
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Statistics in Biopharmaceutical Research
• Publisher: Taylor and Francis
• ISSN: 1946-6315
• ISSN (Online): 1946-6315