Sample size calculation for multi-arm parallel design with restricted mean survival time

Author:

Chen Yaxian1,Lam Kwok Fai12ORCID,Xu Jiajun3

Affiliation:

1. Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong

2. Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore

3. Janssen Research & Development, China

Abstract

With the recent advances in oncology treatment, restricted mean survival time (RMST) is increasingly being used to replace the routine approach based on hazard ratios in randomized controlled trials for time-to-event outcomes. While RMST has been widely applied in single-arm and two-arm designs, challenges still exist in comparing RMST in multi-arm trials with three or more groups. In particular, it is unclear in the literature how to compare more than one intervention simultaneously or perform multiple testing based on RMST, and sample size determination is a major obstacle to its penetration to practice. In this paper, we propose a novel method of designing multi-arm clinical trials with right-censored survival endpoint based on RMST that can be applied in both phase II/III settings using a global [Formula: see text] test as well as a modeling-based multiple comparison procedure. The framework provides a closed-form sample size formula built upon a multi-arm global test and a sample size determination procedure based on multiple-comparison in the phase II dose-finding study. The proposed method enjoys strong robustness and flexibility as it requires less a priori set-up than conventional work, and obtains a smaller sample size while achieving the target power. In the assessment of sample size, we also incorporate practical considerations, including the presence of non-proportional hazards and staggered patient entry. We evaluate the validity of our method through simulation studies under various scenarios. Finally, we demonstrate the accuracy and stability of our method by implementing it in the design of two real clinical trial examples.

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

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