Response-adaptive treatment randomization for multiple comparisons of treatments with recurrent event responses

Author:

Gao Jingya1,Hu Feifang2ORCID,Cheung Siu Hung3ORCID,Su Pei-Fang4

Affiliation:

1. School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China;

2. Department of Statistics, George Washington University, Washington, DC, USA;

3. Department of Statistics, The Chinese University of Hong Kong, Hong Kong, China;

4. Department of Statistics, National Cheng Kung University, Tainan, Taiwan

Abstract

Recurrent event responses are frequently encountered during clinical trials of treatments for certain diseases, such as asthma. The recurrence rates of different treatments are often compared by applying the negative binomial model. In addition, a balanced treatment-allocation procedure that assigns the same number of patients to each treatment is often applied. Recently, a response-adaptive treatment-allocation procedure has been developed for trials with recurrent event data, and has been shown to be superior to balanced treatment allocation. However, this response-adaptive treatment allocation procedure is only applicable for the comparison of two treatments. In this paper, we derive response-adaptive treatment-allocation procedures for trials which comprise several treatments. As pairwise comparisons and multiple comparisons with a control are two common multiple-testing scenarios in trials with more than two treatments, corresponding treatment-allocation procedures for these scenarios are also investigated. The redesign of two clinical studies illustrates the clinical benefits that would be obtained from our proposed response-adaptive treatment-allocation procedures.

Funder

China Postdoctoral Science Foundation

Ministry of Science and Technology

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

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