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BMC Medical Research Methodology

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Open Access 01-12-2022 | Research

Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective

Authors: Elja Arjas, Dario Gasbarra

Published in: BMC Medical Research Methodology | Issue 1/2022

Abstract

Background

Adaptive designs offer added flexibility in the execution of clinical trials, including the possibilities of allocating more patients to the treatments that turned out more successful, and early stopping due to either declared success or futility. Commonly applied adaptive designs, such as group sequential methods, are based on the frequentist paradigm and on ideas from statistical significance testing. Interim checks during the trial will have the effect of inflating the Type 1 error rate, or, if this rate is controlled and kept fixed, lowering the power.

Results

The purpose of the paper is to demonstrate the usefulness of the Bayesian approach in the design and in the actual running of randomized clinical trials during phase II and III. This approach is based on comparing the performance of the different treatment arms in terms of the respective joint posterior probabilities evaluated sequentially from the accruing outcome data, and then taking a control action if such posterior probabilities fall below a pre-specified critical threshold value. Two types of actions are considered: treatment allocation, putting on hold at least temporarily further accrual of patients to a treatment arm, and treatment selection, removing an arm from the trial permanently. The main development in the paper is in terms of binary outcomes, but extensions for handling time-to-event data, including data from vaccine trials, are also discussed. The performance of the proposed methodology is tested in extensive simulation experiments, with numerical results and graphical illustrations documented in a Supplement to the main text. As a companion to this paper, an implementation of the methods is provided in the form of a freely available R package ’barts’.

Conclusion

The proposed methods for trial design provide an attractive alternative to their frequentist counterparts.

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Title: Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective
Authors: Elja Arjas
Dario Gasbarra
Publication date: 01-12-2022
Publisher: BioMed Central
Published in: BMC Medical Research Methodology / Issue 1/2022
Electronic ISSN: 1471-2288
DOI: https://doi.org/10.1186/s12874-022-01526-8

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective

Abstract

Background

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Results

Conclusion

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