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Lookup NU author(s): Dr Faye Williamson
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
We propose a novel response‐adaptive randomization procedure for multi‐armed trials with continuous outcomes that are assumed to be normally distributed. Our proposed rule is non‐myopic, and oriented toward a patient benefit objective, yet maintains computational feasibility. We derive our response‐adaptive algorithm based on the Gittins index for the multi‐armed bandit problem, as a modification of the method first introduced in Villar et al. (Biometrics, 71, pp. 969‐978). The resulting procedure can be implemented under the assumption of both known or unknown variance. We illustrate the proposed procedure by simulations in the context of phase II cancer trials. Our results show that, in a multi‐armed setting, there are efficiency and patient benefit gains of using a response‐adaptive allocation procedure with a continuous endpoint instead of a binary one. These gains persist even if an anticipated low rate of missing data due to deaths, dropouts, or complete responses is imputed online through a procedure first introduced in this paper. Additionally, we discuss how there are response‐adaptive designs that outperform the traditional equal randomized design both in terms of efficiency and patient benefit measures in the multi‐armed trial context
Author(s): Williamson SF, Villar SS
Publication type: Article
Publication status: Published
Print publication date: 11/03/2020
Online publication date: 19/07/2019
Acceptance date: 24/06/2019
Date deposited: 13/04/2021
ISSN (print): 0006-341X
ISSN (electronic): 1541-0420
Publisher: Wiley-Blackwell Publishing Ltd.
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