Response-adaptive randomization in clinical trials: from myths to practical considerations
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Response-adaptive randomization (RAR) is part of a wider class of data-dependent sampling algorithms, for which clinical trials have commonly been used as a motivating application. In that context, patient allocation to treatments is defined using the accrued data on responses to alter randomization probabilities, in order to achieve different experimental goals. RAR has received abundant theoretical attention from the biostatistical literature since the 1930's and has been the subject of heated debates. Recently it has received renewed consideration from the applied community due to some successful practical examples. Most position papers on the subject present a one-sided view on its use, which is of limited value for the non-expert. This work aims to address this gap by providing a critical, balanced and updated review of methodological and practical issues to consider when debating the use of RAR in clinical trials.
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