Should RECOVERY have used Response Adaptive Randomization? Evidence from a simulation study

Abstract

\n Background\n\nThe Randomised Evaluation of COVID-19 Therapy (RECOVERY) trial is aimed at addressing the urgent need to find effective treatments for patients hospitalised with suspected or confirmed COVID-19. The trial has had many successes, including discovering that dexamethasone is effective at reducing COVID-19 mortality, the first treatment to reach this milestone in a randomised controlled trial. Despite this, it continues to use standard or `fixed’ randomization (FR) to allocate patients to treatments. We assessed the impact of implementing response adaptive randomization (RAR) within RECOVERY using an array of performance measures, to learn if it could be beneficial going forward. This design feature has recently been implemented within the REMAP-CAP trial.\nMethods\n\nTrial data was simulated to closely match the data for patients allocated to either standard care or dexamethasone in the RECOVERY trial from March-June 2020, representing two out of five arms tested throughout this period. Two forms of FR and two forms of RAR were tested. Randomization strategies were performed at the whole trial level as well as within three pre-specified patient subgroups defined by patients’ respiratory support level.\nResults\n\nRAR strategies led to more patients being given dexamethasone and a lower mortality rate in the trial. Subgroup specific RAR reduced mortality rates even further. RAR did not induce any meaningful bias in treatment effect estimates, but reduced statistical power compared to FR, with subgroup level adaptive randomizations exhibiting the largest power reduction.\nConclusions\n\nUsing RAR within RECOVERY could have resulted in fewer deaths in the trial. However, a larger trial would have been needed to attain the same study power. This could potentially have prolonged the time to full approval of the drug, unless RAR itself led to an increased recruitment rate. Deciding how to balance the needs of patients within a trial and future patients who have yet to fall ill is an important ethical question of our time. RAR deserves to be considered as a design feature in future trials of COVID-19 and other diseases.