Using Randomization Tests to Address Disruptions in Clinical Trials: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions

Abstract

1. AbstractRecent examples for unplanned external events are the global COVID-19 pandemic, the war in Ukraine, or most recently Hurricane Ian in Puerto Rico. Disruptions due to unplanned external events can lead to violation of assumptions in clinical trials. In certain situations, randomization tests can provide non-parametric inference that is robust to violation of the assumptions usually made in clinical trials. The ICH E9 (R1) Addendum on estimands and sensitivity analyses provides a guideline for aligning the trial objectives with strategies to address disruptions in clinical trials. In this paper, we embed randomization tests within the estimand framework to allow for inference following disruptions in clinical trials in a way that reflects recent literature. A stylized clinical trial is presented to illustrate the method, and a simulation study highlights situations when a randomization test that is conducted under the intention-to-treat principle can provide unbiased results.DisclaimerAs a service to authors and researchers we are providing this version of an accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proofs will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to these versions also. FundingThe author(s) reported there is no funding associated with the work featured in this article.