The basic structure of a randomized comparative clinical trial is quite simple. A candidate population that meets the admissibility criteria is recruited. Each candidate who consents to participate is randomly allocated to an experimental treatment or to one or more “controls.” The participants are followed and data are collected until a pre-specified ending criterion is met. To ensure the integrity and usefulness of the trial, it is important that there be sufficient numbers of participants, they be followed as specified without losses, and all desired data be collected. Failure to do so increasingly threatens the informativeness of the trial, and if the losses are biased in some way, the validity of the trial can also be jeopardized. Medical research has become quite adept at meeting the design and operational challenges posed, but the COVID-19 pandemic has inflicted unexpected damages to ongoing trials.
The enormous investments involved and the substantial adverse consequences of failing to gain the desired information from these trials put enormous pressure on our field to find ways of patching the broken trials. In this brief paper, we provide one novel solution to these problems: using simulation to attempt to rescue these studies and make up for the lost data.
