Leveraging External Data to Augment a Single Arm Study or the Control Arm of a Randomized Clinical Trial

Oregon Convention Center 

Incorporating external data into clinical trials has mainly been through using various matching methods for baseline characteristics to establish an external control arm or to augment a single-arm study or the control arm of a randomized controlled trial (RCT). However, matching the baseline characteristics between the trial subjects and the external subjects can only guarantee that the external subjects leveraged are comparable on the baseline characteristics. The difference between the two data sources may still exist due to contemporaneous and operational characteristics that are not captured in the baseline. Such differences are usually reflected in the outcomes data rather than in the subjects' baseline characteristics. In this talk, we present novel propensity-score integrated methods for augmenting a single-arm study first, and then extend it to augmenting the control arm of an RCT. The methods are explained using illustrative examples.