All Times EDT
Keywords: real-world data, historical borrowing, propensity score, Bayesian
In many orphan diseases and pediatric indications, conducting randomized controlled trials may be unsuitable due to ethical concerns, limited populations, timelines, or cost. Leveraging information on the control through a prior can potentially reduce sample size requirement. However, unless an objective prior is used to impose complete ignorance for the parameter being estimated, it results in biased estimates and inflated type-I error. Hence, it is essential to assess both confirmatory and contradictory knowledge during prior construction to avoid “cherry-picking” advantageous information. For this purpose, propensity score methods are employed to minimize selection bias by incorporating supplemental control subjects and accounting for their similarity in terms of pre-treatment characteristics to the subjects in the current trial. In this paper, we consider single experimental arm in the current trial and the control arm is completely borrowed from the supplemental data . The simulation experiments show that the proposed method reduces prior and data conflict and improves the precision of the of the average treatment effect.