Propensity score-integrated power prior approach for augmenting the control arm of a randomized controlled trial by incorporating multiple external data sources

• Published in: Journal of biopharmaceutical statistics Vol. 32; no. 1; pp. 158 - 169
• Main Authors: Lu, Nelson, Wang, Chenguang, Chen, Wei-Chen, Li, Heng, Song, Changhong, Tiwari, Ram, Xu, Yunling, Yue, Lilly Q.
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis 02.01.2022; Taylor & Francis Ltd
• Subjects: multiple external data sources; outcome-free design; power prior; propensity score; Real-world data; real-world evidence; outcome-free design; power prior; real-world evidence; multiple external data sources; Real-world data; propensity score
• ISSN: 1054-3406; 1520-5711
• DOI: 10.1080/10543406.2021.1998098

In this paper, a propensity score-integrated power prior approach is developed to augment the control arm of a two-arm randomized controlled trial (RCT) with subjects from multiple external data sources such as real-world data (RWD) and historical clinical studies containing subject-level outcomes and covariates. The propensity scores for the subjects in the external data sources versus the subjects in the RCT are first estimated, and then subjects are placed in different strata based on their estimated propensity scores. Within each propensity score stratum, a power prior is formulated with the information contributed by the external data sources, and Bayesian inference on the treatment effect is obtained. The proposed approach is implemented under the two-stage study design framework utilizing the outcome-free principle to ensure the integrity of a study. An illustrative example is provided to demonstrate the implementation of the proposed approach.