Semi-supervised mixture multi-source exchangeability model for leveraging real-world data in clinical trials.

ABSTRACT: The traditional trial paradigm is often criticized as being slow, inefficient, and costly. Statistical approaches that leverage external trial data have emerged to make trials more efficient by augmenting the sample size. However, these approaches assume that external data are from previously conducted trials, leaving a rich source of untapped real-world data (RWD) that cannot yet be effectively leveraged. We propose a semi-supervised mixture (SS-MIX) multisource exchangeability model (MEM); a flexible, two-step Bayesian approach for incorporating RWD into randomized controlled trial analyses. The first step is a SS-MIX model on a modified propensity score and the second step is a MEM. The first step targets a representative subgroup of individuals from the trial population and the second

SUBMITTER: Haine LMF 

PROVIDER: S-EPMC11247180 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature