Fusion designs and estimators for treatment effects.

ABSTRACT: While randomized trials remain the best evidence for treatment effectiveness, lack of generalizability often remains an important concern. Additionally, when new treatments are compared against existing standards of care, the potentially small benefit of the new treatment may be difficult to detect in a trial without extremely large sample sizes and long follow-up times. Recent advances in "data fusion" provide a framework to combine results across studies that are applicable to a given population of interest and allow treatment comparisons that may not be feasible with traditional study designs. We propose a data fusion-based estimator that can be used to combine information from two studies: (1) a study comparing a new treatment to the standard of care in the local population of interest

SUBMITTER: Breskin A 

PROVIDER: S-EPMC8237350 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature