Combining Non-randomized and Randomized Data in Clinical Trials Using Commensurate Priors.

ABSTRACT: Randomization eliminates selection bias, and attenuates imbalance among study arms with respect to prognostic factors, both known and unknown. Thus, information arising from randomized clinical trials (RCTs) is typically considered the gold standard for comparing therapeutic interventions in confirmatory studies. However, RCTs are limited in contexts wherein patients who are willing to accept a random treatment assignment represent only a subset of the patient population. By contrast, observational studies (OSs) often enroll patient cohorts that better reflect the broader patient population. However, OSs often suffer from selection bias, and may yield invalid treatment comparisons even after adjusting for known confounders. Therefore, combining information acquired from OSs with data from

SUBMITTER: Zhao H 

PROVIDER: S-EPMC5404417 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature