Conference Program

Propensity Score Stratified MAP Prior and Posterior Inference for Incorporating Information Across Multiple Potentially Heterogeneous Data Sources (303620)

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*Dooti Roy, Boehringer Ingelheim Pharmaceuticals, Inc. 
Martin Oliver Sailer, Boehringer Ingelheim Pharma GmbH & Co. KG 
Yaqian Zhu, University of Pennsylvania 
Zheng Zhu, Boehringer Ingelheim Pharmaceuticals, Inc. 

Keywords: Propensity score, treatment effect, Bayesian borrowing, schizophrenia;

Incorporation of external information is becoming increasingly common when designing clinical trials. Availability of multiple sources of information has inspired development of methodologies that account of potential heterogeneity not only between the prospective trial and the pooled external data sources but also between the different external data sources themselves.

Our approach proposes an intuitive way of handling such a scenario by using propensity score based stratification and then utilizing robust meta-analytic predictive priors for each stratum to incorporate the prior data to distinguish among different external data sources in each stratum.

Through extensive simulations, our approach proves to be more efficient and less biased than the currently available methods. This approach can be deployed while designing augmented single arm trial or while creating a synthetic control arm for a parallel, randomized, two armed design. We also apply our method in a real case study for Schizophrenia trials from the TransCelerate initiative.