Bayesian Clustering Prior With Overlapping Indices for Effective Use of Multisource External Data

Authors

Xuetao Lu
J Jack Lee

Language

English

Publication Date

9-15-2025

Journal

Statistical Methods in Medical Research

DOI

10.1177/09622802251367439

PMID

40953124

PMCID

PMC12669405

PubMedCentral® Posted Date

9-15-2025

PubMedCentral® Full Text Version

Post-print

Abstract

The use of external data in clinical trials offers numerous advantages, such as reducing enrollment, increasing study power, and shortening trial duration. In Bayesian inference, information in external data can be transferred into an informative prior for future borrowing (i.e. prior synthesis). However, multisource external data often exhibits heterogeneity, which can cause information distortion during the prior synthesizing. Clustering helps identifying the heterogeneity, enhancing the congruence between synthesized prior and external data. Obtaining optimal clustering is challenging due to the trade-off between congruence with external data and robustness to future data. We introduce two overlapping indices: the overlapping clustering index and the overlapping evidence index . Using these indices alongside a K-means algorithm, the optimal clustering result can be identified by balancing this trade-off and applied to construct a prior synthesis framework to effectively borrow information from multisource external data. By incorporating the (robust) meta-analytic predictive (MAP) prior within this framework, we develop (robust) Bayesian clustering MAP priors. Simulation studies and real-data analysis demonstrate their advantages over commonly used priors in the presence of heterogeneity. Since the Bayesian clustering priors are constructed without needing the data from prospective study, they can be applied to both study design and data analysis in clinical trials.

Keywords

Information borrowing, real-world data, evidence synthesis, heterogeneity, clustering, prior data congruency, prior robustness

Published Open-Access

yes

Recommended Citation

Xuetao Lu and J Jack Lee, "Bayesian Clustering Prior With Overlapping Indices for Effective Use of Multisource External Data" (2025). Faculty, Staff and Student Publications. 6068.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/6068