Adaptively Combining Randomized and External Control Data Using a Mixture Prior in the Presence of Heterogeneity

2026-10-07

AI Summary

This study addresses the challenge of safely incorporating external control data in randomized trials when resources are limited and patient heterogeneity exists. To this end, we propose a hybrid group sequential Bayesian design. Its core innovation lies in introducing an adaptive mixture prior that dynamically calibrates the degree of external information borrowing based on internal-external data congruence, while enabling subgroup-level efficacy comparisons and timely enrollment stopping. By integrating Bayesian inference, group sequential methodology, and survival analysis techniques, the proposed approach achieves efficient data borrowing while rigorously preserving the validity of statistical inference. Simulation studies demonstrate that this strategy outperforms existing methods for external data integration, substantially improving clinical trial efficiency.

Abstract

When resources are limited in a randomized trial, a common strategy is to augment data from the control arm with external controls. We propose a hybrid group sequential Bayesian design that uses this approach to compare time-to-event distributions. The design allows between-treatment effects to differ between patient subgroups, and adaptively combines subgroups that have similar hazard functions. The aim is to reduce the control arm sample size without compromising the validity of comparative inferences due to systematic trial-versus-external data differences. The model borrows external control data dynamically by using a self-adapting mixture prior, which is a weighted average of a non-informative prior and an informative prior constructed from the external controls. The amount of borrowing is proportional to the agreement between the randomized and external controls. At each interim analysis, the design compares the treatments in each subgroup, and if inferiority or superiority is concluded stops accrual for that subgroup. Simulations show that the proposed design outperforms other methods for incorporating external control data in a randomized trial, and improves efficiency.

Problem

• external control data
• randomized trial
• heterogeneity
• sample size reduction
• time-to-event

Innovation

• Bayesian group sequential design
• Mixture prior
• External control data
• Time-to-event analysis
• Adaptive borrowing