Bayesian fusion forests for heterogeneous treatment effects on survival from randomised and real-world data

• URL: http://arxiv.org/abs/2607.29295v1
• Date: Fri, 31 Jul 2026 11:12:55 GMT
• Title: Bayesian fusion forests for heterogeneous treatment effects on survival from randomised and real-world data
• Abstract summary: We develop a nonparametric framework to estimate heterogeneous treatment effects on survival outcomes.<n>The framework relaxes the unconfoundedness assumption on the real-world data by assuming instead that the treatment effect transports across the two sources.<n>We combine the ACTG 175 trial with the Multicenter AIDS Cohort Study to estimate the effect of combination antiretroviral therapy for HIV.
• Score: 0.10705399532413612
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We develop the Bayesian fusion forest, a nonparametric framework to estimate heterogeneous treatment effects on survival outcomes by combining a randomised controlled trial and real-world data. The framework relaxes the unconfoundedness assumption on the real-world data by assuming instead that the treatment effect transports across the two sources. Our method opens up right- and interval-censored outcomes to data fusion. We model the survival time with an accelerated failure time decomposition into a shared baseline prognosis, a source-specific deviation, a treatment effect, and a confounding function. The confounding function absorbs the confounding bias in the real-world data. Each component receives a Bayesian tree ensemble prior. The shared baseline prognosis borrows strength across sources, while the deviation captures between-source heterogeneity. A hierarchical Dirichlet process mixture models the error distribution nonparametrically. A simulation study shows efficiency gains over a trial-only analysis across varying levels of confounding and between-source heterogeneity. We combine the ACTG 175 trial with the Multicenter AIDS Cohort Study to estimate the effect of combination antiretroviral therapy for HIV. The fusion identifies a benefit for nearly every patient whereas the trial alone is inconclusive.

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