Bayesian Mediation Analysis for Time-to-Event Outcome: Investigating Racial Disparity in Breast Cancer Survival

Document Type

Article

Publication Date

2-8-2025

Publication Title

Communications in Statistics: Theory and Methods

Abstract

Mediation analysis is conducted to make inferences on effects of mediators that intervene the relationship between an exposure variable and an outcome. Bayesian mediation analysis (BMA) naturally considers the hierarchical structure of the effects from the exposure variable to mediators and then to the outcome. We propose three BMA methods on survival outcomes, where mediation effects are measured in terms of hazard rate, survival time, or log of survival time respectively. In addition, we allow setting a limited survival time in the time-to-event analysis. The methods are validated by comparing the estimation precision at different scenarios through simulations. The three methods all give effective estimates. Finally, the methods are applied to the Surveillance, Epidemiology, and End Results Program (SEER) supported special studies to explore the racial disparity in breast cancer survivals. The included variable completely explained the observed racial disparities. We provide visual aids to help with the result interpretations.

First Page

242

Last Page

258

PubMed ID

39829950

Volume

54

Issue

1

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