Bayesian Multivariate Joint Modeling for Multiple Events Time Data and Survival

Abstract

Individuals may experience multiple recurrent events and a dependent terminal event during their life period of a disease. Follow-up may be interrupted for some reasons. Also, death can stop the follow-up. Therefore, it is considered as a terminal event. In this article, we propose a Bayesian multivariate joint frailty model that jointly analyzes two types of recurrent events with a dependent terminal event. The Markov chain Monte Carlo methods are used to estimate the posterior distributions of model parameters. The performance of this approach is examined based on simulation study using exponential distribution. We apply the proposed method to a real dataset on breast cancer, which motivated this research. The main purpose was to model the dependency between multiple recurrent events (locoregional and metastatic) and the terminal event (death) after a breast cancer. Funding: This work was supported by tarbiat modares university, faculty of medical science. The collection of cancer data used in this study was supported by Shahid Beheshti Breast Cancer Research Center in Iran. Declaration of Interest: The authors declare that they have no competing interests.