Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-varying Covariates

TL;DR

This paper introduces Bayesian nonparametric Weibull delegate racing (WDR), a flexible survival analysis model capable of handling competing events, covariates, and various data complexities, with demonstrated superior performance on synthetic and real datasets.

Contribution

The paper presents WDR, a novel Bayesian nonparametric survival model that accommodates nonlinear covariate effects, competing risks, and data truncation, with an efficient inference algorithm and practical R implementation.

Findings

WDR outperforms benchmark methods in synthetic data analysis.

WDR effectively models nonlinear covariate effects in real datasets.

WDR uncovers new insights in disease progression and biomarker effects.

Abstract

We propose Bayesian nonparametric Weibull delegate racing (WDR) for survival analysis with competing events and achieve both model interpretability and flexibility. Utilizing a natural mechanism of surviving competing events, we assume a race among a potentially infinite number of sub-events. In doing this, WDR accommodates nonlinear covariate effects with no need of data transformation. Moreover, WDR is able to handle left truncation, time-varying covariates, different types of censoring, and missing event times or types. We develop an efficient MCMC algorithm based on Gibbs sampling for Bayesian inference and provide an \texttt{R} package. Synthetic data analysis and comparison with benchmark approaches demonstrate WDR's outstanding performance and parsimonious nonlinear modeling capacity. In addition, we analyze two real data sets and showcase advantages of WDR. Specifically, we study time to death of three types of lymphoma and show the potential of WDR in modeling nonlinear covariate effects and discovering new diseases. We also use WDR to investigate the age at onset of mild cognitive impairment and interpret the accelerating or decelerating effects of biomarkers on the progression of Alzheimer's disease.