Open Access
June 2016 Flexible Bayesian Survival Modeling with Semiparametric Time-Dependent and Shape-Restricted Covariate Effects
Thomas A. Murray, Brian P. Hobbs, Daniel J. Sargent, Bradley P. Carlin
Bayesian Anal. 11(2): 381-402 (June 2016). DOI: 10.1214/15-BA954


Presently, there are few options with available software to perform a fully Bayesian analysis of time-to-event data wherein the hazard is estimated semi- or non-parametrically. One option is the piecewise exponential model, which requires an often unrealistic assumption that the hazard is piecewise constant over time. The primary aim of this paper is to construct a tractable semiparametric alternative to the piecewise exponential model that assumes the hazard is continuous, and to provide modifiable, user-friendly software that allows the use of these methods in a variety of settings. To accomplish this aim, we use a novel model formulation for the log-hazard based on a low-rank thin plate linear spline that readily facilitates adjustment for covariates with time-dependent and proportional hazards effects, possibly subject to shape restrictions. We investigate the performance of our model choices via simulation. We then analyze colorectal cancer data from a clinical trial comparing the effectiveness of two novel treatment regimes relative to the standard of care for overall survival. We estimate a time-dependent hazard ratio for each novel regime relative to the standard of care while adjusting for the effect of aspartate transaminase, a biomarker of liver function, that is subject to a non-decreasing shape restriction.


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Thomas A. Murray. Brian P. Hobbs. Daniel J. Sargent. Bradley P. Carlin. "Flexible Bayesian Survival Modeling with Semiparametric Time-Dependent and Shape-Restricted Covariate Effects." Bayesian Anal. 11 (2) 381 - 402, June 2016.


Published: June 2016
First available in Project Euclid: 14 May 2015

zbMATH: 1357.62281
MathSciNet: MR3471995
Digital Object Identifier: 10.1214/15-BA954

Primary: 62F15 , 62N86
Secondary: 62F30

Keywords: Bayesian methods , colorectal cancer , penalized splines , semiparametric methods , shape-restricted effects , Survival analysis , time-dependent effects

Rights: Copyright © 2016 International Society for Bayesian Analysis

Vol.11 • No. 2 • June 2016
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