title: Fully semiparametric Bayesian approach for modeling survival data with cure fraction.
abstract: In this paper, we consider a piecewise exponential model (PEM) with random time grid to develop a full semiparametric Bayesian cure rate model. An elegant mechanism enjoying several attractive features for modeling the randomness of the time grid of the PEM is assumed. To model the prior behavior of the failure rates of the PEM we assume a hierarchical modeling approach that allows us to control the degree of parametricity in the right tail of the survival curve. Properties of the proposed model are discussed in detail. In particular, we investigate the impact of assuming a random time grid for the PEM on the estimation of the cure fraction. We further develop an efficient collapsed Gibbs sampler algorithm for carrying out posterior computation. A Bayesian diagnostic method for assessing goodness of fit and performing model comparisons is briefly discussed. Finally, we illustrate the usefulness of the new methodology with the analysis of a melanoma clinical trial that has been discussed in the literature.
authors: Departamento de Estatística, Universidade Federal de Minas Gerais, Avenida Presidente Antônio Carlos, 6627, CEP 31270-901, Belo Horizonte-MG, Brasil.
authors: Fabio N
authors: FN
authors: Demarqui
authors: Dipak K
authors: DK
authors: Dey
authors: Rosangela H
authors: RH
authors: Loschi
authors: Enrico A
authors: EA
authors: Colosimo
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001699:Biometry / Q000379:methods*; D002986:Clinical Trials as Topic; D005260:Female; D006801:Humans; D008297:Male; D008545:Melanoma / Q000628:therapy; D015233:Models, Statistical; D016019:Survival Analysis; D016896:Treatment Outcome
keywords: Bayesian inference; Data augmentation; MCMC methods; Piecewise exponential model; Random partitions