Mixture and non-mixture cure fraction models based on the generalized modified Weibull distribution with an application to gastric cancer data |
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| Authors: | Edson Z Martinez Jorge A Achcar Alexandre AA Jácome José S Santos |
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| Affiliation: | 1. Department of Social Medicine, University of São Paulo (USP), Ribeirão Preto School of Medicine, Brazil;2. Department of Medical Oncology, Barretos Cancer Hospital, Str. Antenor Duarte Villela, 1331 Barretos, Brazil;3. Department of Surgery and Anatomy, University of São Paulo (USP), Ribeirão Preto School of Medicine, Brazil |
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| Abstract: | The cure fraction models are usually used to model lifetime time data with long-term survivors. In the present article, we introduce a Bayesian analysis of the four-parameter generalized modified Weibull (GMW) distribution in presence of cure fraction, censored data and covariates. In order to include the proportion of “cured” patients, mixture and non-mixture formulation models are considered. To demonstrate the ability of using this model in the analysis of real data, we consider an application to data from patients with gastric adenocarcinoma. Inferences are obtained by using MCMC (Markov Chain Monte Carlo) methods. |
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| Keywords: | Survival analysis Bayesian analysis Generalized modified Weibull distribution Cure fraction model Gastric cancer |
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