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Stat Methods Med Res ; 25(1): 336-51, 2016 Feb.
Article in English | MEDLINE | ID: mdl-22767866

ABSTRACT

Bayesian reasoning, survival analysis and multi-state models are used to assess survival times for Stage IV non-small-cell lung cancer patients and the evolution of the disease over time. Bayesian estimation is done using minimum informative priors for the Weibull regression survival model, leading to an automatic inferential procedure. Markov chain Monte Carlo methods have been used for approximating posterior distributions and the Bayesian information criterion has been considered for covariate selection. In particular, the posterior distribution of the transition probabilities, resulting from the multi-state model, constitutes a very interesting tool which could be useful to help oncologists and patients make efficient and effective decisions.


Subject(s)
Bayes Theorem , Carcinoma, Non-Small-Cell Lung/mortality , Lung Neoplasms/mortality , Biostatistics , Carcinoma, Non-Small-Cell Lung/pathology , Humans , Lung Neoplasms/pathology , Markov Chains , Monte Carlo Method , Neoplasm Staging , Regression Analysis , Survival Analysis
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