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Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data

Identifieur interne : 001A20 ( Main/Exploration ); précédent : 001A19; suivant : 001A21

Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data

Auteurs : Jiin Choi [Corée du Sud] ; Stewart J. Anderson [États-Unis] ; Thomas J. Richards [États-Unis] ; Wesley K. Thompson [États-Unis]

Source :

Journal of applied statistics [ 0266-4763 ] ; 2014.

RBID : PMC:4157686

Abstract

SUMMARY

We implement a joint model for mixed multivariate longitudinal measurements, applied to the prediction of time until lung transplant or death in idiopathic pulmonary fibrosis. Specifically, we formulate a unified Bayesian joint model for the mixed longitudinal responses and time-to-event outcomes. For the longitudinal model of continuous and binary responses, we investigate multivariate generalized linear mixed models using shared random effects. Longitudinal and time-to-event data are assumed to be independent conditional on available covariates and shared parameters. A Markov chain Monte Carlo (MCMC) algorithm, implemented in OpenBUGS, is used for parameter estimation. To illustrate practical considerations in choosing a final model, we fit 37 different candidate models using all possible combinations of random effects and employ a Deviance Information Criterion (DIC) to select a best fitting model. We demonstrate the prediction of future event probabilities within a fixed time interval for patients utilizing baseline data, post-baseline longitudinal responses, and the time-to-event outcome. The performance of our joint model is also evaluated in simulation studies.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4157686

DOI: 10.1080/02664763.2014.909784
PubMed: 25214700
PubMed Central: 4157686

Affiliations:

Le document en format XML

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Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data

Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data

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