Lifetime Data Anal - A parametric model fitting time to first event for overdispersed data: application to time to relapse in multiple sclerosis.

Tópicos

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Resumo

In this article, we propose a parametric model for the distribution of time to first event when events are overdispersed and can be properly fitted by a Negative Binomial distribution. This is a very common situation in medical statistics, when the occurrence of events is summarized as a count for each patient and the simple Poisson model is not adequate to account for overdispersion of data. In this situation, studying the time of occurrence of the first event can be of interest. From the Negative Binomial distribution of counts, we derive a new parametric model for time to first event and apply it to fit the distribution of time to first relapse in multiple sclerosis (MS). We develop the regression model with methods for covariate estimation. We show that, as the Negative Binomial model properly fits relapse counts data, this new model matches quite perfectly the distribution of time to first relapse, as tested in two large datasets of MS patients. Finally we compare its performance, when fitting time to first relapse in MS, with other models widely used in survival analysis (the semiparametric Cox model and the parametric exponential, Weibull, log-logistic and log-normal models).

Resumo Limpo

articl propos parametr model distribut time first event event overdispers can proper fit negat binomi distribut common situat medic statist occurr event summar count patient simpl poisson model adequ account overdispers data situat studi time occurr first event can interest negat binomi distribut count deriv new parametr model time first event appli fit distribut time first relaps multipl sclerosi ms develop regress model method covari estim show negat binomi model proper fit relaps count data new model match quit perfect distribut time first relaps test two larg dataset ms patient final compar perform fit time first relaps ms model wide use surviv analysi semiparametr cox model parametr exponenti weibul loglogist lognorm model

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