A1020
Title: Sicure: An R-package for single-index mixture cure models - application to a cardiotoxicity dataset
Authors: Beatriz Pineiro-Lamas - Universidade da Coruna (Spain) [presenting]
Ana Lopez-Cheda - University of A Coruna (Spain)
Ricardo Cao - University of Coruna (Spain)
Abstract: In survival analysis, there are situations in which not all subjects are susceptible to the final event. For example, if the event is a cancer therapy-related adverse effect, there will be a fraction of patients (considered cured) who will never experience it. Mixture cure models address this by estimating both the probability of cure and the survival function for the uncured subjects. In the literature, nonparametric estimation of these functions focuses on continuous univariate covariates. However, in clinical practice, it is common to collect several patient characteristics and even medical images. The R package sicure provides a set of functions related to the implementation of single-index mixture cure models that can handle a vector covariate under the assumption that the survival function depends on it through an unknown linear combination that can be estimated by maximum likelihood. This approach can be easily extended to functional covariates. The implementation of a nonparametric estimator for the density function of the uncured individuals is also included. Although the use of this package is illustrated with a medical dataset, it may be useful in any other field that involves a time variable, an uncensoring indicator, more than one covariate, and the presence of a cure fraction.
