Estimation of survival and hazard curves of mixture Mirra cure rate model: Application to gastric and breast cancer data

In many applications related to time to event data, especially in the medical field, it is common the presence of a fraction of individuals not expecting to experience the event of interest, these individuals immune to the event or cured for the disease during the study are known as long–term survivors. To estimate survival and hazard curves, in this situation, it is common the use of Weibull cure rate model due to its great flexibility and simplicity. In this paper, we present the estimation of survival and hazard curves using a extension of Mirra model using the classical cure rate approach and applying it to gastric and breast cancer data. The inferences of interest were obtained using a Bayesian approach and the results achieved from this study showed that the Mirra model has a good fit and could be an useful alternative for estimation and shape prediction of survival and hazard curves for long– term survivors, especially for cancer data. The results could be extended using regression approach in order to identify risk factor that affects the survival probability.