Gastric Cancer Survival Analysis: Applying the Bayesian Mixture Cure Rate Frailty Models

Bayesian mixture cure rate frailty model is a model used in survival analysis by controlling frailty when the fraction of cured individuals exists. The present study was performed as the first systematic review in survival analysis with cure fraction. The aim of this systematic review was to study and evaluate the related studies on Bayesian mixture cure rate frailty model. Also, this model was used to demonstrate its importance and applicability in determining the variables affecting the survival of patients with gastric cancer.

This systematic review was done based on the PRISMA guideline by considering related searching keywords in PubMed, Scopus, Science Direct, Web of Science, and Google Scholar. Also, Bayesian mixture cure rate frailty model was used to analyze gastric cancer data.

In the beginning, 882 studies related to survival analysis of cure rate model were found. Finally, by reading the full-text, only 4 related studies were found based on the inclusion and exclusion criteria. In these studies, semi-parametric models and parametric model with Weibull distribution were used for time-to-event data. Also, based on the results of the model, significant and affective variables on the survival of patients with gastric cancer were found.

According to the results of this study, in the cure model, choice of proper distribution for the frailty variable and baseline distribution can influence the results. It was also found that place of residence, chemotherapy, morphology, and metastasis are effective variables on survival of patients with gastric cancer.