Application of a Non-Mixture Cure Rate Model for Analyzing Survival of Patients with Brain Cancer

Abstract

The results of the discovery of very good treatments for all types of cancer in recent years have led to a decrease in mortality. We deal with these observations as cure or immune and models for survival data which involve cure fraction are known as cure rate models or long-term survival models. Methods and Materials, during the past few decades the statistical methods for survival analysis of data have found applications in wide range of fields especially in medical researches, The aim of this research is to study the most factors affecting of brain cancer in Erbil city using Weibull parametric and Logistic-Cox non mixture cure survival models for modelling and identifying the most affecting factors of brain cancer in our data. The data used in this research was obtained from Rzgari Hospital for Cancer in the Kurdistan Region of Iraq – Erbil. The results for our data showed that Extent and Histopathology are the most important factors affecting the brain cancer.