A review of survival analysis and brain tumor patient data

Survival analysis is used to analyze and interpret data that occurs in the period of time until the occurrence of a situation that is wanted to be investigated. Due to the censored nature of the data to be used in survival analysis and generally having a distorted distribution, the results obtained by parametric methods are not healthy, so non-parametric methods are used. In this study, it was aimed to examine the survival probability of 220 patients diagnosed with brain tumors at Malatya Education and Research Hospital between 01.01.2010 and 31.12.2020. For this purpose, Cox Regression and Kaplan-Meier analysis were performed based on the age, gender, brain tumor diagnosis code, spread, treatment duration, and result (presence/absence of death) variables of the patients. As a result of the analysis, the gender, age, and brain tumor diagnosis code variables examined were not found to be statistically significant, while the spread variable was found to be statistically significant. Keywords: Survival Analysis, Cox Regression, Kaplan-Meier Method, Censored Data, Glioma.