Strategic Survival Analysis of Gastric Cancer Patients for Augmented Reality

Abstract

Gastric cancer (GC) is the fifth most common type of cancer worldwide and the third leading cause of cancer-related death. The Cox model and accelerated failure time models are widely used in the modeling of survival data for various diseases. The goal of this study was to compare the performance of the Cox proportional hazard (PH) model and accelerated failure time (AFT) models in determining the factors that influence gastric cancer death. The data for this study was obtained from gastric cancer patients admitted to the Tikur Anbesa specialized hospital, between January 1, 2015, and February 29, 2020. A total of 409 gastric cancer patients were studied retrospectively. Cox proportional hazard and accelerated-failure-time (AFT) models were compared to identify an appropriate survival model that determines factors that affect the time to death of gastric cancer patients. To compare the performance of all models, the AIC, BIC, and Likelihood criteria were used. The analysis was carried out using the R statistical software.