Bayesian Analysis for Survival of Patients with Gastric Cancer in Iran


Background &
Objectives: Gastric cancer is one of the most common cancers in the world. The aim of thisstudy was to evaluate prognostic factors using Bayesian interval censoring analysis.
Methods: This is a historicalcohort study of 178 patients from February 2003 through January 2008, admitted with gastric cancer to onereferral hospital in Tehran. Age at diagnosis, sex, histology type, tumor grade, tumor size, pathologic stage,lymph node metastasis and distant of metastasis were entered into the analysis using Bayesian Weibull andExponential models. The term DIC was employed to find best model.
Results: The results showed that as ageincreased, the risk of death slightly increased significantly in both Weibull and Exponential models with similarresults. Patients with grater tumor size were also in higher risk of death followed by advanced pathologic stage.Neither the Weibull nor the Exponential models found sex, distant metastasis, histology type, tumor grade andlymph node metastasis to be prognostic factors. Based on DIC, Bayesian analysis of the Weibull model performedbetter than the Exponential model.
Conclusion: According to these results the early detection of patients atlower ages and in primary stages is important to increase the survival in patients with gastric cancer.