Document Type: Original Article

Authors

1 Modeling of Noncommunicable Diseases Research Center, Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran

2 Student Research Center, Hamadan University of Medical Sciences, Hamadan, Iran

3 Health Center, Ilam University of Medical Sciences and Health Services, Ilam, Iran

4 Department of General Surgery, Faculty of Medicine, Hamadan University of Medical Sciences and Health Services, Hamadan, Iran

5 Research Center for Molecular Medicine, Department of Microbiology, Faculty of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran

Abstract

Background: Gastric cancer is the second leading cause of cancer death. The aim of this study was to determine the survival rate affected by risk factors in patients with gastric adenocarcinoma.Methods: We performed this retrospective cohort study on patients diagnosed with gastric adenocarcinoma during 2005-2012 in Hamadan, Iran. All patients with pathological diagnosis enrolled in the study. The effects of patients’ demographical and pathological data were assessed in terms of survival. The univariate and multivariate Weibull models were used to determine the effects of these factors on survival rate. Data was analyzed by SPSS16 and STATA10 software.Results: A total of 112 gastric adenocarcinoma patients were followed. Patients included 74 (66.1%) males. During the follow-up, 102 (91.1) patients died. Patients’ had a mean (SD) survival of 21.9 (1.9) months and a median survival of 15 months. The “one-, three- and five-year survival rates were 62%, 16% and 9% respectively. The results showed that metastasis, chemotherapy, tumor site and grade had statistically significant impacts on patient survival.Conclusion: A potentially important role for tumor grade, tumor site, metastasis, and pathologic stage of disease existed in terms of patient survival after surgery. The current research has indicated that neoadjuvant treatment increased survival in patients with gastric adenocarcinoma. It is expected that the prognostic model based on the mentioned factors may assist individual risk stratification and help in the planning of potential forthcoming studies.