Multivariate Analysis of Prognostic Factors in Gastric Cancer Patients Using Additive Hazards Regression Models

Abstract

Background & <br/><b>Objectives</b>: Gastric cancer is the second leading cause of cancer death worldwide and is the most common type of cancer in Iran. The objective of this paper is to apply the additive hazards models to the study of survival of patients with gastric cancer and to compare results obtained by the additive hazards models and the Cox model. <br/><b>Methods</b>: We retrospectively studied 213 patients with gastric cancer who were registered in one referral cancer registry center in Tehran, Iran. Age at diagnosis, sex, presence of metastasis, tumor size, histology type, lymph node metastasis, and pathologic stages were entered into analysis using the Cox model and additive hazard models. To visualize a covariate effect over time, the estimated cumulative regression function by the Aalen’s model is examined. <br/><b>Results</b>: The five-year survival rate and the median life expectancy in the studied patients were 14.6% and 29.6 months, respectively. Multivariate Cox and Additive hazards models analysis identified that age at diagnosis, tumor size and pathologic stage were independent prognostic factors for the survival of patients with gastric cancer (P<0.05). Moreover, pathologic stage has a late or delayed effect according to the Aalen’s plot. Other clinicopathological characteristics were not statistically significant (P>0.05). <br/><b>Conclusion</b>: Since Cox and additive models give different aspects of the association between risk factors and the study outcome, it seems desirable to use together to give a more comprehensive understanding of data. Our results also suggest that early detection of patients in younger age and in primary stages is important to increase survival of patients with gastric cancer.