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A Comparison Between Cox Proportional Hazard Models And Logistic Regression On Prognostic Factors In Gastric Cancer
Abstract
Material and methods: To determine the independent prognostic factors reducing survival time for gastric cancer, we compared the parametric methods (logistic regression) and non-parametric methods (Cox proportional hazard models) applied to patients who registered
in one cancer registry center located in southern Iran.
Results: Of 442, 266 (60.2 %) died. In multivariate analyses using the Cox proportional hazard model, Age at diagnosis (P = 0.018, Hazard
rate= 1.84), grade of tumor (P = 0.018, Hazard rate=1.56), and metastasis (P = 0.004, Hazard rate=1.53) were the most independent
prognostic factors. As well as, using the stepwise logistic regression model, Age at diagnosis, (P = 0.005, Odds Ratio=1.01), grade of tumor
(P=0.025, OR=1.95), and metastasis (P<0.001, OR=2.81) were also the most independent factors who affected on survival.
Conclusion: Although regression coefficients are not all the same, these three factors are the most prognostic factors that affect on survival
of gastric patients in both multivariate analyses.