Prognostic Factors in Gastric Cancer Using Log-Normal Censored Regression Model (Report‪)‬

Background & objectives: Gastric cancer is one of the most common cancers in the world. It is rarely detected early, and the prognosis remains poor. Cox proportional hazard model is used to examine the relationship between survival and covariates. Parametric survival models such as log normal regression model can also be used for this analysis. We used log normal regression model in this study to evaluate prognostic factors in gastric cancer and compared with Cox model. Methods: We retrospectively studied the 746 patients diagnosed with gastric cancer admitted in a referral hospital in Tehran, Iran, from February 2003 through January 2007. Age at diagnosis, sex, extent of wall penetration, histology type, tumour grade, tumour size, pathologic stage, lymph node metastasis and presence of metastasis were entered into a log normal model. Hazard rate (HR) was employed to interpret the risk of death and the results were compared with Cox regression. The AIC (Akaike Information Criterion) was employed to compare the efficiency of models.