West Asia Organization for Cancer Prevention (WAOCP), APOCP's West Asia Chapter. Asian Pacific Journal of Cancer Prevention 1513-7368 19 3 2018 03 01 Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients 749 753 57627 10.22034/APJCP.2018.19.3.749 EN Danial Habibi Department of Biostatistics, Faculty of Medicine, Arak University of Medical Sciences, Arak,Iran. 0000-0003-4080-1809 Mohammad Rafiei Department of Biostatistics, Faculty of Medicine, Arak University of Medical Sciences, Arak,Iran. Ali Chehrei Pars Clinicopathology Clinicopathology Laboratory, Arak, Iran. Zahra Shayan Trauma Research Center, Department of Community Medicine, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran. Soheil Tafagodi Department of Biostatistics, Faculty of Medicine, Arak University of Medical Sciences, Arak,Iran. Journal Article 2017 09 18 Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer.<br />This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and<br />parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in<br />unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike<br />Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that<br />all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma<br />provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis,<br />the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest,<br />largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes,<br />to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model<br />(log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models<br />outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. https://journal.waocp.org/article_57627_f9bc55de7eecc12c33904c795c73d9e4.pdf