Objective:To construct a Logistic regression model based on baseline CT to predict neoadjuvant chemotherapy re-sponse in advanced gastric cancer.Methods:Pretherapeutic and posttreatment CT imaging data and clinical data of 156 patients with advanced gastric cancer receiving neoadjuvant chemotherapy were retrospectively collected.The collected cases were randomly assigned into the training cohort(n=117)and the validation cohort(n=39)at a ratio of 3∶1.In the training cohort,the univariate analyse were performed to explore the relationship between relevant pretherapeutic indicators and the response of gastric cancer,and the indicators with statistical difference were included in a multivariate Logistic regression to determine the independent predictors.Subsequently,a Logistic regression model was constructed based on above independent predictors.Predictive performance of the model was evaluated by the receiver operating characteristic curve(ROC)and area under the ROC curve(AUC).In the validation cohort,the prediction effi-ciency of the model was verified by Kappa test.Results:In the training cohort,the univariate analysis showed statistically significant difference in cT stage,cN stage,and gross tumor volume(GTV)between patients with and without response(P＜0.05).Multivariate analyses showed that cT stage,cN stage,and GTV were independent influencing factors of the response(P＜0.05).ROC showed that the AUC of the Logistic regression model based on independent predictors to predict the treatment response was 0.724.In the validation cohort,the predictive model also performed well(Kappa=0.623).Conclusion;The Logistic regression model developed based on the cT staging,cN stage,and GTV is of great value in predicting the response of advanced gastric cancer after neoadjuvant chemotherapy.