A Nomogram for Prediction of Survival in Patients After Gastrectomy Within Enhanced Recovery After Surgery (ERAS): A Single-Center Retrospective Study.

BACKGROUND Enhanced Recovery After Surgery (ERAS) programs can optimize clinical outcomes and have been widely used across multiple specialties, but a personalized prediction model involving ERAS for the prognosis of gastric cancer is lacking. MATERIAL AND METHODS We retrospectively collected clinical data on 725 gastric cancer patients within ERAS who underwent curative gastric resection in the Affiliated Hospital of Qingdao University from 2007 to 2014. Kaplan-Meier method, log-rank test, and Cox proportional risk model were used to determine the independent prognostic factors of patients. The accuracy of model was evaluated by C-index, calibration curve, and Decision Curve Analysis (DCA), and the receiver operator characteristic (ROC) curve was used to compare the nomogram model with the predictive value of TNM staging system. RESULTS The 5-year overall survival (OS) of 725 patients within ERAS was 72.5%. Age at diagnosis, T stage, N stage, and postoperative complications were determined to be independent factors affecting the prognosis of patients within ERAS, and nomogram model was constructed. The C-index of the training group was 0.809 and that of the verification group was 0.804; the calibration curves and DCA of the 2 groups showed good accuracy. Through verification, we found that, compared with the TNM staging assessment method, the nomogram model was more accurate in predicting the prognosis of gastric cancer. CONCLUSIONS This study identified factors affecting the prognosis of patients with gastric cancer, and we constructed the first prognostic nomogram model in ERAS mode to facilitate postoperative personalized prognostic evaluation.