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/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.