Abstract:Objective To investigate the risk factors for postoperative infection after D2 radical resection for gastric cancer, and construct a nomogram model that can accurately predict the risk of postoperative infection.Methods Clinical data of patients underwent D2 radical resection for gastric cancer in the gastrointestinal surgery department of the hospital affiliated to a Medical University in Anhui from January 2019 to December 2021 were retrospectively analyzed. Patients were randomly divided into the training set and the validation set in a ratio of 3 ∶1. Patients in the training set were divided into the infected group and the non-infected group. Univariate and multivariate logistic regression were used to analyze the independent risk factors for postoperative infection after D2 radical resection for gastric cancer. A nomogram model of risk prediction was constructed based on the independent risk factors after D2 radical resection for gastric cancer, validated and assessed in the training set and validation set data, respectively. Receiver operating characteristic (ROC) curve, Hosmer-Lemeshow goodness-of-fit test and calibration curve were used to assess the efficiency of the model. Clinical decision curve analysis (DCA) was used to evaluate clinical validity of the model.Results A total of 477 patients were included in analysis, with 358 in the training set and 119 in the validation set. Among them, 185 patients underwent D2 radical resection for gastric cancer developed postoperative infection, with lower respiratory tract infection being the main infection (n=98, 53.0%), followed by organ or cavity infection (n=48, 25.9%) and bloodstream infection (n=17, 9.2%). Multivariate logistic regression analysis showed the history of abdominal surgery (OR=1.922, 95%CI: 1.048-3.523), NRS 2002≥3 points (OR=3.525, 95%CI: 2.178-5.707), PNI < 49.6(OR=1.662, 95%CI: 1.061-2.602), high ASA classification (Grade 2 vs Grade 1: OR=3.513, 95%CI: 1.883-6.557; Grade 3 vs Grade 1: OR=10.219, 95%CI: 1.097-95.216), combined with organ resection (OR=2.115, 95%CI: 1.105-4.049), and admission to the intensive care unit (OR=15.927, 95%CI: 1.847-137.330) were independent risk factors for postoperative infection after D2 radical resection for gastric cancer (all P < 0.05). A nomogram model of risk prediction was constructed based on the above independent risk factors. The area under the curve (AUC) in the training set and validation set were 0.768 (95%CI: 0.718-0.818) and 0.750 (95%CI: 0.664-0.837), respectively, indicating good discrimination ability of the model. Hosmer-Lemeshow goodness-of-fit test suggested a good fit for the model (P>0.05), and the calibration curve showed good consistency in predicting infection after D2 radical resection for gastric cancer. DCA curve demonstrated the high clinical value of the model.Conclusion The nomogram prediction model based on independent risk factors for postoperative infection after D2 radical resection for gastric cancer can provide a quantitative and intuitive reference tool for early clinical evaluation of the probability of infection after D2 radical resection for gastric cancer.