Nomogram for Prediction of Postoperative Morbidity in Patients with Colon Cancer Requiring Emergency Therapy

Background: Postoperative complications are the major cause of mortality and prolonged hospitalization after emergency surgery for colon cancer. This study aimed to propose an effective nomogram to predict postoperative complications in order to improve the outcomes. Material/Methods: We retrospectively analyzed 449 patients who underwent emergency surgery for complicated colon cancer at the County Emergency Hospital Clinic "St. Apostle Andrei" in Gala??i, in the period from 2008 to 2017. Postoperative complications were intestinal obstruction, leakage, bleeding, peritonitis, wound infection, surgical wound dehiscence, respiratory failure, heart failure, acute renal failure, sepsis, and Clostridium difficile colitis, within a month after surgery. Logistic regression models were used to identify the independent prediction factors, and a nomogram was created, based on the best model. Results: A total of 106 patients (21%) presented postoperative complications after emergency surgery for colon cancer; 51 patients (11.36%) died during the postoperative period. After identifying the risk factors through univariate regression analysis, we identified the independent prediction factors in 2 multivariate regression models. The model with the highest accuracy included the following 7 independent prediction factors: Eastern Cooperative Oncology Group performance status, Charlson score, white blood cell count, electrolyte and coagulation disorders, surgery time, and cachexia (P<0.05 for all). This model showed good precision in predicting postoperative complications, with an area under curve of 0.83 and ideal accordance between the predicted and observed probabilities. Conclusions: The nomogram developed in this study, which was based on a multivariate logistic regression model, had good individual prediction of postoperative complications.