Exploring the independent risk factors that affect the survival of patients with primary appendiceal tumors after surgery, constructing and validating column charts to help identify high-risk patients, and developing personalized treatment plans.

We retrospectively collected clinical data from patients diagnosed with appendiceal tumors in the American Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015, and randomly divided them into a training set and a validation set. Multiple factor Cox regression analysis was used to identify independent risk factors that affect overall survival (OS) in patients with primary appendiceal tumors after surgery. A new column chart model was developed and evaluated through internal validation.

Age, Pathology type, Tumor stage, N-stage, M-stage, lymph node dissection quantity, and CEA status were identified as independent risk factors affecting the prognosis of postoperative appendiceal tumor patients (P＜0.05). The C-index of the column chart training set was 0.811 (95% CI: 0.797~0.825), and the C-index of the validation set was 0.844 (95% CI: 0.819~0.869). The area under the ROC curve (AUC) of the 1-, 3-, and 5-year overall survival rates was 0.807, 0.849, and 0.824 in the training set, and 0.857, 0.862, and 0.825 in the validation set, respectively. Further validation of the predictive model's ability to distinguish between different outcome events was performed using X-year 10-fold 200-fold cross-validation. The calibration curve and decision curve analysis (DCA) showed good consistency and clinical benefits. The risk grading system divided all patients into three groups, and the Kaplan-Meier curve showed good stratification and discrimination ability between different groups regarding OS.

We developed a new column chart model to predict postoperative overall survival (OS) in patients with primary appendiceal tumors. In addition, the risk grading system helps accurately assess prognosis and guide treatment.