Prediction of distant metastasis and survival of appendiceal cancer patients: a SEER population-based study

Appendiceal cancer (AC) is a rare and heterogeneous malignancy that is often diagnosed incidentally and shows marked variation in metastatic risk and prognosis. Current staging systems provide limited individualized prediction, so we developed and validated nomogram models to estimate distant metastasis (DM) and survival outcomes.

Data of 6,916 pathologically confirmed AC patients diagnosed between 2004 and 2021 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training (n=4,844) and validation (n=2,072) cohorts at a 7:3 ratio. Independent risk factors for DM were identified by logistic regression, while prognostic factors for overall survival (OS) and cancer-specific survival (CSS) were determined by Cox regression analyses. Based on these variables, nomograms were constructed and their performance was assessed using concordance index (C-index), area under the curve (AUC), calibration curves, and decision curve analysis (DCA).

The DM nomogram showed excellent discrimination with AUCs of 0.916 and 0.905 in the training and validation cohorts, respectively. For OS and CSS, age ≥51 years, poor differentiation, advanced tumor-node-metastasis (TNM) stage, histological subtype, chemotherapy, marital status, and surgery were significant predictors. The OS and CSS nomograms demonstrated high accuracy, with C-indexes above 0.85 and robust AUCs for 1-, 3-, and 5-year survival predictions in both cohorts. Calibration curves and DCA confirmed good agreement between predicted and observed outcomes as well as clinical utility. Risk stratification based on the DM nomogram effectively distinguished patients with significantly different OS and CSS.

These nomograms provide reliable tools for individual prediction and clinical decision-making in AC patients.