Nomogram models for predicting overall and cancer-specific survival in early-onset gastric cancer patients: a population-based cohort study.

To develop nomogram models for predicting the overall survival (OS) and cancer-specific survival (CSS) of early-onset gastric cancer (EOGC) patients. A total of 1077 EOGC patients from the Surveillance, Epidemiology, and End Results (SEER) database were included, and an additional 512 EOGC patients were recruited from the Fourth Hospital of Hebei Medical University, serving as an external test set. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors. Based on these factors, two nomogram models were established, and web-based calculators were developed. These models were validated using receiver operating characteristics (ROC) curve analysis, calibration curves, and decision curve analysis (DCA). Multivariate analysis identified gender, histological type, stage, N stage, tumor size, surgery, primary site, and lung metastasis as independent prognostic factors for OS and CSS in EOGC patients. Calibration curves and DCA curves demonstrated that the two constructed nomogram models exhibited good performance. These nomogram models demonstrated superior performance compared to the 7th edition of the AJCC tumor-node-metastasis (TNM) classification (internal validation set: 1-year OS: 0.831 vs 0.793, P = 0.072; 1-year CSS: 0.842 vs 0.816, P = 0.190; 3-year OS: 0.892 vs 0.857, P = 0.039; 3-year CSS: 0.887 vs 0.848, P = 0.018; 5-year OS: 0.906 vs 0.880, P = 0.133; 5-year CSS: 0.900 vs 0.876, P = 0.109). In conclusion, this study developed two nomogram models: one for predicting OS and the other for CSS of EOGC patients, offering valuable assistance to clinicians.