Abstract
PURPOSE: Gastric signet ring cell carcinoma (GSRC) is a distinct gastric cancer (GC) subtype. This study aimed to develop and validate a nomogram to predict overall survival (OS) and guide clinical decision-making. METHODS: This study included 2,203 GSRC patients from the SEER database (2010-2019), randomly split into a modeling cohort (n = 1,542) and an internal validation cohort (n = 661). An external cohort of 74 patients from the Second Affiliated Hospital of Nanjing Medical University (2019-2024; median follow-up 34 months) was used for validation. Predictor variables-age, sex, chemotherapy, lymph node ratio (LNR), T and M categories, tumor size, and tumor number-were included in a cox proportional hazard model. A nomogram was derived from the cox model and internally validated using 1,000 bootstrap resamples. Discrimination, calibration, and decision curve analysis (DCA) evaluated model performance. RESULTS: The nomogram included age, chemotherapy, LNR, T and M categories, and tumor size. In the modeling cohort, time-dependent area under the receiver operating characteristic curve (AUC) was 0.79, 0.85, and 0.85 at 12, 36, and 60 months; internal validation AUCs were 0.79, 0.85, and 0.85. In the external cohort, AUC at 36 months was 0.91 (primary horizon), with exploratory IPCW-AUCs of 1.00 at 12 and 60 months due to class imbalance. Calibration showed close agreement between predicted and observed OS, and DCA demonstrated clinical net benefit across relevant thresholds. CONCLUSION: This study developed a nomogram for OS prediction in GSRC patients, supporting risk stratification and clinical decision-making.