Construction and Validation of a Prognostic Prediction Model for Gastric Mucinous Adenocarcinoma Based on the SEER Database

Abstract

This study focused on the development and validation of a prognostic model to predict overall survival (OS) in patients with gastric mucinous adenocarcinoma (GMA), utilizing data from the SEER database. A cohort of 537 GMA patients was analyzed to identify factors affecting survival, using both univariate and multivariate Cox regression analyses on demographic and clinicopathological variables. The analysis led to the creation of a nomogram model. Findings revealed that TNM staging and the administration of radiotherapy or chemotherapy were significant factors impacting survival outcomes. Specifically, patients at stages T4, N3, and M1 faced a notably higher mortality risk, while those who received radiotherapy and chemotherapy experienced a significant reduction in mortality risk. The model's performance, as indicated by C-indices of 0.73 in the training set and 0.66 in the validation set, suggests robust predictive capability. The area under the curve (AUC) analysis confirmed high accuracy in predicting 1-year, 3-year, and 5-year survival rates, and calibration curves displayed strong agreement between predicted and actual outcomes. Decision curve analysis (DCA) demonstrated that the model exhibited significant clinical utility across various thresholds. Overall, this study presents a reliable prognostic tool for individualized risk stratification and clinical treatment in GMA patients. Future work should focus on enhancing the model by incorporating molecular biological data to increase its predictive accuracy and applicability.