Work

Development and validation of a novel prognostic model for gastric signet ring cell carcinoma based on inflammation-nutrition indicators

Year: 2026

Type: article

Abstract: Background Gastric signet-ring cell carcinoma (GSRCC) is a highly aggressive subtype of gastric cancer with poor prognosis. Existing prognostic models lack integrated analysis of systemic inflammation and nutritional status. This study aimed to develop and validate a prognostic model incorporating inflammatory and nutritional indicators to enhance individualized clinical management in GSRCC patients. Methods A total of 604 GSRCC patients who underwent curative surgery between 2014 and 2018 were retrospectively analyzed and divided into training ( n = 368) and validation ( n = 236) cohorts. Prognostic factors were selected using univariate analysis, multivariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression. A nomogram integrating clinicopathological features and inflammation-nutrition indicators was constructed and evaluated using calibration curves, time-dependent ROC (t-ROC) analysis, and decision curve analysis (DCA). Results X-tile analysis determined optimal cut-off values for inflammation and nutrition markers. Multivariate analysis identified age ≥60 years, upper tumor location, T4 stage, N2–N3 stage, lymphocyte-to-CRP ratio (LCR) ≥ 8,785.7, and geriatric nutritional risk index (GNRI) ≥ 112.9 as independent predictors of overall survival (all p < 0.05). The combined LCR_GNRI score showed strong prognostic discrimination ( p < 0.001). The nomogram achieved a concordance index (C-index) of 0.831, with good calibration and substantial clinical benefit confirmed by DCA. Conclusions This study developed and validated a novel GSRCC prognostic nomogram integrating inflammatory and nutritional indicators, offering improved discrimination and clinical utility. It provides a practical tool for precise risk stratification and personalized management of GSRCC patients.

Source: Frontiers in Nutrition

DOI: 10.3389/fnut.2026.1623570