A Non-Endoscopic Dynamic Nomogram for Atrophic Gastritis Risk Stratification Based on Serum Indicators and Clinical Factors

Abstract

Background Atrophic gastritis (AG) is a key precancerous lesion in gastric carcinogenesis, underscoring the need for non-endoscopic screening tools to improve early detection. This study aimed to develop a predictive model for AG based on serum indicators and clinical factors. Methods This single-center retrospective study enrolled 520 patients who underwent gastroscopy with biopsy at Shaoxing Second Hospital between January 2023 and December 2025. AG severity was classified via the Kimura-Takemoto system (no/mild: C0-C1, n=349; moderate/severe: C2-C3 and O-type, n=171). Multivariate analysis was performed to identify independent predictors. The performance of the resulting predictive model was evaluated, and decision curve analysis was used to evaluate the clinical utility across a range of threshold probabilities. An interactive dynamic nomogram was created for real-time risk calculation. Results Multivariate analysis identified four independent predictors of moderate/severe AG: older age (OR = 1.082, P < 0.001), elevated neutrophil count (NE) (OR = 2.036, P = 0.043), decreased fibrinogen (FIB) (OR = 0.56, P < 0.001), and elevated carcinoembryonic antigen (CEA) (OR = 1.171, P = 0.011). The predictive model demonstrated good discrimination in the development cohort (AUC = 0.780) and was further evaluated in an independent 94-patient inter-campus cohort (AUC = 0.705), confirming its discriminatory ability within the same hospital system. Conclusion This non-endoscopic model incorporating age, NE, FIB, and CEA provides a practical tool for AG risk stratification, As a single-center retrospective model, it requires further multi-center prospective validation before clinical implementation; nevertheless, it may help guide endoscopic surveillance decisions and contribute to the early prevention of gastric cancer.