Combined Model of Inflammatory-Nutritional Indicators and Tumor Markers for Predicting Prognosis in Patients with...

Objectives: The TNM staging system for distal cholangiocarcinoma (dCCA) has limited accuracy due to its anatomical basis. This study developed a prognostic model integrating inflammatory-nutritional markers and tumor biomarkers to improve risk stratification. Methods: We analyzed 208 dCCA patients undergoing pancreaticoduodenectomy (2017-2024). Independent prognostic factors for overall survival (OS) were identified via Cox regression, including tumor marker (corrected CA19-9) and host status markers (PLR, CAR, and PNI). A nomogram was constructed and evaluated using calibration, ROC, and DCA. Patients were risk-stratified using the model's score. Results: Four independent factors were identified: corrected CA19-9 (HR = 2.438), PLR (HR = 2.041), CAR (HR = 2.477), and PNI (HR = 0.415). The nomogram showed excellent discrimination for 1-, 3-, and 5-year OS (AUC: 0.847, 0.824, 0.858), good calibration, and clinical utility per DCA. Risk stratification significantly distinguished high-risk (n = 110) from low-risk (n = 98) groups (log-rank p < 0.0001). Discussion: This multidimensional model (tumor burden, inflammation, nutrition) outperforms TNM staging, highlighting host systemic status. Despite its single-center retrospective design, it shows promise for personalized risk assessment. Conclusion: The CINS (Cholangiocarcinoma Inflammation-Nutrition Score) accurately predicts prognosis and effectively risk-stratifies dCCA patients, aiding personalized treatment planning.