PMID: 40287635 https://pubmed.ncbi.nlm.nih.gov/40287635/

Abstract

PURPOSE: Many prognostic scores based on systemic inflammation have been developed. Most of these prognostic scores have been shown to influence the prognosis of hepatocellular carcinoma (HCC) patients. This research aims to develop a novel prognostic system based on inflammatory markers for patients with HCC.

PATIENTS AND METHODS: This research encompassed 920 HCC patients who underwent potentially radical surgical resection. We employed receiver-operating characteristic (ROC) curve analysis to determine the optimal cutoff value for the preoperative inflammatory prognostic score. Univariate and multivariate Cox regression analyses were conducted to pinpoint features that significantly influence outcomes for patients with HCC. We employed a calibration curve and decision curve analysis (DCA) to appraise the application of the nomogram.

RESULTS: The multivariate Cox regression identified that systemic immunoinflammatory response index (SIRI), C-reactive protein-albumin ratio (CAR), tumor size, hepatitis B virus (HBV)-DNA, prothrombin time, microvascular invasion, macroscopic vascular invasion, and Edmondson-Steiner grade were all independent predictors of overall survival (OS). The predictive accuracy of the nomogram for estimating 1-, 3-, and 5-year OS was measured by the area under the receiver operating characteristic curve (AUC). In the training cohort, the AUC scores for the 1-, 3-, and 5-year OS were 0.815, 0.805, and 0.776. For the validation cohort, the respective AUC scores were 0.814, 0.737, and 0.730. Additionally, our nomogram shows a high capacity for distinguishing between different risk groups and is practical for clinical use.

CONCLUSION: The nomogram demonstrates strong predictive performance for the 1-, 3-, and 5-year OS of HCC patients undergoing radical surgery. The combination of related markers (SIRI, CAR, etc.) makes it more reliable and beneficial in predicting prognosis in HCC patients.