An Inflammation-Associated Prognostic Model for Hepatocellular Carcinoma Following Radical Resection

Hepatocellular carcinoma (HCC) remains poor, and inflammatory markers have emerged as potential predictors. This study aimed to develop and validate a nomogram for predicting overall survival (OS) in patients with HCC after radical hepatectomy by integrating inflammatory markers with clinicopathological factors.

We retrospectively analyzed patients with HCC who underwent radical hepatectomy at the Guangdong Provincial People's Hospital between 2014 and 2018. The patients were randomly assigned (2:1 ratio) to the training and validation cohorts. Independent prognostic factors were identified using univariate and multivariate Cox regression analyses to construct a nomogram. The performance of the model was assessed using ROC, calibration, and decision curve analysis (DCA) and compared with established staging systems (AJCC 8th edition TNM, BCLC, and CNLC).

The training and validation cohorts included 242 and 121 patients, respectively. Aspartate aminotransferase-to-platelet ratio index (APRI), systemic inflammation response index (SIRI), and microvascular invasion (MVI) were identified as independent prognostic factors (P < 0.05). In the training cohort, the nomogram achieved AUCs of 0.837, 0.778, and 0.793 for the 1-, 3-, and 5-year OS, respectively. The corresponding AUCs in the validation cohort were 0.712, 0.746, and 0.746, respectively. The calibration curves and DCA confirmed the robust predictive ability of the model. The nomogram AUCs were significantly higher than those of all staging systems (P < 0.05).

The proposed nomogram, incorporating APRI, SIRI, and MVI, effectively predicts OS in patients with HCC following radical resection and outperforms conventional staging systems.