RAR-Based Prognostic Model for Predicting Overall Survival in Hepatitis B Virus-Related Hepatocellular Carcinoma: A Multicenter Study.

Abstract

Purpose: Hepatitis B virus-related hepatocellular carcinoma poses a significant global health challenge. This study aimed to develop and validate a novel prognostic nomogram integrating the red blood cell distribution width-to-albumin ratio for predicting patients' overall survival.

Patients and methods: A retrospective cohort of 1403 patients was divided into training, internal validation, and external validation cohorts. A multivariate Cox regression model selected variables to construct a nomogram and an online calculator, which were subsequently validated.

Results: The ratio emerged as an independent risk factor for long-term survival (hazard ratio: 5.808, 95% confidence interval: 1.721-19.599). A prognostic nomogram incorporating nine variables based on the ratio was developed. Calibration curves demonstrated high concordance between the predicted and actual 3-year survival rates. Decision curve analysis indicated that the nomogram significantly increased the net benefit of predicting 3-year survival. Based on the area under the receiver operating characteristic curves, the nomogram outperformed traditional models in predicting survival across the three cohorts. Patients were stratified into low-, intermediate-, and high-risk groups based on risk scores calculated from the nomogram. In all cohorts, the median survival time of the high-risk group was significantly shorter than that of the intermediate- and low-risk groups. An online calculator, deployed via a web-based platform, facilitated convenient mortality risk prediction for these patients.

Conclusion: The ratio-based nomogram we developed can accurately predict the survival of patients with hepatitis B virus-related hepatocellular carcinoma, serving as an effective auxiliary tool for clinical personalized treatment and prognostic assessment.