RESUMO
INTRODUCTION AND OBJECTIVES: We initiated this multicenter study to integrate important risk factors to create a nomogram for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) for clinician decision-making. PATIENTS AND METHODS: Between April 2011 and March 2022, 2281 HCC patients with an HBV-related diagnosis were included. All patients were randomly divided into two groups in a ratio of 7:3 (training cohort, n = 1597; validation cohort, n = 684). The nomogram was built in the training cohort via Cox regression model and validated in the validation cohort. RESULTS: Multivariate Cox analyses revealed that the portal vein tumor thrombus, Child-Pugh class, tumor diameter, alanine aminotransferase level, tumor number, extrahepatic metastases, and therapy were independent predictive variables impacting overall survival. We constructed a new nomogram to predict 1-, 2-, and 3-year survival rates based on these factors. The nomogram-related receiver operating characteristics (ROC) curves indicated that the area under the curve (AUC) values were 0.809, 0.806, and 0.764 in predicting 1-, 2-, and 3-year survival rates, respectively. Furthermore, the calibration curves revealed good agreement between real measurements and nomogram predictions. The decision curve analyses (DCA) curves demonstrated excellent therapeutic application potential. In addition, stratified by risk scores, low-risk groups had longer median OS than medium-high-risk groups (p < 0.001). CONCLUSIONS: The nomogram we constructed showed good performance in predicting the 1-year survival rate for HBV- related HCC.