HBcrAg predicts hepatocellular carcinoma development: An analysis using time-dependent receiver operating characteristics

Abstract

Several hepatitis B virus (HBV) markers have been identified as factors associated with the development of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). We clarified the predictive power of HBV markers for the development of HCC using receiver operating characteristic (ROC) analysis with a consideration of time dependence. A total of 1031 CHB patients who were not treated with nucleos(t)ide analogue therapy were enrolled. Univariate, multivariate, and time-dependent ROC curves for HBV markers associated with the development of HCC were analyzed. Seventy-eight patients developed HCC during the follow-up period (median duration 10.7years). Different levels or statuses of several HBV markers (HBV genotype, HBV DNA, HBV core-related antigen (HBcrAg), hepatitis B e antigen (HBeAg), and basal core promoter (BCP)), but not hepatitis B surface antigen, were significantly associated with the incidence of HCC by univariate analysis using the log-rank test. Cox proportional hazards models using the covariates of HBV genotype status, HBV DNA levels, HBcrAg levels, HBeAg status, and BCP status indicated that HBcrAg >2.9logU/ml (hazard ratio (HR), 5.05; 95% confidence interval (CI), 2.40-10.63) and BCP mutation (HR, 28.85; 95% CI, 4.00-208.20) were independently associated with the incidence of HCC. Additionally, time-dependent ROC analysis showed that HBcrAg was superior to HBV DNA in terms of predictive power for HCC development throughout the follow-up period. Elevation of HBcrAg levels in CHB patients is associated with the development of HCC. HBcrAg is an excellent predictor of HCC development. Hepatitis B virus (HBV) core-related antigen (HBcrAg) is an excellent predictor of hepatocellular carcinoma (HCC) development in chronic hepatitis B patients without nucleos(t)ide analogue therapy. HBcrAg was superior to HBV DNA in terms of predictive power for HCC development by time-dependent receiver operating characteristic analysis.