Predictive Nomograms for Clinical Outcomes in Hepatitis B-Related Cirrhosis Patients Receiving Antiviral Therapy.

ABSTRACT

OBJECTIVE: Many scores have been constructed to predict liver-related events in chronic hepatitis B, while most of them are based on baseline clinical parameters. The objective of this study was to develop nomograms based on on-treatment improvement in established scores to predict clinical outcomes in patients with hepatitis B virus (HBV)-related cirrhosis who are receiving antiviral therapy. METHODS: The Cox proportional hazards regression model was used. Nomograms were constructed for the prediction of liver-related events, hepatocellular carcinoma (HCC), and liver-related mortality risk during long-term antiviral therapy. RESULTS: A total of 277 treatment-naive patients with HBV-associated cirrhosis were enrolled from January 2010 to December 2013. After a median follow-up of 63.3 months, 95 patients developed liver-related events, including 59 patients with liver-related death. Multivariate Cox analysis showed that the albumin-bilirubin score at year 1 was an independent predictor of liver-related events, liver-related mortality, and HCC. Age, decompensation, and delayed virological remission were independent factors for liver-related mortality. Age was also a risk factor for liver-related events. The concordance index values of event-nomogram, mortality-nomogram, and HCC-nomogram were 0.742 (95% confidence interval [CI], 0.691~0.793), 0.799 (95% CI, 0.748~0.850), and 0.613 (95% CI, 0.540~0.686), respectively. The calibration plots showed an agreement between the predicted and observed incidences, which indicates good calibration of the model of event-nomogram and mortality-nomogram. CONCLUSION: The nomograms achieved an optimal preoperative prediction of liver-related events, mortality, and HCC development in patients with HBV-related cirrhosis receiving antiviral therapy. These findings may help to identify high-risk patients for further optimal surveillance and intervention strategies.