# Predictive Value of Hepatitis B Core-Related Antigen for Multiple Recurrence Outcomes After Treatment Cessation in Chronic Hepatitis B: A Meta-Analysis Study

## TL;DR

This study shows that a blood test called HBcrAg can reliably predict if chronic hepatitis B patients will relapse after stopping treatment.

## Contribution

The study confirms HBcrAg as a robust non-invasive biomarker for predicting relapse in chronic hepatitis B patients after treatment cessation.

## Key findings

- HBcrAg has a pooled sensitivity of 0.81 and specificity of 0.72 for predicting relapse.
- Threshold effects were the main source of heterogeneity, resolved after excluding outlier cutoff values.
- HBcrAg's predictive value is not affected by age, sex, or detection methods.

## Abstract

Background: Hepatitis B core-related antigen (HBcrAg), a novel serum biomarker reflecting the activity of intrahepatic covalently closed circular DNA (cccDNA), has generated conflicting evidence regarding its clinical utility for predicting post-antiviral therapy relapse in chronic hepatitis B (CHB) patients. Methods: We systematically analyzed 13 studies (15 cohorts, n = 1529 patients) from PubMed, Web of Science, Wanfang, and CNKI (through April 2025). A bivariate model evaluated HBcrAg’s predictive performance for relapse outcomes, including virological relapse, clinical relapse, and hepatitis flares. Results: HBcrAg demonstrated a pooled sensitivity of 0.81 (95% CI: 0.75–0.86) and specificity of 0.72 (95% CI: 0.67–0.76) for relapse prediction, with a diagnostic odds ratio of 10.66 (95% CI: 7.36–15.42) and summary AUC of 0.83 (95% CI: 0.80–0.86). Subgroup analysis identified threshold effects as the primary source of heterogeneity, which resolved (I2 < 13%) after excluding studies with outlier cutoff values. Meta-regression established that HBcrAg’s predictive value was unaffected by age, sex, hepatitis B e antigen status, or detection methods (p > 0.05). Conclusions: HBcrAg is validated as a robust non-invasive biomarker to optimize treatment cessation strategies, with high sensitivity providing strong negative predictive value in CHB populations. Future research should prioritize multi-marker models to enhance prediction accuracy.