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Background and objective <p>Despite achieving functional cure with pegylated interferon-based therapy, a significant proportion of chronic hepatitis B (CHB) patients experience recurrence, even in the presence of high anti-HBs titers. Robust predictors to identify these at-risk individuals are lacking. We aimed to develop and validate a novel model integrating viral (HBcrAg) and host immune (anti-HBc, anti-HBs) biomarkers for personalized recurrence prediction.</p> Methods <p>In this ambispective cohort, 84 CHB patients with functional cure (28 recurrence [R], 56 non-recurrence [NR]) were rigorously selected via 1:2 propensity score matching and followed for ≥ 96&#xa0;weeks. Serum levels of HBcrAg, anti-HBc, and anti-HBs at end-of-treatment (EOT) were quantified. Independent predictors were identified by logistic regression, and diagnostic performance was evaluated by ROC analysis.</p> Results <p>At EOT, the R group had significantly higher HBcrAg levels than the NR group (3.30 ± 1.13 vs. 2.26 ± 1.04 log<sub>10</sub> U/mL; p &lt; 0.001), along with lower anti-HBc levels (2.53 ± 0.77 vs. 3.22 ± 0.53 log<sub>10</sub> IU/mL; p &lt; 0.001) and lower anti-HBs levels (1.89 ± 0.82 vs. 2.26 ± 0.56 log<sub>10</sub> IU/mL; p = 0.014). Multivariate analysis confirmed HBcrAg (OR = 3.48, p = 0.001) and anti-HBc (OR = 0.10, p = 0.001) as independent predictors, while anti-HBs lost significance. The combined three-marker model outperformed any single biomarker, achieving an AUC of 0.88 (95% CI 0.791–0.941), with a high negative predictive value of 91.8%. Crucially, among patients with high anti-HBs (&gt; 2.0 log₁₀ IU/mL), 93.3% (14/15) of relapsers had concurrently elevated HBcrAg, versus only 21.3% (10/47) of non-relapsers.</p> Conclusion <p>The HBcrAg/anti-HBc axis is a key determinant of relapse risk after functional cure. A combined biomarker model provides superior risk stratification, accurately identifying high-risk patients missed by anti-HBs alone, and paves the way for individualized post-treatment surveillance strategies.</p> Graphical abstract <p></p>

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A combined model of HBcrAg, anti-HBc, and anti-HBs predicts recurrence after functional cure of chronic hepatitis B

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Xiao Lin,
  • Shan Ren,
  • Chunyang Huang,
  • Pengfei Yu,
  • Yanhong Zheng,
  • Bin Xu,
  • Sujun Zheng,
  • Xinyue Chen

摘要

Background and objective

Despite achieving functional cure with pegylated interferon-based therapy, a significant proportion of chronic hepatitis B (CHB) patients experience recurrence, even in the presence of high anti-HBs titers. Robust predictors to identify these at-risk individuals are lacking. We aimed to develop and validate a novel model integrating viral (HBcrAg) and host immune (anti-HBc, anti-HBs) biomarkers for personalized recurrence prediction.

Methods

In this ambispective cohort, 84 CHB patients with functional cure (28 recurrence [R], 56 non-recurrence [NR]) were rigorously selected via 1:2 propensity score matching and followed for ≥ 96 weeks. Serum levels of HBcrAg, anti-HBc, and anti-HBs at end-of-treatment (EOT) were quantified. Independent predictors were identified by logistic regression, and diagnostic performance was evaluated by ROC analysis.

Results

At EOT, the R group had significantly higher HBcrAg levels than the NR group (3.30 ± 1.13 vs. 2.26 ± 1.04 log10 U/mL; p < 0.001), along with lower anti-HBc levels (2.53 ± 0.77 vs. 3.22 ± 0.53 log10 IU/mL; p < 0.001) and lower anti-HBs levels (1.89 ± 0.82 vs. 2.26 ± 0.56 log10 IU/mL; p = 0.014). Multivariate analysis confirmed HBcrAg (OR = 3.48, p = 0.001) and anti-HBc (OR = 0.10, p = 0.001) as independent predictors, while anti-HBs lost significance. The combined three-marker model outperformed any single biomarker, achieving an AUC of 0.88 (95% CI 0.791–0.941), with a high negative predictive value of 91.8%. Crucially, among patients with high anti-HBs (> 2.0 log₁₀ IU/mL), 93.3% (14/15) of relapsers had concurrently elevated HBcrAg, versus only 21.3% (10/47) of non-relapsers.

Conclusion

The HBcrAg/anti-HBc axis is a key determinant of relapse risk after functional cure. A combined biomarker model provides superior risk stratification, accurately identifying high-risk patients missed by anti-HBs alone, and paves the way for individualized post-treatment surveillance strategies.

Graphical abstract