Introduction

Hepatitis B virus (HBV) infection is a significant global public health issue. According to the World Health Organization (WHO), approximately 296 million people suffer from chronic HBV infection, and there are 1.5 million new infections each year worldwide [1]. Chronic hepatitis B (CHB) can lead to liver fibrosis, cirrhosis, hepatocellular carcinoma, and premature death. Moreover, it is associated with an increased risk of several other types of cancers [2]. Without proper treatment, it is estimated that hepatitis B-related deaths will reach 1.14 million by 2035 [3]. In China, the number of individuals with chronic HBV infections is remarkably high, estimated around 80 million in 2022, making it the leading country in terms of hepatitis B surface antigen (HBsAg)-positive populations [4]. While China has made considerable progress in the prevention and treatment of hepatitis B, diagnosis and treatment concepts are evolving rapidly [5]. Despite these efforts, achieving the WHO's goal of "eliminating viral hepatitis as a public health hazard by 2030" remains a significant challenge [6].

The ideal treatment goal for CHB patients is achieving HBsAg seroclearance or seroconversion, considered as a functional cure, as endorsed by authoritative national and international guidelines [6,7,8,9]. However, the rate of spontaneous HBsAg seroclearance in adult CHB patients is only 1.17% per year [10], and even lower at 1% for children [11]. Current antiviral drugs for HBV mainly include interferon-α (containing both conventional interferon-α and pegylated interferon-α) and nucleos(t)ide analogues (NAs). The annual incidence of HBsAg seroclearance with NAs is a mere 0.22%, with a 10-year cumulative incidence of 2.11% [12]. In contrast, studies have shown that pegylated interferon-α (PegIFNα)-based therapy has significantly improved functional cure rates. For instance, PegIFNα-based regimens resulted in a high HBsAg seroclearance rate of 47% in inactive HBsAg carriers (IHCs), compared to only 1.54% in the control group (including NAs-treated or untreated patients) [13]. PegIFNα-based therapy has also shown promising results in patients with prior NAs experience [14, Data extraction

Two researchers (Yan Huang and **gwen Feng), with extensive experience in the field of hepatitis B, independently screened the literature based on predetermined inclusion and exclusion criteria. They used a standardized data extraction form to extract information, cross-checked each case, and resolved any disagreements through discussion with a third researcher (Shaowen Jiang). The extracted data included: (1) study characteristics: name of first author, country, year of publication, type of study; (2) basic patient information: sample size, age, gender; (3) treatment modality: treatment regimen, duration of therapy, length of follow-up after discontinuation of PegIFNα; and (4) predictors of HBsAg seroclearance prioritized for evaluating outcomes at the end of follow-up (if reported); if not, end-of-treatment outcomes were assessed.

Quality assessment

The Cochrane risk of bias was used to assess the quality of the randomized controlled trials (RCTs) [34], while the Newcastle–Ottawa Quality Assessment Scale (NOS) was used for cohort studies [35]. The MINORS score was used for single-arm studies [36]. Quality assessment was performed independently by two investigators, and discrepancies were resolved by a third investigator.

Statistical analysis

The primary objective of this study is to extract effect estimates, such as hazard ratio (HR) or odds risk (OR), from multivariate Cox or logistic regression models, along with their corresponding 95% confidence intervals (CIs) for each risk factor related to the outcome of interest. For statistical analysis, predictors were considered only if relevant data from at least two studies were available. To quantify statistical heterogeneity, the I2 and Cochrane Q tests were employed, which assessed the proportion of variation between studies attributable to heterogeneity rather than chance. When I2 > 50% and p value < 0.05 indicated substantial heterogeneity, a random-effects model was utilized. Conversely, a fixed-effects model was used in the absence of significant heterogeneity, with sensitivity analysis to verify the results. Subgroup analyses were performed to evaluate the impact of region and treatment duration on the pooled estimates. Meta-regression analysis was used to obtain the source of high heterogeneity for findings on some factors reported in more than 10 articles. Publication bias in the literature was assessed using Egger and Begge tests, with a minimum of seven articles required for the analysis. If evidence of publication bias was detected, the Trim and Fill procedure was applied. Statistical significance was set at a p value of less than 0.05. All statistical analyses were conducted using Stata software version 15.0 (Stata Corp., College Station, TX, USA). Quality assessment of RCT studies was performed using Review Manager 5.3.

Results

Figure 1 illustrates the study selection process. Initially, 4350 publications were identified using the search terms. After screening titles and abstracts, 269 studies were considered potentially relevant and underwent a full review. Among these, 242 studies were excluded due to various reasons, including a lack of reporting on multivariate analysis predictors, duplicate patient data, or other issues. Eventually, 27 studies were included in the meta-analysis.

Fig. 1
figure 1

Flow diagram showing the selection of studies for the meta-analysis

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Study characteristics

The analysis included a total of 27 studies conducted between 2009 and 2023, involving 7913 patients, of which 5706 (72.1%) were male. The studies exhibited substantial variations in sample size, ranging from 42 to 2579 participants, with most being conducted in China (22 studies), followed by 3 studies in the Netherlands, 1 in France, and 1 in Thailand. For study types, it comprised 13 multi-center studies and 14 single-center studies; 5 randomized controlled trials (RCTs), 9 cohort studies, and 13 single-arm trials. Among these, 17 (62.9%) studies were prospective, while the remaining 10 were retrospective. 7 studies were treatment-naive patients; 10 were NAs-treated patients; 10 included both treatment-naive and NAs-treated patients/ undisclosed. In addition, 4 studies included HBeAg (hepatitis B e antigen) positive patients, 14 included HBeAg negative patients, and 9 included both HBeAg positive and negative patients. Furthermore, 3 studies focused on IHCs, and one of these also included patients with chronic HBV infection. The treatment durations varied, with 48 weeks being the most common (17 studies), followed by 24–48 weeks in 2 studies, 48–96 weeks in 4 studies, 96 weeks in 3 studies, and over 96 weeks in one study. The follow-up period after discontinuation of PegIFNα treatment ranged from 0 to 360 weeks (Supplementary Table 2).

Quality assessment

The RCTs demonstrated a low risk of test bias and missed visits, thanks to the use of quantitative laboratory indicators and a missed visit rate of less than 20%. However, selection bias remained unclear in three RCTs due to unreported randomization and allocation methods. Furthermore, implementation bias was high across four RCTs as they used open-label controlled trials (Fig. 2). Each of the nine cohort studies exhibited a low risk score ranging between 7 and 9 (Supplementary Table 3). Similarly, the 12 single-arm studies also demonstrated a low risk score, ranging from 12 to 15 (Supplementary Table 4).

Fig. 2
figure 2

Quality assessment of randomized control trials

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Correlation between baseline characteristics and HBsAg seroclearance

Among the 27 included studies, the correlation between age (in years), gender, genotype (A, B, D), treatment strategy (combination with NAs vs. monotherapy), baseline HBsAg (log10 IU/ml), HBeAg (Log S/CO), HBV DNA (log10 IU/mL), and HBsAg seroclearance was reported in 8, 2, 4, 2, 14, 2, and 4 studies, respectively.

Table 1 presents the combined estimates of baseline factors that were reported in two or more studies. Regarding patient characteristics, a younger age showed a positive correlation with HBsAg seroclearance (OR = 0.961, 95% CI 0.925–0.997, I2 = 61.6%). There was a significant difference in sample size between the two gender-related studies (2579 vs. 60), with males demonstrating greater difficulty in achieving HBsAg seroclearance compared to females (OR = 0.537, 95% CI 0.371–0.777, I2 = 0%). Concerning baseline virological indicators, patients with genotype A were more likely to achieve HBsAg seroclearance than those with genotype D (OR = 10.738, 95% CI 3.098–37.215, I2 = 0%), and genotype B (OR = 7.472, 95% CI 2.549–21.897, I2 = 0%). In addition, treatment with PegIFNα combined with NAs demonstrated a higher probability of achieving HBsAg seroclearance compared to PegIFNα monotherapy (OR = 2.126, 95% CI 1.059–4.269, I2 = 0%). Furthermore, lower baseline HBsAg (log10 IU/ml) and HBV DNA (log10 IU/mL) were significantly associated with HBsAg seroclearance (OR = 0.373, 95% CI 0.266–0.522, I2 = 56.1%; OR = 0.414, 95% CI 0.253–0.678, I2 = 16.9%). However, baseline HBeAg (log S/CO) did not show a statistically significant relationship with HBsAg seroclearance (OR = 0.877, 95% CI 0.556–1.384, I2 = 0%) (Supplementary Figs. 1–3).

Table 1 Baseline guided therapy (BGT) predictors associated with HBsAg seroclearance
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Correlation of on-treatment virological and biochemical factors with HBsAg seroclearance

Among the 27 studies, the relationship of HBsAg (log10 IU/mL) during treatment, HBsAg (IU/mL) at week 12, HBsAg (log10 IU/mL) decline from baseline to week 12 and 24, HBsAg decline from baseline to week 12 (≥ 1 vs. < 1 log10 IU/mL, ≥ 0.5 vs. < 0.5 log10 IU/mL), and ALT elevation at week 12 (upper limit of normal, ULN; ULN standards were based on the reported articles) with HBsAg seroclearance was reported in 13, 3, 8, 4, and 2 studies, respectively.

Table 2 provides a summary of the pooled estimates for on-treatment factors associated with HBsAg seroclearance, reported in two or more studies. The results showed that lower HBsAg levels (log10 IU/mL) at week 12 and 24 were associated with a higher likelihood of achieving HBsAg seroclearance (OR = 0.384, 95% CI 0.230–0.642, I2 = 63.7%; OR = 0.294, 95% CI 0.217–0.398, I2 = 14.2%, respectively). Moreover, a greater reduction in HBsAg (log10 IU/mL) from baseline to week 12 and 24 was associated with increased HBsAg seroclearance (OR = 6.689, 95% CI 4.198–10.660, I2 = 0%; OR = 6.513, 95% CI 4.626–9.169, I2 = 42.1%). Similarly, HBsAg decline > 1 or > 0.5 log10 IU/ml from baseline to week 12 showed a significant association with HBsAg seroclearance (OR = 18.277, 95% CI 2.096–159.396, I2 = 56.9%; OR = 4.530, 95% CI 3.692–5.558, I2 = 0%). ALT elevation at week 12 was also a strong predictor (OR = 3.622, 95% CI 2.015–6.512, I2 = 0%) (Supplementary Figs. 4, 5).

Table 2 Response guided therapy (RGT) predictors associated with HBsAg seroclearance
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Subgroup analysis based on PegIFNα treatment course and region

Subgroup analyses were conducted based on whether the PegIFNα treatment course exceeded the standard 48-week treatment. For baseline characteristics, there was no significant association between age and HBsAg seroclearance for treatment ≤ 48 weeks (OR = 0.978, 95% CI 0.933–1.026, I2 = 65.4%). However, for treatment > 48 weeks, a younger age was associated with a higher likelihood of achieving HBsAg seroclearance (OR = 0.917, 95% CI 0.875–0.961, I2 = 0%). The remaining results were consistent with the overall analysis.

For on-treatment factors, HBsAg at week 12 (log10 IU/mL) was significantly associated with HBsAg seroclearance for treatment ≤ 48 weeks (OR = 0.334, 95% CI 0.168–0.664, I2 = 70%), but this association disappeared when the treatment exceeded 48 weeks (OR = 0.545, 95% CI 0.156–1.911, I2 = 74.6%). The remaining results were consistent with the overall analysis (Table 2).

The study included a predominantly Asian population, and similar results were observed in subgroup analysis based on the Asian population as compared to the overall population (Tables 3, 4).

Table 3 Baseline guided therapy (BGT) predictors associated with HBsAg seroclearance in Asian population
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Table 4 Response guided therapy (RGT) predictors associated with HBsAg seroclearance in Asian population
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Some predictive factors related to HBsAg seroclearance could not be combined due to only one study reporting usable data. These predictors included virological indicators, such as quantitative hepatitis B core antibody (qAnti-HBc), HBsAb, hepatitis B core-related antigen (HBcrAg), HBsAg composition (large hepatitis B surface proteins [LHBs], middle hepatitis B surface proteins [MHBs]); biochemical indicators, such as creatinine (Cr), hemoglobin (HGB), and platelet (PLT); immunological and other biomarkers, such as monocyte Myeloid-derived suppressor cells (mMDSCs), CD4+ Treg, CD86+ plasmacytoid dendritic cell (pDC), C–X–C Motif Chemokine Ligand 9 (CXCL9), microRNAs-3960, microRNAs-126-3p, and others (Supplementary Table 5).

Meta-regression, sensitivity and publication bias analysis

Meta-regression was used to explore the effects of 5 confounding factors (publication year, region, study design, treatment naïve and treatment duration) on heterogeneity. Only region was significantly associated with the high heterogeneity of findings on baseline HBsAg (Supplementary Fig. 6). The Cochrane's Q test p values and I2 statistics indicated high heterogeneity for the factors of HBsAg at week 48 (log10 IU/mL) and HBsAg at week 12 (IU/mL) (I2 = 90%, p = 0.002; I2 = 81.8%, p = 0.004, respectively). However, due to the limited number of studies on these two factors, sensitivity or subgroup analyses could not be conducted. The I2 value for HBsAg decline from baseline to week 12 (log10 IU/mL) decreased from 95 to 0% after excluding one study. This change might be attributed to the inclusion of both total HBsAg and HBsAg components in the multifactorial regression analysis. To assess publication bias, Begg or Egger tests were performed for age and baseline HBsAg (log10 IU/mL) in studies with seven or more inclusions. The tests did not indicate significant publication bias (Supplementary Figs. 1, 3). However, the Egger test for HBsAg level (log10 IU/mL) showed evidence of publication bias (p < 0.05), although no literature was identified for correction using the pruning method. Nevertheless, sensitivity analyses did not show any significant changes in the results.

Discussion

Complete eradication or sterilizing cure of CHB, defined as the elimination of cccDNA and integrated HBV DNA, is considered an unrealistic endpoint under existing medical conditions. However, functional cure is considered an ideal, achievable endpoint and the goal to strive for. As evidenced by multiple studies, aggressive antiviral therapy aimed at achieving functional cure significantly reduces the incidence of cirrhosis, liver decompensation, and liver cancer-related mortality [9, 37]. Expanding the treatment indications for CHB and increasing the coverage of available treatments are highly effective and cost-effective strategies to reduce adverse outcomes related to CHB [38]. Combining NAs with PegIFNα and extending the treatment duration in current therapeutic regimens have been shown to prolong quality-adjusted life-years, making it more cost-effective than NAs monotherapy [39]. Ongoing real-world studies with large sample sizes and multicenter participation are focused on achieving functional cure for CHB patients and reducing the incidence of liver cancer [21] reported that compared to interferon monotherapy, NAs add-on interferon had a similar outcome in their meta‑analysis, while we found that the combination of PegIFNα with NAs resulted in a higher probability of achieving HBsAg seroclearance compared to PegIFNα monotherapy. This disagreement could be attributed to different research objectives and inclusion criteria. We aimed to summarize potential predictors for HBsAg seroclearance by PegIFNα in CHB patients, so only studies that utilized multivariate Cox or logistic regression to report at least one predictor for HBsAg seroclearance by PegIFNα-containing therapy would be included in our meta‑analysis. By contrast, a number of studies, in which conventional interferon-α was used for treating CHB patients, and multivariate Cox or logistic regression was not applied in statistical analysis, were also included in the meta-analysis of Liu et al. Subgroup analysis revealed that there was no significant association between HBsAg at week 12 and HBsAg seroclearance when the treatment duration exceeded 48 weeks; however, HBsAg levels at week 24 may serve as a better predictor. Consequently, the recommended time point for prediction should be shifted to week 24 in PegIFNα treatments lasting longer than 48 weeks. Li et al. demonstrated that in CHB patients whose HBsAg levels plateaued after the initial PegIFNα treatment, adopting a PegIFNα-based intermittent approach could result in a high HBsAg seroclearance rate of up to 44.06% when an early HBsAg response was achieved in both initial treatment and retreatment. Notably, HBsAg levels before retreatment and a decline of > 0.5 log10 IU/mL in HBsAg levels at week 12 were identified as independent predictors of HBsAg seroclearance after retreatment [

Data availability

The data presented in this study are available in article or supplementary material.

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Acknowledgements

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Funding

This work was supported by the National Natural Science Foundation of China (Nos. 82070604, 82270618), the Shanghai Municipal Key Clinical Specialty (shslczdzk01103), the Shanghai Rui** Hospital Three-Year Plan of the Clinical Skills and Innovations (2018CR005) and the Shanghai Three-year public health plan (GWV-10.1-XK13).

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Author notes

  1. Shaowen Jiang, Simin Guo and Yan Huang have contributed equally to this work.

Authors and Affiliations

  1. Department of Infectious Diseases, Rui** Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Shaowen Jiang, Simin Guo, Yan Huang, Huijuan Zhou, Qing Guo, Wei**g Wang, Haiguang **n & Qing **e

  2. School of Life Sciences, **amen University, **amen, China

    Yalin Yin

  3. School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China

    **gwen Feng

  4. Department of Infectious Diseases, Rui** Hospital North, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Wei**g Wang

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  1. Shaowen Jiang
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Contributions

QX, HX and WW were responsible for the study conceptualization, design, interpretation of data and obtaining funding. SJ and SG performed the literature search and drafted the manuscript. SG, YH and JF carried out the data extraction and statistical analysis. WW and SJ performed the quality assessment. YY, HZ and QG critically reviewed and revised the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Wei**g Wang, Haiguang **n or Qing **e.

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Conflict of interest

Shaowen Jiang, Simin Guo, Yan Huang, YalinYin, **gwen Feng, Huijuan Zhou, Qing Guo, Wei**g Wang, Haiguang **n, Qing **e declare that they have no conflict of interest.

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Jiang, S., Guo, S., Huang, Y. et al. Predictors of HBsAg seroclearance in patients with chronic HBV infection treated with pegylated interferon-α: a systematic review and meta-analysis. Hepatol Int 18, 892–903 (2024). https://doi.org/10.1007/s12072-024-10648-8

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