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Original article

Dynamics of HBV surface antigen related endpoints in chronic hepatitis B infection: a systematic review and meta-analysis

Yusi Chen, Justin Jinhui Li, Rong Chen, Gailing Li, Jia Ji

Corresponding author name: Jia Ji
Corresponding author e-mail: jji13@its.jnj.com

doi: 10.3851/IMP3366


Background: In chronic hepatitis B (CHB) treatment, hepatitis B virus surface antigen (HBsAg) is regarded as a promising clinical endpoint associated with long-term clinical outcomes. We performed a meta-analysis to characterize the dynamics and influencing factors of HBsAg.

Methods: Literature search was conducted through PubMed from January 1995 to May 2015 for papers reporting HBsAg in patients receiving various anti-viral treatments. We conducted weighted linear regression to select for potential influencing factors on maximum HBsAg loss percentage, and subgroup analysis to calculate the pooled estimates of maximum HBsAg loss and seroconversion percentage following treatment of interferon (IFN), nucleoside analogue (NUC), or combination therapies (NUC+IFN), respectively. Study heterogeneity was assessed through sensitivity test and I-square statistics.

Results: We collected data from 24 papers involving 6674 adult CHB patients. In most studies, average HBsAg level decreased during treatment but relapsed after treatment cessation, while HBsAg loss or seroconversion percentage continued to increase or remain stable after treatment cessation. No strong relationship was observed between maximum HBsAg change and its baseline level. The pooled estimates of maximum HBsAg loss percentage for IFN (5.3%, 2.7%-7.9%) and NUC+IFN (5.2%, 3.1%-7.4%) were significantly higher than that of NUC (0.93%, 0.29%-1.6%). Higher maximum HBsAg loss percentage is associated with longer peak time. Pooled maximum HBsAg seroconversion percentage estimates were 1.6%, 0.56% and 6.2% for IFN, NUC and NUC+IFN.

Conclusions: With respect to HBsAg lowering, this meta-analysis confirmed the importance of longer treatment duration and addition of IFN, which revealed the potential value of immune-based therapies.


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