Models for predicting hepatitis B e antigen seroconversion in response to interferon-α in chronic hepatitis B...

Area of Science:

• Hepatology
• Virology
• Immunology

Background:

• Chronic hepatitis B (CHB) infection affects millions globally.
• Hepatitis B e antigen (HBeAg) seroconversion is a key indicator of treatment response.
• Interferon-alpha (IFN-α) is a treatment option for CHB.

Purpose of the Study:

• To develop predictive models for HBeAg seroconversion in CHB patients treated with IFN-α.
• To identify baseline and on-treatment predictors of response to IFN-α therapy.

Main Methods:

• 147 treatment-naïve HBeAg-positive CHB patients in China were analyzed.
• Serum biomarkers including ALT, HBV DNA, HBsAg, HBeAg, and anti-HBc were measured at multiple time points.
• Univariate and multivariate analyses were used to identify predictors and construct predictive models.

Main Results:

• Baseline predictors of seroconversion included high ALT, low HBeAg, and high anti-HBc levels.
• On-treatment predictors at 12 and 24 weeks included HBeAg levels, HBeAg decline, and anti-HBc levels.
• Models incorporating these factors showed significant differences in response rates based on predictive scores.

Conclusions:

• Predictive models with good positive and negative values were developed for IFN-α therapy response.
• These models can aid in calculating the probability of HBeAg seroconversion during IFN-α treatment.