# Predictive value of HBeAg titer dynamics for HBsAg clearance in pediatric chronic hepatitis B

## TL;DR

This study finds that tracking HBeAg levels and age in children with hepatitis B can predict if they will clear the virus, helping doctors tailor treatments.

## Contribution

The study introduces a predictive model combining HBeAg titer dynamics and age to forecast HBsAg clearance in pediatric hepatitis B patients.

## Key findings

- Younger age and steeper HBeAg titer decline are strongly associated with HBsAg clearance in children.
- A logistic regression model using HBeAg titer reduction and age accurately predicts HBsAg clearance probability.
- Children aged ≤6 years showed a significantly higher HBsAg loss rate compared to older children.

## Abstract

Achieving functional cure of chronic hepatitis B (CHB), characterized by the loss of HBV DNA and HBsAg, remains challenging in adults but demonstrates higher success rates in children. Elucidating the factors influencing HBsAg loss in pediatric patients is crucial for optimizing treatment strategies. This study aimed to evaluate the predictive value of HBeAg titer dynamics for HBsAg clearance in pediatric CHB and develop a predictive model incorporating these dynamics.

This retrospective cohort study analyzed 119 children aged 1–18 years with CHB treated with nucleos(t)ide analogues. Patient outcomes were evaluated using two independent classification approaches: HBsAg loss status and age stratification (≤6 vs. >6 years). Treatment response was assessed through longitudinal HBeAg titer measurements during the first 12 months. Based on identified predictors, a logistic regression model was developed incorporating age and HBeAg titer dynamics to predict HBsAg clearance probability.

The study population exhibited a median age of 6.2 years. Factors associated with HBsAg loss encompassed younger age, female sex, and absence of breakthrough. In multivariate analysis, younger age was identified as the only significant factor. The cumulative HBsAg loss rate demonstrated markedly higher values in the ≤6 years group (Hazard ratio 7.69). HBeAg titer decline exhibited significantly steeper trajectories in the HBsAg loss group. The developed predictive model, “Log Odds = −1.182 + 0.308 × log_reduction−0.205 × age”, demonstrated good performance with high accuracy.

Early HBeAg titer dynamics combined with age at treatment initiation may serve as useful predictors of HBsAg clearance in pediatric CHB. Our predictive model, utilizing readily available semi-quantitative HBeAg measurements, could potentially assist clinicians in therapeutic decision-making and individualized treatment strategies.