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Author Spotlight: Advancements and Challenges in Hepatitis B Virus Detection
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Modeling covalently closed circular DNA dynamics in assessing chronic hepatitis B prognosis
Qiulin Huang1, Qiang Li2, Zaitang Huang3
1School of Mathematics and Statistics, Southwest University, Chongqing, 400715, China.
Mathematical Biosciences
|November 13, 2025
Summary
This study introduces a mathematical model to predict hepatitis B virus (HBV) covalently closed circular DNA (cccDNA) levels. The model accurately forecasts serologic negative conversion (SNC) in chronic hepatitis B (CHB) patients, aiding treatment strategies.
Area of Science:
- Virology
- Mathematical Biology
- Hepatology
Background:
- Covalently closed circular DNA (cccDNA) persistence in HBV-infected hepatocytes drives chronic hepatitis B (CHB) pathogenesis.
- Hepatitis B surface antigen (HBsAg) levels serve as a surrogate marker for cccDNA quantification.
Purpose of the Study:
- To develop and validate a mathematical model for predicting cccDNA kinetics in HBV-infected hepatocytes.
- To assess the model's accuracy in forecasting serologic negative conversion (SNC) in CHB patients.
Main Methods:
- Development of a mathematical model to simulate cccDNA dynamics.
- Analysis of clinical data from 96 newly treated CHB patients.
- Calculation of the basic reproduction rate and identification of backward bifurcation.
Main Results:
- The mathematical model demonstrated a high concordance rate (93.75%) with clinical outcomes for SNC prediction.
- Baseline HBsAg, HBV DNA, and hepatitis e surface antigen levels significantly influence model accuracy.
- Backward bifurcation was identified in the cccDNA kinetics model.
Conclusions:
- The proposed mathematical model effectively predicts SNC in CHB patients.
- The model's accuracy is influenced by baseline viral markers.
- This model can assist in designing clinical withdrawal indicators for CHB treatment.
