Related Experiment Video
Updated: Feb 2, 2026
Induction and Clinical Scoring of Chronic-Relapsing Experimental Autoimmune Encephalomyelitis
Published on: July 4, 2007
Risk factors and predicted model for clinical relapse after antiviral therapy cessation in chronic hepatitis B
Xiaoli Zhang1, Meiyan Mao2, Yunxia Zhang1
1Department of Infectious Diseases, Southern Central Hospital of Yunnan Province (The First People's Hospital of Honghe State), Gejiu, 661000, Yunnan, China.
Insights
Older age, higher HBV DNA levels, and shorter antiviral treatment duration increase the risk of chronic hepatitis B (CHB) relapse after stopping therapy. A predictive model incorporating these factors shows good clinical value for anticipating relapse.
Area of Science:
- Hepatology
- Virology
- Clinical Medicine
Background:
- Chronic hepatitis B (CHB) management involves antiviral therapy, but relapse risk after discontinuation is a concern.
- Understanding factors predicting relapse is crucial for optimizing treatment strategies and patient monitoring.
Purpose of the Study:
- To identify risk factors for clinical relapse in CHB patients after discontinuing antiviral therapy.
- To develop and validate a predictive model for clinical relapse within two years post-treatment cessation.
Main Methods:
- Retrospective analysis of 99 CHB patients who discontinued antiviral therapy (nucleos(t)ide analogs or interferon).
- Multivariate logistic regression used to identify independent risk factors for relapse.
- A predictive model was constructed and evaluated using ROC analysis.
Main Results:
- 45.45% of patients relapsed within two years of discontinuing therapy.
- Independent risk factors for relapse included older age, higher HBsAg levels, higher HBV DNA load at discontinuation, and shorter total antiviral treatment duration.
- The developed predictive model demonstrated high accuracy (AUC=0.945) for predicting 2-year clinical relapse.
Conclusions:
- Age, HBV DNA load, HBsAg levels at discontinuation, and total antiviral duration are key predictors of CHB relapse.
- The established predictive model offers significant clinical utility for assessing relapse risk in CHB patients after treatment cessation.
Background:
This study aimed to analyze the risk factors and predicted model for clinical relapse after discontinuation of antiviral therapy in patients with chronic hepatitis B (CHB).
Methods:
A retrospective analysis was conducted on the clinical data of 99 CHB patients who met the discontinuation criteria and were treated at Southern Central Hospital of Yunnan Province (The First People's Hospital of Honghe State) from March 2020 to December 2022. All subjects received nucleos(t)ide analogs (NAs) or interferon-based antiviral therapy and discontinued treatment once they met the cessation criteria, followed by a 2-year follow-up. Based on relapse status, patients were divided into a relapse group and a non-relapse group. Clinical characteristics were compared between the two groups. A multivariate logistic regression analysis was performed to analyze the independent risk factors for clinical relapse within 2 years after treatment cessation.
Results:
During the 2-year follow-up, 45 patients (45.45%) experienced clinical relapse after discontinuation. Compared with the non-relapse group, the relapse group exhibited significantly higher age, HBsAg levels at treatment cessation, and HBV DNA load at discontinuation (p < 0.05), as well as a shorter total duration of antiviral therapy (p < 0.05). Multivariate analysis revealed that age, total antiviral treatment duration, HBV DNA load at discontinuation, and HBsAg levels at cessation were independent risk factors for clinical relapse of CHB patients (p < 0.05). A combined predictive model was constructed based on multivariate logistic regression coefficients: combined model = -17.497 + 0.181 × age + (-0.123) × total antiviral duration + 1.746 × HBV DNA at discontinuation + 0.032 × HBsAg at discontinuation. ROC analysis demonstrated that the AUC of the combined model was 0.945 (95% CI: 0.902-0.987) for predicting 2-year clinical relapse, with a sensitivity of 91.11% and specificity of 83.33%. Spearman correlation analysis indicated that patient age and HBV DNA load at discontinuation were negatively correlated with time to relapse (p < 0.05), whereas HBsAg levels showed no significant correlation with total antiviral duration (p > 0.05).
Conclusions:
Age, HBV DNA load at discontinuation, HBsAg quantification at discontinuation, and the total antiviral duration were identified as key factors influencing clinical relapse after cessation of antiviral therapy in patients with CHB. A predictive model incorporating these factors demonstrated good clinical predictive value.
Related Concept Videos
01:26Factors Affecting the Risk of Infection
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
01:12Statistical Software for Data Analysis and Clinical Trials
01:16Hepatic Drug Excretion: Influencing Factors
01:29Factors Affecting Protein-Drug Binding: Patient-Related Factors
Age stands as a key determinant in protein-drug binding. Neonates, characterized by low albumin content, experience heightened concentrations of unbound drugs such as phenytoin and...
01:24Chronic Kidney Disease II: Clinical Manifestations
01:14Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...