Prediction of long-term HBsAg seroclearance in patients with HBeAg-negative chronic hepatitis B.

Background & Aims: Predicting the long-term HBsAg seroclearance, an ideal endpoint, is relevant for decision-making regarding antiviral therapy for patients with chronic hepatitis B (CHB). This study aimed to identify predictors and develop a prediction model for HBsAg seroclearance in patients with HBeAg-negative CHB. Methods: A total of 2,032 untreated HBeAg-negative patients who underwent a 2-year baseline observation period were enrolled. Prediction models were developed using independent predictors of seroclearance, and their performance was evaluated through internal and external validation using an independent cohort of 753 patients, along with sensitivity analyses. Results: The estimated annual incidence of HBsAg seroclearance was 2.22% (15,508 person-years). Conclusions: The HepBLOSS models for HBsAg seroclearance exhibited an outstanding ability to stratify the probability of seroclearance over a 15-year period. These models hold promising potential to guide treatment decisions, aiming to achieve a functional cure in patients with CHB. Impact and implications: Achieving a functional cure for chronic hepatitis B, defined as HBsAg seroclearance, is a realistic treatment endpoint, especially given the virus's lifelong persistence in hepatocytes and its significant association with improved prognosis. This study identified independent predictors of seroclearance, including HBV DNA levels, age, sex, and HBsAg levels, and developed a robust prediction model based on these factors. The models demonstrated strong predictive accuracy over a 15-year period, offering valuable guidance for clinicians in establishing treatment strategies and predicting patient prognosis.