biostudies-literatureLi JFujian Provincial Health Technology Projectthe Joint Funds for the Innovation of Science and Technology, Fujian ProvinceNational Natural Science Foundation of China2629088https://www.ebi.ac.uk/biostudies/studies/S-EPMC12915860biostudies-literatureUnknown17(1)Despite advances in antiviral therapy, the rate of functional cure for chronic hepatitis B (CHB) remains unsatisfactory, and developing an applicable prediction model is pivotal to improving it. Thus, we aimed to identify key predictive factors and develop prognostic models for functional cure in HBeAg-negative patients and the advantaged populations. This retrospective study included 202 HBeAg-negative CHB patients (114 classified as advantaged populations) receiving pegylated interferon-alpha (PEG-IFNα) therapy for model derivation and internal validation, and 183 HBeAg-negative CHB patients (117 classified as advantaged populations) for model external validation. Using 48 routinely collected clinical indicators, we constructed prediction models through LASSO regression followed by multiVirulenceMachine learning prediction of functional cure to pegylated interferon-alpha therapy in two HBV populations: Advantaged populations and HBeAg-negative patients.PMC129158602024CXA018824723442023Y9018Yang XLi HLi JLin CHe YXun ZJiang RZheng QGong KWang LfalseMachine learning prediction of functional cure to pegylated interferon-alpha therapy in two HBV populations: Advantaged populations and HBeAg-negative patients.Despite advances in antiviral therapy, the rate of functional cure for chronic hepatitis B (CHB) remains unsatisfactory, and developing an applicable prediction model is pivotal to improving it. Thus, we aimed to identify key predictive factors and develop prognostic models for functional cure in HBeAg-negative patients and the advantaged populations. This retrospective study included 202 HBeAg-negative CHB patients (114 classified as advantaged populations) receiving pegylated interferon-alpha (PEG-IFNα) therapy for model derivation and internal validation, and 183 HBeAg-negative CHB patients (117 classified as advantaged populations) for model external validation. Using 48 routinely collected clinical indicators, we constructed prediction models through LASSO regression followed by multi2026-01-01T00:00:00Z2026 Dec2026-07-16T06:40:38.867Z2026-07-09T10:40:34.777ZS-EPMC129158604165692010.1080/21505594.2026.2629088