Salman A. Precision stratification for hepatitis B functional cure: Biomarkers, machine learning and the combination-therapy era. World J Clin Cases 2026; 14(27): 126695 [DOI: 10.12998/wjcc.126695]
Corresponding Author of This Article
Ahmed Salman, FRACP, FRCP, Department of Internal Medicine, Kasr Alainy School of Medicine, 1 Al-Saray Street, Al-Manial, Cairo 11559, Al Qāhirah, Egypt. awea844@gmail.com
Research Domain of This Article
Gastroenterology & Hepatology
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review-article
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Salman A. Precision stratification for hepatitis B functional cure: Biomarkers, machine learning and the combination-therapy era. World J Clin Cases 2026; 14(27): 126695 [DOI: 10.12998/wjcc.126695]
World J Clin Cases. Sep 26, 2026; 14(27): 126695 Published online Sep 26, 2026. doi: 10.12998/wjcc.126695
Precision stratification for hepatitis B functional cure: Biomarkers, machine learning and the combination-therapy era
Ahmed Salman
Ahmed Salman, Department of Internal Medicine, Kasr Alainy School of Medicine, Cairo 11559, Al Qāhirah, Egypt
Author contributions: Salman A contributed to the conception and design of the review, the literature search, and drafting of the manuscript; data interpretation, and critical revision of the manuscript for important intellectual content.
AI contribution statement: ChatGPT (OpenAI; ChatGPT 5.6) assisted with literature searching, language editing, grammatical correction, and figure design. All AI-assisted content was reviewed and verified by the author, who takes full responsibility for the integrity, accuracy, and originality of the final work.
Conflict-of-interest statement: The author declares that he has no conflict of interest to disclose.
Corresponding author: Ahmed Salman, FRACP, FRCP, Department of Internal Medicine, Kasr Alainy School of Medicine, 1 Al-Saray Street, Al-Manial, Cairo 11559, Al Qāhirah, Egypt. awea844@gmail.com
Received: August 11, 2026 Revised: September 22, 2026 Accepted: October 9, 2026 Published online: September 26, 2026 Processing time: 63 Days and 21.5 Hours
Abstract
A functional cure for chronic hepatitis B remains uncommon despite effective viral suppression. Phase 3 bepirovirsen trials reported functional cure in 19%-20% of selected noncirrhotic patients who were receiving stable nucleos(t)ide analog therapy and had baseline hepatitis B surface antigen levels above 100 IU/mL and up to 3000 IU/mL. A lower baseline antigen level is associated with response across several regimens, but heterogeneous eligibility criteria and endpoints preclude attributing efficacy to selection alone. This narrative minireview examines serum biomarkers, selected prediction models, treatment-related harm, and residual hepatocellular carcinoma (HCC) risk after antigen loss. It distinguishes sustained off-treatment functional cure from antigen loss during continued background therapy, and separates pretreatment selection from on-treatment response prediction and post-clearance risk assessment. Existing models provide useful prognostic information; however, no integrated biomarker or machine learning model has been validated to allocate curative regimens. Observational evidence identifies substantial variation in HCC risk after antigen loss but does not establish the safety of surveillance withdrawal. Current society guidelines should govern clinical monitoring, whereas prospective studies should assess risk-based refinement. Diagnostic biomarker performance across genotypes does not establish transferable prediction of cure; external validation, calibration, assay standardization, and demonstrated clinical benefit remain prerequisites for implementation.
Core Tip: A low baseline hepatitis B surface antigen level is associated with response to several investigational regimens, but it should not be treated as a universal treatment-selection threshold. This minireview distinguishes functional cure from other antigen endpoints, separates baseline selection from on-treatment prediction, and appraises model validation, safety, and external validity. No integrated model is available for allocating curative regimens. Hepatocellular carcinoma risk persists after antigen loss; current guideline-based surveillance should continue where indicated, whereas prospective studies should evaluate risk-based refinement.
