HBsAg Quantification‐Based Models for Predicting Hepatocellular Carcinoma Risk in Nucleos(t)ide Analogs‐Experienced Patients With Chronic Hepatitis B: The HBsAg ‐ HCC Score

医学 肝细胞癌 内科学 慢性肝炎 乙型肝炎表面抗原 肿瘤科 危险分层 胃肠病学 风险评估 梅德林 乙型肝炎 风险因素 弗雷明翰风险评分 试验预测值 预测模型 慢性病
作者
Yi‐Fan Guo,Xiao‐Xia Niu,Le Li,Yan Chen,Yan Liu,Chang Guo,Meng‐Qi Sun,Yi‐Zhe Zhang,Xu‐Yang Li,Chunyan Wang,Yi-Xiang Wang,Lin Tan,George Lau,Dong Ji
出处
期刊:Alimentary Pharmacology & Therapeutics [Wiley]
卷期号:64 (1): 62-73
标识
DOI:10.1111/apt.70652
摘要

BACKGROUND: Chronic hepatitis B (CHB) virus infection is the leading cause of hepatocellular carcinoma (HCC). Nucleos(t)ide analogs (NAs) effectively suppress HBV replication, but residual HCC risk remains in treated patients, highlighting the need for reliable risk stratification tools. Existing prediction models rely heavily on age and liver function parameters and often overlook hepatitis B surface antigen (HBsAg) quantification, a key marker closely tied to HBV-related HCC, resulting in inadequate clinical predictive accuracy. METHODS: To address this gap, we developed the novel HBsAg-HCC Score using a two-cohort design: retrospective training (1190 NA-treated CHB patients) with Cox regression to identify independent HCC risk factors, followed by validation in an independent prospective cohort (506 patients). Its performance was compared with three established tools (PAGE-B, mPAGE-B, aMAP). RESULTS: Five independent HCC risk factors were identified: higher HBsAg levels, older age, male sex, hypoproteinaemia, and elevated APRI. The HBsAg-HCC Score derived from these factors showed strong predictive power: 3-/5-/7-year AUCs of 0.867/0.872/0.871 in the training cohort (significantly outperforming PAGE-B, mPAGE-B, aMAP) and 0.784/0.780/0.777 in the validation cohort. Internal and external cross-validation confirmed its stability and reliability. CONCLUSIONS: By incorporating HBsAg quantification, a virus-specific marker often missing from conventional models, the HBsAg-HCC Score offers a more comprehensive and accurate approach to HCC risk stratification in NAs-experienced CHB patients, addressing a critical limitation of existing models directly.
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