人们普遍认为，抗病毒治疗可以降低乙型肝炎病毒（HBV）相关肝细胞癌（HCC）的发病率，但仍有一部分慢性乙型肝炎病毒感染患者尽管接受抗病毒治疗，仍会发展为肝细胞癌。本研究旨在开发一种能够在开始抗病毒治疗之前预测慢性 HBV 感染患者长期发生 HCC 的模型。非选择性纳入2006年4月至2023年3月期间接受初始抗病毒治疗并完成长期随访的1450名慢性乙型肝炎患者。使用最小绝对收缩和选择算子（LASSO）和Cox回归分析来构建模型。结果在外部队列（n = 210）中得到验证，并与现有模型进行比较。所有患者的中位随访时间为60个月，最长随访时间为144个月，期间发生HCC 32例。构建了基于GGT、AFP、肝硬化、性别、年龄和乙型肝炎e抗体预测HCC的列线图模型（TARGET-HCC），表现出良好的预测性能。在推导队列中，C 指数为 0.906 (95% CI = 0.869-0.944)，在验证队列中，C 指数为 0.780 (95% CI = 0.673-0.886)。与现有模型相比，TARGET-HCC 显示出有希望的预测性能。此外，时间依赖性特征重要性曲线表明，在抗病毒治疗的最初十年中，性别始终是 HCC 最稳定的预测因子。这种基于无创临床特征的简单预测模型可以帮助临床医生在开始抗病毒治疗之前识别慢性 HBV 感染的 HCC 高危患者。© 2024 Wiley periodicals LLC。

It is generally acknowledged that antiviral therapy can reduce the incidence of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), there remains a subset of patients with chronic HBV infection who develop HCC despite receiving antiviral treatment. This study aimed to develop a model capable of predicting the long-term occurrence of HCC in patients with chronic HBV infection before initiating antiviral therapy. A total of 1450 patients with chronic HBV infection, who received initial antiviral therapy between April 2006 and March 2023 and completed long-term follow-ups, were nonselectively enrolled in this study. Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis was used to construct the model. The results were validated in an external cohort (n = 210) and compared with existing models. The median follow-up time for all patients was 60 months, with a maximum follow-up time of 144 months, during which, 32 cases of HCC occurred. The nomogram model for predicting HCC based on GGT, AFP, cirrhosis, gender, age, and hepatitis B e antibody (TARGET-HCC) was constructed, demonstrating a good predictive performance. In the derivation cohort, the C-index was 0.906 (95% CI = 0.869-0.944), and in the validation cohort, it was 0.780 (95% CI = 0.673-0.886). Compared with existing models, TARGET-HCC showed promising predictive performance. Additionally, the time-dependent feature importance curve indicated that gender consistently remained the most stable predictor for HCC throughout the initial decade of antiviral therapy. This simple predictive model based on noninvasive clinical features can assist clinicians in identifying high-risk patients with chronic HBV infection for HCC before the initiation of antiviral therapy.© 2024 Wiley Periodicals LLC.