National Clinical Research Center of Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, Mainland China.
Liver Research Center, Beijing Key Laboratory of Translational Medicine in Liver Cirrhosis, Beijing Friendship Hospital, Capital Medical University, Beijing, Mainland China.
Am J Gastroenterol. 2022 Sep 1;117(9):1444-1453. doi: 10.14309/ajg.0000000000001865. Epub 2022 Jun 10.
To assess comparative performance of 14 hepatocellular carcinoma (HCC) prediction models in chronic hepatitis B (CHB) patients using on-treatment values at different timepoints.
Based on a nationwide prospective cohort of 986 treatment-naive CHB patients undergoing entecavir therapy with every 26-week follow-up, 14 HCC risk scores were calculated using on-treatment values at week 26, 52, 78, and 104, respectively. Model performance predicting 3-year HCC was assessed using time-dependent area under the receiver operating characteristic curve (AUC) and calibration index. Model cutoffs were validated through common diagnostic accuracy measures.
During median 4.7-year follow-up, 56 (7.5%) developed HCC. Discrimination using on-treatment values within first 2 years was generally acceptable for most models (AUCs ranging from 0.68 to 0.81), except for REACH-B, NGM-HCC, and PAGE-B, although AUCs slightly decreased from week 26 to 104. Of these, REAL-B, CAMD, GAG-HCC, AASL-HCC, LSM-HCC, mPAGE-B, and mREACH-BII showed highest discrimination with AUCs ranging from 0.76 to 0.81, 0.72 to 0.76, 0.70 to 0.76, and 0.71 to 0.74 when reassessment at week 26, 52, 78, and 104, respectively. With reassessment within first 2 years, both REAL-B and CAMD calibrated well (Brier score ranging from 0.037 to 0.052). Of 9 models reporting cutoffs, REAL-B, AASL-HCC, and mPAGE-B using on-treatment values could identify 30%-40% of patients as low risk with minimal HCC incidence in the low-risk group (0.40% [REAL-B]-1.56% [mPAGE-B]).
In this undergoing antiviral treatment CHB cohort, most HCC prediction models performed well even using on-treatment values during first 2 years, particularly REAL-B, AASL-HCC, CAMD, and mPAGE-B model.
本研究旨在评估 14 种肝癌（HCC）预测模型在接受恩替卡韦治疗的慢性乙型肝炎（CHB）患者中的表现，这些模型使用的是不同时间点的治疗中值。
基于一项全国性的前瞻性队列研究，该研究纳入了 986 例未经治疗的 CHB 患者，他们接受恩替卡韦治疗，每 26 周进行一次随访。分别使用治疗中值在第 26、52、78 和 104 周时计算 14 种 HCC 风险评分。使用时间依赖性受试者工作特征曲线下面积（AUC）和校准指数评估预测 3 年 HCC 的模型性能。通过常用的诊断准确性指标验证模型截断值。
在中位 4.7 年的随访期间，56 例（7.5%）发生 HCC。在最初 2 年内使用治疗中值进行评估时，大多数模型的区分度普遍较好（AUC 范围为 0.68 至 0.81），除了 REACH-B、NGM-HCC 和 PAGE-B 模型，尽管 AUC 从第 26 周到第 104 周略有下降。在这些模型中，REAL-B、CAMD、GAG-HCC、AASL-HCC、LSM-HCC、mPAGE-B 和 mREACH-BII 的区分度最高，其 AUC 范围分别为 0.76 至 0.81、0.72 至 0.76、0.70 至 0.76 和 0.71 至 0.74，当在第 26、52、78 和 104 周重新评估时。在最初的 2 年内重新评估时，REAL-B 和 CAMD 的校准效果都很好（Brier 评分范围为 0.037 至 0.052）。在报告截断值的 9 个模型中，REAL-B、AASL-HCC 和 mPAGE-B 使用治疗中值可以将 30%至 40%的患者识别为低风险，低风险组的 HCC 发生率最低（0.40%[REAL-B]-1.56%[mPAGE-B]）。
在这项正在进行抗病毒治疗的 CHB 队列中，即使使用最初 2 年内的治疗中值，大多数 HCC 预测模型的表现都很好，尤其是 REAL-B、AASL-HCC、CAMD 和 mPAGE-B 模型。
