Suita, Japan.
Amagasaki, Japan.
Aliment Pharmacol Ther. 2021 Nov;54(10):1340-1349. doi: 10.1111/apt.16632. Epub 2021 Oct 7.
Several factors associated with hepatocellular carcinoma (HCC) occurrence after sustained virological response (SVR) in patients with hepatitis C have been reported. However, few validation studies have been performed in the era of direct-acting anti-virals (DAAs).
To develop a prediction model for HCC occurrence after DAA-mediated SVR and validate its usefulness.
We analysed 2209 patients with SVR and without a history of HCC who initiated DAA treatment at 24 Japanese hospitals. These patients were divided into a training set (1473 patients) and a validation set (736 patients).
In the training set, multivariate Cox proportional hazards analysis showed that the baseline BMI (≥25.0 kg/m , P = 0.024), baseline fibrosis-4 (FIB-4) index (≥3.25, P = 0.001), albumin level at SVR (<4.0 g/dL, P = 0.010) and alpha-foetoprotein level at SVR (≥5.0 ng/mL, P = 0.006) were significantly associated with HCC occurrence. We constructed a prediction model for HCC occurrence with these four factors (2 points were added for the FIB-4 index, and 1 point was added for each of the other three factors). Receiver operating characteristics curve analysis identified a score of 2 as the optimal cut-off value for the prediction model (divided into 0-1 and 2-5). In the validation set, the sensitivity and negative predictive value for HCC occurrence were 87.5% and 99.7%, respectively, at 2 years and 71.4% and 98.0%, respectively, at 3 years.
A prediction model combining these four factors contributes to an efficient surveillance strategy for HCC occurrence after DAA-mediated SVR.
已有研究报道了丙型肝炎患者获得持续病毒学应答（SVR）后发生肝细胞癌（HCC）的多种相关因素。然而，在直接作用抗病毒药物（DAA）时代，仅有少数验证性研究。
建立 DAA 介导的 SVR 后 HCC 发生的预测模型并验证其有效性。
我们分析了 2209 例在 24 家日本医院接受 DAA 治疗且无 HCC 病史的 SVR 患者。这些患者被分为训练集（1473 例）和验证集（736 例）。
在训练集中，多变量 Cox 比例风险分析显示，基线时体重指数（BMI）（≥25.0kg/m ，P=0.024）、基线纤维化-4（FIB-4）指数（≥3.25，P=0.001）、SVR 时白蛋白水平（<4.0g/dL，P=0.010）和 SVR 时甲胎蛋白水平（≥5.0ng/mL，P=0.006）与 HCC 发生显著相关。我们构建了一个基于这四个因素的 HCC 发生预测模型（FIB-4 指数加 2 分，其他三个因素各加 1 分）。受试者工作特征曲线分析确定 2 分为预测模型的最佳截断值（分为 0-1 分和 2-5 分）。在验证集中，该模型在 2 年时预测 HCC 发生的敏感性和阴性预测值分别为 87.5%和 99.7%，在 3 年时分别为 71.4%和 98.0%。
该模型结合了这四个因素，有助于制定 DAA 介导的 SVR 后 HCC 发生的高效监测策略。
