Hepatology, Hepatobiliopancreatic Surgery and Transplant Group, La Fe Health Research Institute (IIS La Fe), Valencia, Spain.
National Institute for the Study of Liver and Gastrointestinal Diseases, CIBEREHD, Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
United European Gastroenterol J. 2024 Sep;12(7):901-910. doi: 10.1002/ueg2.12571. Epub 2024 May 8.
BACKGROUND & AIMS: Several hepatocellular carcinoma (HCC) risk-models have been developed to individualise patient surveillance following sustained viral response (SVR) in Hepatitis C Virus patients. Validation of these models in different cohorts is an important step to incorporate a more personalised risk assessment in clinical practice. We aimed at applying these models to stratify the risk in our patients and potentially determine cost-saving associated with individualised HCC risk-stratification screening strategy.
Patients with baseline F3-4 fibrosis treated with new oral direct-acting antivirals who had reached a SVR were regularly followed as part of the HCC surveillance strategy. Six models were applied: Pons, aMAP, Ioannou, HCC risk, Alonso and Semmler. Validation of the models was performed based on sensitivity and the proportion of patients labelled as "high risk".
After excluding 557 with less than 3 fibrosis, 12 without SVR, 18 with a follow up (FU) <1 year, 17 transplant recipients, 16 lost to FU and 31 with HCC at time of antiviral therapy, our cohort consisted of 349 F3-4 SVR patients. Twenty-three patients (6.6%) developed HCC after a median FU of 5.12 years. The sensitivity of the different models varied between 0.17 (Semmler7noalcohol) and 1 (Alonso A and aMAP). The lowest proportion of high-risk patients corresponded to the Semmler-noalcohol model (5%). Sixty-three and 90% of the Alonso A and aMAP patients, respectively were labelled as high risk. The most reliable HCC risk-model applied to our cohort to predict HCC development is the Alonso model (based on fibrosis stage assessed by liver stiffness measurements or Fibrosis-4 index (FIB-4) at baseline and after 1 year, and albumin levels at 1 year) with a-100% sensitivity in detecting HCC among those at high risk and 63% labelled as high risk. The application of the model would have saved the cost of 1290 ultrasound no longer being performed in the 37% low-risk group.
In our cohort, the Alonso A model allows the most reliable reduction in HCC screening resulting in safely stopping life-long monitoring in about a third of F3-F4 patients achieving SVR with DAAs.
已经开发了几种肝癌（HCC）风险模型，以对丙型肝炎病毒患者持续病毒应答（SVR）后进行个体化患者监测。在不同队列中验证这些模型是将更个体化的风险评估纳入临床实践的重要步骤。我们旨在应用这些模型对我们的患者进行分层，并有潜力确定与个体化 HCC 风险分层筛查策略相关的节省成本。
基线 F3-4 纤维化的患者接受新的口服直接作用抗病毒药物治疗，达到 SVR 后作为 HCC 监测策略的一部分定期随访。应用了 6 种模型：Pons、aMAP、Ioannou、HCC 风险、Alonso 和 Semmler。根据敏感性和标记为“高危”的患者比例验证模型。
排除 557 例纤维化程度<3 级、12 例未达到 SVR、18 例随访<1 年、17 例移植受者、16 例随访丢失和 31 例抗病毒治疗时患有 HCC 的患者后，我们的队列包括 349 例 F3-4 SVR 患者。中位随访 5.12 年后，23 例患者（6.6%）发生 HCC。不同模型的敏感性在 0.17（Semmler7noalcohol）和 1（Alonso A 和 aMAP）之间变化。Semmler-noalcohol 模型的高危患者比例最低（5%）。Alonso A 和 aMAP 患者中分别有 63%和 90%被标记为高危。应用于我们队列中预测 HCC 发生的最可靠 HCC 风险模型是 Alonso 模型（基于基线和 1 年后的肝硬度测量或纤维化-4 指数（FIB-4）以及 1 年后的白蛋白水平评估的纤维化阶段），在高危人群中 HCC 的检测敏感性为 100%，有 63%被标记为高危。该模型的应用可节省在低危组中约 37%不再进行 1290 次超声检查的成本。
在我们的队列中，Alonso A 模型可以更可靠地减少 HCC 筛查，使大约三分之一达到 SVR 的 F3-F4 患者安全停止终生监测。
