NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, California, USA.
Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Hepatology. 2023 Dec 1;78(6):1858-1866. doi: 10.1097/HEP.0000000000000470. Epub 2023 May 22.
Magnetic resonance elastography (MRE) is an accurate, continuous biomarker of liver fibrosis; however, the optimal combination with clinical factors to predict the risk of incident hepatic decompensation is unknown. Therefore, we aimed to develop and validate an MRE-based prediction model for hepatic decompensation for patients with NAFLD.
This international multicenter cohort study included participants with NAFLD undergoing MRE from 6 hospitals. A total of 1254 participants were randomly assigned as training (n = 627) and validation (n = 627) cohorts. The primary end point was hepatic decompensation, defined as the first occurrence of variceal hemorrhage, ascites, or HE. Covariates associated with hepatic decompensation on Cox-regression were combined with MRE to construct a risk prediction model in the training cohort and then tested in the validation cohort. The median (IQR) age and MRE values were 61 (18) years and 3.5 (2.5) kPa in the training cohort and 60 (20) years and 3.4 (2.5) kPa in the validation cohort, respectively. The MRE-based multivariable model that included age, MRE, albumin, aspartate aminotransferase, and platelets had excellent discrimination for the 3- and 5-year risk of hepatic decompensation (c-statistic 0.912 and 0.891, respectively) in the training cohort. The diagnostic accuracy remained consistent in the validation cohort with a c-statistic of 0.871 and 0.876 for hepatic decompensation at 3 and 5 years, respectively, and was superior to Fibrosis-4 in both cohorts ( p < 0.05).
An MRE-based prediction model allows for accurate prediction of hepatic decompensation and assists in the risk stratification of patients with NAFLD.
磁共振弹性成像（MRE）是一种准确、连续的肝纤维化生物标志物；然而，将其与临床因素相结合，以预测肝失代偿事件的风险尚不清楚。因此，我们旨在开发和验证一种基于 MRE 的预测模型，以预测非酒精性脂肪性肝病（NAFLD）患者的肝失代偿。
这是一项国际多中心队列研究，纳入了来自 6 家医院的 MRE 检查的 NAFLD 患者。共有 1254 名患者被随机分配到训练队列（n = 627）和验证队列（n = 627）。主要终点是肝失代偿，定义为首次出现静脉曲张出血、腹水或肝性脑病。对 Cox 回归中与肝失代偿相关的协变量与 MRE 相结合，在训练队列中构建风险预测模型，然后在验证队列中进行测试。训练队列中患者的中位（IQR）年龄和 MRE 值分别为 61（18）岁和 3.5（2.5）kPa，验证队列中患者的中位（IQR）年龄和 MRE 值分别为 60（20）岁和 3.4（2.5）kPa。该 MRE 多变量模型纳入了年龄、MRE、白蛋白、天冬氨酸氨基转移酶和血小板，在训练队列中对 3 年和 5 年肝失代偿风险的区分度极佳（c 统计值分别为 0.912 和 0.891）。在验证队列中，该模型的诊断准确性仍然一致，3 年和 5 年肝失代偿的 c 统计值分别为 0.871 和 0.876，且优于两个队列中的 Fibrosis-4（p < 0.05）。
基于 MRE 的预测模型可以准确预测肝失代偿，并有助于对 NAFLD 患者进行风险分层。
