Kugelmas Marcelo, Noureddin Mazen, Gunn Nadege, Brown Kimberly, Younossi Zobair, Abdelmalek Manal, Alkhouri Naim
South Denver Gastroenterology, Englewood, Colorado, USA.
Houston Research Institute, Houston, Texas, USA.
Liver Int. 2023 May;43(5):964-974. doi: 10.1111/liv.15555. Epub 2023 Mar 27.
There is ongoing recognition of the burden of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), with fibrosis being the most important histological feature that is associated with progression to cirrhosis and the occurrence of major adverse liver outcomes. Liver biopsy is the gold standard applied to detect NASH and determine the stage of fibrosis, but its use is limited. There is a need for non-invasive testing (NIT) techniques to identify patients considered at-risk NASH (NASH with NAFLD activity score > 4 and ≥ F2 fibrosis). For NAFLD-associated fibrosis, several wet (serological) and dry (imaging) NITs are available and demonstrate a high negative predictive value (NPV) for excluding those with advanced hepatic fibrosis. However, identifying at-risk NASH is more challenging; there is little guidance on how to use available NITs for these purposes, and these NITs are not specifically designed to identify at-risk NASH patients. This review discusses the need for NITs in NAFLD and NASH and provides data to support the use of NITs, focusing on newer methods to non-invasively identify at-risk NASH patients. This review concludes with an algorithm that serves as an example of how NITs can be integrated into care pathways of patients with suspected NAFLD and potential NASH. This algorithm can be used for staging, risk stratification and the effective transition of patients who may benefit from specialty care.
非酒精性脂肪性肝病(NAFLD)和非酒精性脂肪性肝炎(NASH)的负担日益受到关注,纤维化是最重要的组织学特征,与肝硬化进展及主要不良肝脏结局的发生相关。肝活检是用于检测NASH和确定纤维化阶段的金标准,但应用有限。需要非侵入性检测(NIT)技术来识别被认为有NASH风险的患者(NAFLD活动评分>4且纤维化≥F2的NASH)。对于NAFLD相关纤维化,有几种湿式(血清学)和干式(影像学)NIT可供使用,并且在排除晚期肝纤维化患者方面显示出较高的阴性预测值(NPV)。然而,识别有NASH风险的患者更具挑战性;关于如何将现有NIT用于这些目的几乎没有指导,并且这些NIT并非专门设计用于识别有NASH风险的患者。本综述讨论了NAFLD和NASH中对NIT的需求,并提供数据支持NIT的使用,重点关注非侵入性识别有NASH风险患者的新方法。本综述最后给出了一个算法,作为NIT如何整合到疑似NAFLD和潜在NASH患者护理路径中的示例。该算法可用于分期、风险分层以及可能受益于专科护理的患者的有效转诊。