Liver stiffness thresholds to predict disease progression and clinical outcomes in bridging fibrosis and cirrhosis

GUT(2023)

引用 15|浏览44
暂无评分
摘要
Objective In retrospective studies, liver stiffness (LS) by vibration-controlled transient elastography (VCTE) is associated with the risk of liver decompensation in patients with non-alcoholic steatohepatitis (NASH), but prospective data in biopsy-confirmed cohorts with advanced fibrosis are limited. We aimed to establish thresholds for LS by VCTE that predict progression to cirrhosis among patients with bridging fibrosis and hepatic decompensation among patients with cirrhosis due to NASH. Design We used data from four randomised placebo-controlled trials of selonsertib and simtuzumab in participants with advanced fibrosis (F3-F4). The trials were discontinued due to lack of efficacy. Liver fibrosis was staged centrally at baseline and week 48 (selonsertib study) or week 96 (simtuzumab study). Associations between LS by VCTE with disease progression were determined using Cox proportional hazards regression analysis. Results Progression to cirrhosis occurred in 16% (103/664) of participants with bridging fibrosis and adjudicated liver-related events occurred in 4% (27/734) of participants with baseline cirrhosis. The optimal baseline LS thresholds were >= 16.6 kPa for predicting progression to cirrhosis, and >= 30.7 kPa for predicting liver-related events. Baseline LS >= 16.6 kPa (adjusted HR 3.99; 95% CI 2.66 to 5.98, p<0.0001) and a >= 5 kPa (and >= 20%) increase (adjusted HR 1.98; 95% CI 1.20 to 3.26, p=0.008) were independent predictors of progression to cirrhosis in participants with bridging fibrosis, while baseline LS >= 30.7 kPa (adjusted HR 10.13, 95% CI 4.38 to 23.41, p<0.0001) predicted liver-related events in participants with cirrhosis. Conclusion The LS thresholds identified in this study may be useful for risk stratification of NASH patients with advanced fibrosis.
更多
查看译文
关键词
cirrhosis,fibrosis,nonalcoholic steatohepatitis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要