articleJAMAMar 21, 2024GREEN OA

Vibration-Controlled Transient Elastography Scores to Predict Liver-Related Events in Steatotic Liver Disease

Chinese University of Hong Kong · Yonsei University · +29 more institutions

PubMed
Indexed incrossrefpubmed

Abstract

Importance

Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most common chronic liver disease worldwide. It is important to develop noninvasive tests to assess the disease severity and prognosis.

Objective

To study the prognostic implications of baseline levels and dynamic changes of the vibration-controlled transient elastography (VCTE)-based scores developed for the diagnosis of advanced fibrosis (Agile 3+) and cirrhosis (Agile 4) in patients with MASLD. Design, Setting, and Participants: This cohort study included data from a natural history cohort of patients with MASLD who underwent VCTE examination at 16 tertiary referral centers in the US, Europe, and Asia from February 2004 to January 2023, of which the data were collected prospectively at 14 centers. Eligible patients were adults aged at least 18 years with hepatic steatosis diagnosed by histologic methods (steatosis in ≥5% of hepatocytes) or imaging studies (ultrasonography, computed tomography or magnetic resonance imaging, or controlled attenuation parameter ≥248 dB/m by VCTE). Main Outcomes and Measures: The primary outcome was liver-related events (LREs), defined as hepatocellular carcinoma or hepatic decompensation (ascites, variceal hemorrhage, hepatic encephalopathy, or hepatorenal syndrome), liver transplant, and liver-related deaths. The Agile scores were compared with histologic and 8 other noninvasive tests.

Citation impact

195
total citations
FWCI
68.39
Percentile
100%
References
32
Citations per year

Authors

40

Topics & keywords

Keywords
  • Medicine
  • Transient elastography
  • Transient (computer programming)
  • Liver disease
  • Internal medicine
  • Radiology
  • Gastroenterology
  • Pathology
UN Sustainable Development Goals
  • Reduced inequalities
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Funding