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Mouse Model of Metabolic Dysfunction-Associated Steatotic Liver Disease with Fibrosis
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Review Article: Fibrosis-4 Index in Steatotic Liver Disease-Past, Present and Future
Kriti Soni1, Vinay Jahagirdar1, Omar Albhaisi1
1Division of Gastroenterology, Hepatology, and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, Virginia, USA.
Background:
Steatotic liver disease (SLD) is highly prevalent, and fibrosis stage is the strongest determinant of liver-related outcomes, hepatocellular carcinoma and mortality. Liver biopsy remains the reference standard for staging, but it is invasive, subject to sampling and observer variability. These limitations have accelerated the use of noninvasive tests (NITs) across various settings.
Aims:
This review summarizes the past, present and future of the Fibrosis-4 (FIB-4) index in SLD.
Methods:
We reviewed the development of serum-based fibrosis assessment, validation of FIB-4 across SLD subtypes, its incorporation into clinical pathways, real-world performance and potential role in precision therapy and longitudinal risk assessment.
Results:
Initially derived in patients with HIV/hepatitis C coinfection using age, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and platelet count, FIB-4 has since been validated across SLD populations. FIB-4 generally provides moderate discrimination for advanced fibrosis and high negative predictive value (NPV) when used with dual thresholds and age-adjusted cutoffs. Modern care pathways operationalize FIB-4 as the first-line triage test, followed by transient elastography or another second line test for indeterminate or elevated results, with specialty referral and selective biopsy reserved for diagnostic uncertainty or discordant testing.
Conclusions:
In the precision therapy era, FIB-4 remains a scalable front-door test but should not serve as a stand-alone selector for drug eligibility; confirmatory staging is required to identify F2-F3 disease and exclude cirrhosis. Future directions include trajectory-based monitoring, integration with elastography and multi-analyte biomarkers, and selective layering of genetic risk to refine prognosis in intermediate and high-risk strata.
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