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Lookup NU author(s): Helen Jarvis
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2026 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/. Steatotic liver disease (SLD) is the leading cause of chronic liver disease in Europe, with liver fibrosis representing the strongest predictor of liver-related outcomes and an important contributor to cardiometabolic risk. This Series paper examines diagnostic innovation and models of care to improve fibrosis detection and risk stratification across the continuum of care for SLD. A growing range of non-invasive tests for fibrosis assessment is now available, including blood-based biomarkers, imaging modalities, automated laboratory algorithms, and artificial intelligence-enabled tools. However, implementation remains inconsistent because of limited awareness, restricted geographic and financial access to advanced diagnostics, fragmented referral pathways, heterogeneous reimbursement, limited use of automated reflex testing, and poor digital integration across laboratories and electronic health records. Integrated multidisciplinary models of care linking primary care with specialist services may improve early fibrosis detection, referral efficiency, and equitable access to risk-stratified management, particularly among people living with indicator conditions such as type 2 diabetes and obesity.
Author(s): Pugliese N, White TM, Brennan PN, Pannain S, Hagstrom H, Michel M, Rice-Duek L, Targher G, Caussy C, Dillon JF, Tacke F, Kopka CJ, Sebastiani G, Boursier J, Tsochatzis EA, Brouwer WP, Guaraldi G, Vettor R, Thiele M, Roden M, Stefan N, Jarvis H, Gines P, Schattenberg JM, Pose E, Buttigieg S, Byrne CD, Lazarus JV
Publication type: Review
Publication status: Published
Journal: The Lancet Regional Health - Europe
Year: 2026
Volume: 65
Print publication date: 01/06/2026
Online publication date: 25/06/2026
Acceptance date: 11/05/2026
ISSN (electronic): 2666-7762
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.lanepe.2026.101722
DOI: 10.1016/j.lanepe.2026.101722
