Diagnostic innovation and models of care to improve fibrosis detection and risk stratification in steatotic liver disease
Abstract
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.
Related
- Prediction Models Versus Fibrosis-4 Index (FIB-4) for Advanced Fibrosis in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD): A Verification-Audited Systematic Review and Meta-Analysis
- Comparison of Metabolic Dysfunction‐Associated Steatotic Liver Disease Between Individuals With Werner Syndrome and Those With Insulin‐Resistant Type 2 Diabetes: Hepatic Steatosis and Fibrosis Indices
- Factors associated with significant liver fibrosis in patients with type 2 diabetes mellitus and metabolic dysfunction-associated steatotic liver disease: a single-center retrospective study
- Screening for metabolic dysfunction-associated steatotic liver disease in type 2 diabetes patients using the fibrosis-4 score in medina-retrospective study
- Adipose Tissue Pericellular Fibrosis, Weight Loss and Features of Metabolic Dysfunction-Associated Steatotic Liver Disease after Bariatric Surgery
BibTeX
@article{pugliese2026diagnostic,
title = {{Diagnostic innovation and models of care to improve fibrosis detection and risk stratification in steatotic liver disease}},
author = {Nicola Pugliese and Trenton White and Paul Brennan and Silvana Pannain and Hannes Hagström and Maurice Michel and Lisa Rice-Duek and Giovanni Targher and Cyrielle Caussy and John Dillon and Frank Tacke and Christopher Kopka and Giada Sebastiani and Jerome Boursier and Emmanuel Tsochatzis and Willem Pieter Brouwer and Giovanni Guaraldi and Roberto Vettor and Maja Thiele and Michael Roden and Norbert Stefan and Helen Jarvis and Pere Gines and Jörn Schattenberg and Elisa Pose and Stefan Buttigieg and Christopher Byrne and Jeffrey Lazarus},
journal = {The Lancet Regional Health - Europe},
year = {2026},
month = oct,
doi = {10.1016/j.lanepe.2026.101722},
url = {https://hal.science/hal-05840334v1},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Diagnostic innovation and models of care to improve fibrosis detection and risk stratification in steatotic liver disease
AU - Nicola Pugliese
AU - Trenton White
AU - Paul Brennan
AU - Silvana Pannain
AU - Hannes Hagström
AU - Maurice Michel
AU - Lisa Rice-Duek
AU - Giovanni Targher
AU - Cyrielle Caussy
AU - John Dillon
AU - Frank Tacke
AU - Christopher Kopka
AU - Giada Sebastiani
AU - Jerome Boursier
AU - Emmanuel Tsochatzis
AU - Willem Pieter Brouwer
AU - Giovanni Guaraldi
AU - Roberto Vettor
AU - Maja Thiele
AU - Michael Roden
AU - Norbert Stefan
AU - Helen Jarvis
AU - Pere Gines
AU - Jörn Schattenberg
AU - Elisa Pose
AU - Stefan Buttigieg
AU - Christopher Byrne
AU - Jeffrey Lazarus
PY - 2026
DA - 2026/10/27
JO - The Lancet Regional Health - Europe
DO - 10.1016/j.lanepe.2026.101722
UR - https://hal.science/hal-05840334v1
AB - 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.
SN - 2666-7762
ER -