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.