Background & aims: Current screening pathways, developed from tertiary care cohorts, underestimate the presence of Metabolic-dysfunction associated steatotic liver disease (MASLD) in patients with type 2 diabetes mellitus (T2DM) in the community. We developed, validated, and assessed cost-effectiveness of a new score for screening the presence of fibrosis due to MASLD in primary care.
Methods: Consecutive T2DM patients underwent screening for liver diseases with transient elastography (TE). Based on predictors of significant/advanced fibrosis, we generated the BIMAST score (based on aspartate aminotransferase (AST) and body mass index (BMI)) and validated it internally and externally (Royal Free Hospital, London and Palermo Hospital). For cost-effectiveness analysis, 6 screening strategies were compared against standard of care: BIMAST score, ultrasound plus abnormal liver function tests, FIB-4, NAFLD fibrosis score, ELF and transient elastography (TE). A Markov model was built based on fibrosis status. Cost per quality-adjusted life year (QALY) gained and the incremental cost-effectiveness ratio (ICER) were estimated over a lifetime.
Results: Among 300 patients enrolled, 64% (186) had MASLD and 10% (28) other causes of liver disease. In the whole population, patients with significant fibrosis, advanced fibrosis, and cirrhosis due to MASLD were 17% (50/287), 11% (31/287), and 3% (8/287), respectively. In primary care, BIMAST performed better than other non-invasive markers at predicting significant and advanced fibrosis. Moreover, BIMAST reduced false negatives from 54% (ELF) and 38% (FIB-4) to 10%. In both validation cohorts, BIMAST performance was as good as FIB-4. In the cost-utility analysis, ICER was £2,337.92/QALY for BIMAST.
Conclusion: The BIMAST predicts the presence of significant fibrosis in the community, reduces false negatives and is cost-effective. The BIMAST score should be included in the holistic assessment of diabetic patients.
Copyright: © 2024 Forlano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.