Work

Predicting Fibrosis Stage in MASH: The Role of Total Metabolic Syndrome Score and MMP-1

Year: 2025

Type: article

Abstract: Background and Objectives: Fibrosis stage is the key histopathological determinant of liver-related outcomes in metabolic dysfunction-associated steatohepatitis (MASH); however, a reliable noninvasive method for predicting fibrosis stage remains an unmet need. This study aimed to develop an accurate, practical, and noninvasive tool for identifying “at-risk MASH patients”. Materials and Methods: Fifty-six patients with biopsy-confirmed MASH were prospectively enrolled and categorized into fibrosis stages using the NASH-CRN system. In addition to anthropometric and biochemical parameters, seven serum fibrosis biomarkers were evaluated across fibrosis stages. Binary logistic regression analysis was used to construct a scoring model for predicting ≥F2 fibrosis. The diagnostic performance of the proposed model was compared with established noninvasive tests (NITs) and magnetic resonance elastography (MRE) for detecting both ≥F2 and ≥F3 fibrosis. Results: The total metabolic syndrome score was the only variable that significantly distinguished between F1 and F2 stages (p = 0.039). Among the biomarkers, matrix metalloproteinase-1 (MMP-1) showed a significant difference across fibrosis groups (p = 0.009). The AST/ALT ratio was the most robust predictor for differentiating ≥F3 (p < 0.001). A scoring model integrating the total metabolic syndrome score, MMP-1, and AST/ALT ratio demonstrated superior diagnostic accuracy for identifying ≥F2 (AUROC 0.88, 95% CI 0.79–0.97) compared to other NITs and MRE, and strong performance for detecting ≥F3 (AUROC 0.95, 95% CI 0.90–1.00). Conclusions: Total metabolic syndrome score and MMP-1 are promising candidates for future approaches. Combining total metabolic syndrome score, MMP-1, and AST/ALT ratio might detect ≥F2 in MASH with higher diagnostic accuracy than other NITs and MRE.

Source: Medicina

DOI: 10.3390/medicina61061102

Authors: Bahadır Köylü, Cenk Sökmensüer, Muşturay Karçaaltıncaba, Onur Keskin

Institution: Hacettepe University

Language: English

Topic: Liver Disease Diagnosis and Treatment

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,654