Predicting Fibrosis Stage in MASH: The Role of Total Metabolic Syndrome Score and MMP-1
<i>Background and Objectives</i>: 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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Medicina |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1648-9144/61/6/1102 |
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| Summary: | <i>Background and Objectives</i>: 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”. <i>Materials and Methods</i>: 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. <i>Results</i>: The total metabolic syndrome score was the only variable that significantly distinguished between F1 and F2 stages (<i>p</i> = 0.039). Among the biomarkers, matrix metalloproteinase-1 (MMP-1) showed a significant difference across fibrosis groups (<i>p</i> = 0.009). The AST/ALT ratio was the most robust predictor for differentiating ≥F3 (<i>p</i> < 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). <i>Conclusions</i>: 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. |
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| ISSN: | 1010-660X 1648-9144 |