Development and validation of a scoring system to predict MASLD patients with significant hepatic fibrosis
Abstract To address the need for a simple model to predict ≥ F2 fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD) patients, a study utilized data from 791 biopsy-proven MASLD patients from the NASH Clinical Research Network and Jinan University First Affiliated Hospital. T...
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-91013-z |
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| Summary: | Abstract To address the need for a simple model to predict ≥ F2 fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD) patients, a study utilized data from 791 biopsy-proven MASLD patients from the NASH Clinical Research Network and Jinan University First Affiliated Hospital. The data were divided into training and internal testing sets through randomized stratified sampling. A multivariable logistic regression model using key categorical variables was developed to identify ≥ F2 fibrosis. External validation was performed using data from the FLINT trial and multiple centers in China. The DA-GAG score, incorporating diabetes, age, GGT, aspartate aminotransferase/ platelet ratio, and globulin/ total protein ratio, demonstrated superior performance in distinguishing ≥ F2 fibrosis with an area under the receiver operating characteristic curve of 0.79 in training and over 0.80 in testing datasets. The DA-GAG score efficiently identifies MASLD patients with ≥ F2 fibrosis, significantly reducing the medical burden. |
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| ISSN: | 2045-2322 |