MAST versus FAST for active fibrotic MASH: a meta-analysis supporting risk-stratified diagnostic pathways
Year: 2026
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: Objective This meta-analysis aimed to compare the diagnostic accuracy of two new scores—FibroScan-AST (FAST) and MRI-AST (MAST)—for identifying metabolic dysfunction-associated steatohepatitis (MASH) with significant fibrosis. Methods A systematic review and meta-analysis were conducted following PRISMA guidelines, with the protocol registered in PROSPERO. Four studies that compared FAST and MAST with liver biopsies were included. The combined sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated using a bivariate random-effects model. Heterogeneity and threshold effects were assessed using subgroup and sensitivity analyses, respectively. Results The FAST score showed moderate sensitivity (44.7, 95% CI: 28.3–62.4%) and quite high specificity (87.5%, 76.8–93.7%), with an AUC of 0.83 (0.75–0.89). MAST showed better sensitivity (55.9%, 41.5–69.3%) and specificity (88.1%, 85.2–90.6%), with an AUC of 0.84 (0.81–0.88). The difference in the AUC was not statistically significant ( p = 0.964). Compared to FAST, MAST showed a relatively higher positive likelihood ratio (4.71 vs. 3.54) and DOR (9.42 vs. 5.68), although these differences were not statistically significant. FAST showed significant threshold variability ( p = 0.005), whereas MAST results were more consistent. Conclusion Although MAST and FAST differ in sensitivity and stability, their overall diagnostic accuracy does not differ statistically. The core limitation of this study is that only four studies were included, which restricts the reliability of the pooled estimates. Therefore, the findings should be interpreted with caution. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/view/CRD420251109029 .
Source: Frontiers in Medicine
Authors: Shengfang Liu, Qingjuan Zhang, Lijing Wang, Qin Tang, Bingtao Hu
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7154944808