Editorial Note: Metabolic-associated steatohepatitis (MASH) is a subtype of metabolic-associated fatty liver disease (MASLD), characterized by hepatic steatosis, lobular inflammation, and hepatocellular ballooning, with a high risk of progressing to liver fibrosis. One of the biggest challenges in MASH drug clinical trials is the high failure rate of participant screening, which can reach as high as 70%–80%. This is primarily because a significant portion of candidates do not meet the key inclusion criterion of the trial—MASH-related fibrosis—as determined by baseline liver biopsy.Recently, a collaborative study conducted by researchers from France, Belgium, and China evaluated and compared eight different non-invasive screening tests (NITs) to develop an optimized screening strategy for assessing MASH-related fibrosis. The findings were published online in JHEP Reports.
Study Methods
The study included 1,005 MASLD patients with biopsy-confirmed diagnoses from five tertiary medical centers. Researchers conducted a comprehensive evaluation and comparison of eight different NITs, including those specifically designed for MASH-related fibrosis as well as tests recommended for assessing advanced fibrosis.
Inclusion & Exclusion Criteria
- All patients underwent liver biopsy to rule out other causes of hepatic steatosis, such as excessive alcohol consumption or chronic viral hepatitis.
- Patients were excluded if their biopsy specimen was less than 10 mm in length or if they had significant liver-related complications.
NITs Analyzed
The study examined five serum-based tests and three tests based on vibration-controlled transient elastography (VCTE):
- Serum-based tests: Included both simple clinical indices (e.g., FNI and FIB-4) and more complex specific markers (e.g., MACK-3, ELF, and FibroTest).
- VCTE-based tests: Included FibroScan, FAST, and Agile3+.
Data Analysis
- The accuracy of each test in diagnosing MASH-related fibrosis and advanced fibrosis was evaluated using area under the receiver operating characteristic curve (AUROC).
- Diagnostic thresholds were adjusted to achieve 90% sensitivity and 90% specificity, followed by internal validation using 1,000 bootstrap samples.
Key Findings
1. Comparison of Individual NITs
- Among simple serum-based tests, FNI had a significantly higher AUROC than FIB-4 for detecting MASH-related fibrosis (0.709 vs. 0.662, P = 0.019).
- Among VCTE-based tests, FAST showed superior AUROC compared to FibroScan (0.774 vs. 0.728, P = 0.013) and Agile3+ (0.774 vs. 0.708, P = 0.004).
- Among complex serum-based tests, MACK-3 outperformed FibroTest (0.772 vs. 0.615, P < 0.001) and ELF (0.772 vs. 0.700, P = 0.028) in diagnosing MASH-related fibrosis.
2. Optimized NIT Combinations for More Accurate Screening
To further enhance diagnostic accuracy, the researchers proposed two optimized NIT combinations:
- FAST/Agile3+ combination Step 1: Initial screening with FAST Step 2: Confirmation with Agile3+ for borderline cases
- MACK-3/ELF combination Step 1: Initial screening with MACK-3 Step 2: Confirmation with ELF
These sequential screening approaches allowed for more accurate identification of high-risk MASH-related fibrosis patients. Notably, they effectively categorized about one-third of the patients as high-risk while maintaining a false positive rate of only 30%, significantly lower than the current screening failure rate in clinical trials.
Expert Commentary
Professor Jérôme Boursier from Angers University Hospital, France, and corresponding author of the study, stated:
“This study not only confirms the diagnostic superiority of specialized NITs for MASH-related fibrosis but also introduces two highly effective screening combinations. These strategies can significantly improve the selection of appropriate clinical trial participants, reducing screening failure rates and accelerating drug development.”
This study provides critical insights for designing MASH clinical trials, reinforcing the role of NITs in diagnosing and monitoring the disease. With continued advancements in technology, NITs will play an increasingly important role in MASH diagnosis and treatment, facilitating more efficient and targeted clinical research.
