One-step non-invasive diagnosis of metabolic dysfunction-associated steatohepatitis and fibrosis in high-risk population

Abstract

Background and aim: Type 2 Diabetes mellitus (T2DM), age, and obesity are risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to assess the performance of non-invasive tests (NITs) for the diagnosis of metabolic dysfunction-associated steatohepatitis (MASH) and fibrosis in high-risk subjects.

Methods: Multicentre cross-sectional study that included 124 biopsy-proven MASLD in more than 50 years-old patients with overweight/obesity and T2DM. Vibration-controlled transient elastography, Fibrosis-4 index (FIB-4), Non-alcoholic fatty liver disease fibrosis score (NFS), OWLiver Panel (OWLiver DM2 + Metabolomics-Advanced Steatohepatitis Fibrosis Score -MASEF) and FibroScan-AST were performed. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operating characteristic curve (AUC) were calculated. NITs were assessed individually and in sequential/parallel combinations.

Results: 35 (28.2%) patients had early MASH and 66 (53.2%) had MASH with significant fibrosis (at-risk MASH). The OWLiver Panel correctly classified 86.1% as MASH, showing an accuracy, sensitivity, specificity, PPV, and NPV of 0.77, 0.86, 0.35, 0.85, and 0.36, respectively. Class III obesity, diabetes control, or gender did not impact on the performance of the OWLiver Panel (p > 0.1). NITs for at-risk MASH showed an AUC > 0.70 except for NFS. MASEF showed the highest accuracy and NPV for at-risk MASH (AUC 0.77 [0.68-0.85], NPV 72%) and advanced fibrosis (AUC 0.80 [0.71-0.88], NPV 92%). Combinations of NITs for the identification of at-risk MASH did not provide any additional benefit over using MASEF alone.

Conclusion: One-step screening strategy with the OWLiver Panel has high accuracy to detect MASH and at-risk MASH in high-risk subjects for MASLD.

Keywords: MASEF score; MASLD; OWLiver panel; at‐risk MASH; biopsy; fibroscan; metabolic dysfunction‐associated steatotic liver disease; metabolic syndrome; non‐invasive tests; type 2 diabetes mellitus.

FIGURE 1

OWLiver Panel for the diagnosis and characterization of metabolic dysfunction‐associated steatotic liver disease in high‐risk subjects. Results of the OWLiver Panel among patients with isolated steatosis, early MASH and at‐risk MASH at liver biopsy.

FIGURE 2

Diagnostic accuracy for MASH using the OWLiver Panel according to the presence of class III obesity, diabetes mellitus control, gender and iSGLT2/aGLP1 treatment. Error bars represent 95% CIs. The gray area corresponds to the 95% CI of the total cohort. CI, confidence interval; GDC, good diabetes control; NPV, negative predictive value; PPV, positive predictive value.

FIGURE 3

Comparison of AUCs obtained in the study population. Comparisons between MASEF and other NITs for the diagnosis of (a) significant and (b) advanced fibrosis in high‐risk patients. AUC, area under the receiver operating characteristic curve; FAST, FibroScan‐aspartate aminotransferase; FIB‐4, Fibrosis‐4 index; MASEF, Metabolomics‐Advanced Steatohepatitis Fibrosis Score; NFS, NAFLD Fibrosis Score; NITs, non‐invasive tests; VCTE, vibration‐controlled transient elastography.

FIGURE 4

Diagnostic accuracy for significant fibrosis using different combinations of NITs in study population. Error bars represent 95% CIs. The gray area corresponds to the 95% CI of MASEF alone. CI, confidence interval; FAST, FibroScan‐aspartate aminotransferase; FIB‐4, Fibrosis‐4 index; MASEF, Metabolomics‐Advanced Steatohepatitis Fibrosis Score; NFS, NAFLD Fibrosis Score; NITs, non‐invasive tests; NPV, negative predictive value; PPV, positive predictive value; VCTE, vibration‐controlled transient elastography.