One-step non-invasive diagnosis of metabolic dysfunction-associated steatohepatitis and fibrosis in high-risk population
Ver/ Abrir
Identificadores
URI: https://hdl.handle.net/10902/34513DOI: 10.1002/ueg2.12589
ISSN: 2050-6406
ISSN: 2050-6414
Registro completo
Mostrar el registro completo DCAutoría
Iruzubieta Coz, Paula; Mayo, Rebeca; Mincholé, Itziar; Martínez-Arranz, Ibon; Arias Loste, María Teresa

Fecha
2024Derechos
© 2024 The Author(s). United European Gastroenterology Journal published by Wiley Periodicals LLC on behalf of United European Gastroenterology. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
Publicado en
United European Gastroenterology Journal, 2024,12, 919-929
Editorial
Wiley-Blackwell
Enlace a la publicación
Palabras clave
At‐risk MASH
Biopsy
Fibroscan
MASEF score
MASLD
Metabolic dysfunction‐associated steatotic liver disease
Metabolic syndrome
Non‐invasive tests
OWLiver panel
Type 2 diabetes mellitus
Resumen/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.
Colecciones a las que pertenece
- D22 Artículos [1093]
- IDIVAL Artículos [864]
