Validation of BMP8A fibrosis score to identify patients with metabolic dysfunction-associated steatohepatitis with advanced liver fibrosis
Year: 2025
Type: article
Study design: Observational Study
Abstract: Liver fibrosis represents the main risk factor not only for liver-related but also for overall mortality in metabolic dysfunction-associated steatotic liver disease (MASLD) patients, being metabolic dysfunction-associated steatohepatitis (MASH) its more severe clinical form. We recently developed a non-invasive algorithm termed BMP8A Fibrosis Score (BFS) which is able to identify MASH patients with advanced liver fibrosis. The aim of this study was to validate the BFS comparing its diagnostic accuracy with that of other scoring systems developed to assess liver fibrosis in MASH patients. Serum BMP8A was measured in 302 patients with biopsy-proven MASH: 171 with non- or mild fibrosis (F0-F2) and 131 with advanced fibrosis (F3-F4) recruited from seven university hospitals located in different cities in Spain. BFS, Fibrosis-4 (FIB-4) Index, NAFLD Fibrosis Score (NFS), Hepamet Fibrosis Score (HFS), and AST-to-Platelet Ratio Index (APRI) were calculated for each patient. The diagnostic accuracy of the scoring systems was determined according to the area under the receiver operating characteristic (AUROC) curve, sensitivity, specificity, positive (PPV) and negative (NPV) predictive values, and likelihood ratios (LR). BFS showed higher overall accuracy than the other liver fibrosis algorithms calculated in the study cohort, presenting an AUROC of 0.750 for predicting advanced liver fibrosis (F3-F4), and correctly classifying 70.9% of F3-F4 patients with a sensitivity of 58.0%, a specificity of 80.7%, a 71.5% NPV, a 69.7% PPV, a 3.0 LR+, and a 0.5 LR-; the other predictive scores correctly classified a lower percentage of these patients (63.6% for FIB-4 ≥ 2.67, 63.2% for HFS ≥ 0.47, 57.3% for APRI ≥ 1.5 and 56.9% for NFS ≥ 0.675). BFS eliminates the grey area as it uses a single cut-off value (0.46), which is its key advantage over the others, reducing the number of patients with undetermined results (43.4% for FIB-4, 39.1% APRI, 37.4% for HFS, and 24.1% NFS). In sum, BFS properly classified more patients with advanced liver fibrosis (F3-F4) than the other scoring systems, eliminating indeterminate results and improving risk stratification.
Source: Biomarker Research
Authors: Stephania C. Isaza, Carlos Ernesto Fernández-García, Diego Rojo, Paula Iruzubieta, Javier Ampuero, Rocío Aller, Raquel Vinuesa Campo, Laura Izquierdo-Sánchez, Esther Fuertes-Yebra, Patricia Marañón, Jesús M. Banales, Laura Pagés, Carolina Jiménez-González, Javier Rodríguez de Cía, Irene Olaizola, Judith Gómez-Camarero, Víctor Arroyo-Lopez, Manuel Romero-Gómez, Javier Crespo, Juan M. Pericàs, Carmelo García-Monzón, Águeda González-Rodríguez, on behalf of HEPAmet Registry
Institutions: Hospital Universitario Santa Cristina, Instituto de Investigación Sanitaria del Hospital Universitario de La Princesa, Universitat Autònoma de Barcelona, Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Marqués de Valdecilla University Hospital, Instituto de Investigación Marqués de Valdecilla, Consejo Superior de Investigaciones Científicas, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío, Universidad de Valladolid, Centro de Investigación Biomédica en Red, Hospital Clínico Universitario de Valladolid, Centro de Investigación Biomédica en Red Enfermedades Infecciosas, University of the Basque Country, Biogipuzkoa Health Research Institute, Ikerbasque, Universidad de Navarra, Hospital Universitario de Burgos, Instituto de Investigaciones Biomédicas Sols-Morreale, Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas, Universidad Autónoma de Madrid
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,890
Award: G4980142959
OpenAlex ID: W4416393330
