Validation of BMP8A fibrosis score to identify patients with metabolic dysfunction-associated steatohepatitis with advanced liver fibrosis
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Isaza, Stephania C.; Fernández García, Carlos Ernesto; Rojo, Diego; Iruzubieta Coz, Paula; Ampuero, Javier; Aller, Rocío; Campo, Raquel Vinuesa; Izquierdo Sánchez, Laura; Fuertes Yebra, Esther; Marañón, Patricia; Banales, Jesús M.; Pagés, Laura; Jimenez González, Carolina; Cía, Javier Rodríguez de; Olaizola, Irene; Gómez Camarero, Judith; Arroyo Lopez, Víctor; Romero Gómez, Manuel; Crespo García, Javier
; [et al.]Fecha
2025Derechos
© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License
Publicado en
Biomarker research, 2025, 13(1), 149
Editorial
BioMed Central
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Palabras clave
Advanced liver fibrosis
MASLD
MASH
BMP8A
BFS
Non-invasive diagnosis
Validation
Resumen/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.
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