Validation of BMP8A fibrosis score to identify patients with metabolic dysfunction-associated steatohepatitis with advanced liver fibrosis

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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Journal
Biomarker Research
Published
2025-11-19
DOI
https://doi.org/10.1186/s40364-025-00862-3
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Validation of BMP8A fibrosis score to identify patients with metabolic dysfunction-associated steatohepatitis with advanced liver fibrosis

Paula Iruzubieta, Javier Rodríguez de Cía, Laura Pagès, Judith Gómez‐Camarero et al.
Biomarker Research
Liver Disease Diagnosis and Treatment
article

Validation of BMP8A fibrosis score to identify patients with metabolic dysfunction-associated steatohepatitis with advanced liver fibrosis

Paula Iruzubieta, Javier Rodríguez de Cía, Laura Pagès, Judith Gómez‐Camarero, Javier Crespo, Laura Izquierdo-Sánchez, Manuel Romero‐Gómez, Javier Ampuero, Carolina Jiménez-González, Juan M. Pericàs, Águeda González‐Rodríguez, Raquel Vinuesa Campo, Patricia Marañón, Carmelo García‐Monzón, Stephania C. Isaza, Carlos Ernesto Fernández-García, Jesús M. Bañales, Irene Olaizola, Victor Arroyo-López, Esther Fuertes-Yebra, R. Aller, Diego Rojo
article en

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.

Biomarker ResearchVol. 13(1)
Ikerbasque (ES), Universitat Autònoma de Barcelona (ES), Instituto de Investigaciones Biomédicas Sols-Morreale (ES), Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas (ES), Marqués de Valdecilla University Hospital (ES), Biogipuzkoa Health Research Institute (ES), Vall d'Hebron Institut de Recerca (ES), Hospital Universitario Santa Cristina (ES), Instituto de Investigación Marqués de Valdecilla (ES), Centro de Investigación Biomédica en Red (ES), Hospital Universitario de Burgos (ES), Vall d'Hebron Hospital Universitari (ES), Hospital Universitario de La Princesa (ES), Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (ES), Instituto de Biomedicina de Sevilla (ES), Hospital Universitario Virgen del Rocío (ES), Hospital Clínico Universitario de Valladolid (ES), Universidad de Burgos (ES), Universidad Autónoma de Madrid (ES), Universidad de Navarra (ES)
Pfizer, Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Consejo Superior de Investigaciones Científicas, Instituto de Salud Carlos III
Openalex Percentile: Top 54%
Liver Disease Diagnosis and Treatment
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