Evidence mapPaperPMID 41257923Full record

ArticleBiomarker research2025

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

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 and 13 more

Abstract readLetter
In one paragraph

Article in Biomarker research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

23 authors.

Stephania C IsazaMetabolic Syndrome and Vascular Risk Laboratory, Hospital Universitario Santa Cristina, Instituto de Investigación Sanitaria del Hospital Universitario de La Princesa, Madrid, Spain.
Carlos Ernesto Fernández-GarcíaMetabolic Syndrome and Vascular Risk Laboratory, Hospital Universitario Santa Cristina, Instituto de Investigación Sanitaria del Hospital Universitario de La Princesa, Madrid, Spain. cernesto.fernandez.garcia@gmail.com.ORCID http://orcid.org/0000-0001-6180-879X
Diego RojoLiver Unit, Vall d'Hebron University Hospital, Barcelona, Spain.
Paula IruzubietaGastroenterology and Hepatology Department, Marqués de Valdecilla University Hospital, Santander, Spain.
Javier AmpueroSeLiver Group, Instituto de Biomedicina de Sevilla/CSIC/Hospital Virgen del Rocío, Sevilla, Spain.
Rocío AllerServicio A Digestivo Hospital Clínico Universitario Valladolid, Universidad de Valladolid, Biocritic, Valladolid, Spain.
Raquel Vinuesa CampoFundación Burgos por la Investigación de la Salud, Burgos, Spain.
Laura Izquierdo-SánchezCentro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain.
Esther Fuertes-YebraMetabolic Syndrome and Vascular Risk Laboratory, Hospital Universitario Santa Cristina, Instituto de Investigación Sanitaria del Hospital Universitario de La Princesa, Madrid, Spain.
Patricia MarañónMetabolic Syndrome and Vascular Risk Laboratory, Hospital Universitario Santa Cristina, Instituto de Investigación Sanitaria del Hospital Universitario de La Princesa, Madrid, Spain.
Jesús M BanalesCentro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain.
Laura PagésLiver Unit, Vall d'Hebron University Hospital, Barcelona, Spain.
Carolina Jiménez-GonzálezGastroenterology and Hepatology Department, Marqués de Valdecilla University Hospital, Santander, Spain.
Javier Rodríguez de CíaMetabolic Syndrome and Vascular Risk Laboratory, Hospital Universitario Santa Cristina, Instituto de Investigación Sanitaria del Hospital Universitario de La Princesa, Madrid, Spain.
Irene OlaizolaDepartment of Liver and Gastrointestinal Diseases, Biogipuzkoa Health Research Institute - Donostia University Hospital -, University of the Basque Country (UPV/EHU), Donostia-San Sebastian, Spain.
Judith Gómez-CamareroServicio de Aparato Digestivo, Hospital Universitario de Burgos, Burgos, Spain.
Víctor Arroyo-LopezServicio A Digestivo Hospital Clínico Universitario Valladolid, Universidad de Valladolid, Biocritic, Valladolid, Spain.
Manuel Romero-GómezSeLiver Group, Instituto de Biomedicina de Sevilla/CSIC/Hospital Virgen del Rocío, Sevilla, Spain.
Javier CrespoGastroenterology and Hepatology Department, Marqués de Valdecilla University Hospital, Santander, Spain.
Juan M PericàsLiver Unit, Vall d'Hebron University Hospital, Barcelona, Spain.
Carmelo García-MonzónMetabolic Syndrome and Vascular Risk Laboratory, Hospital Universitario Santa Cristina, Instituto de Investigación Sanitaria del Hospital Universitario de La Princesa, Madrid, Spain.
Águeda González-RodríguezInstituto de Investigaciones Biomédicas Sols-Morreale (Consejo Superior de Investigaciones Científicas-Universidad Autónoma de Madrid), Madrid, Spain. aguedagr@iib.uam.es.ORCID http://orcid.org/0000-0003-2851-2318
HEPAmet Registry

Funding

Instituto de Salud Carlos III FI20-00296
6 · The paper itself

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.

Indexed as

Advanced liver fibrosisBFSBMP8AMASHMASLDNon-invasive diagnosisValidation

Identifiers

PMID41257923
PMCPMC12628818

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.