Systemic inflammatory biomarkers define specific clusters in patients with bronchiectasis: A large-cohort study

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• dc.contributor.author Wang, Xuejie
• dc.contributor.author Villa, Carmen
• dc.contributor.author Dobarganes, Yadira
• dc.contributor.author Olveira, Casilda
• dc.contributor.author Girón, Rosa
• dc.contributor.author García-Clemente, Marta
• dc.contributor.author Máiz, Luis
• dc.contributor.author Sibila, Oriol
• dc.contributor.author Golpe, Rafael
• dc.contributor.author Menéndez, Rosario
• dc.contributor.author Rodríguez-López, Juan
• dc.contributor.author Prados, Concepción
• dc.contributor.author Martínez-García, Miguel Ángel
• dc.contributor.author Rodriguez, Juan Luis
• dc.contributor.author Rosa, David de la
• dc.contributor.author Duran Jordà, Xavier, 1974-
• dc.contributor.author García Ojalvo, Jordi
• dc.contributor.author Barreiro Portela, Esther
• dc.date.accessioned 2022-03-07T07:34:46Z
• dc.date.available 2022-03-07T07:34:46Z
• dc.date.issued 2022
• dc.description.abstract Differential phenotypic characteristics using data mining approaches were defined in a large cohort of patients from the Spanish Online Bronchiectasis Registry (RIBRON). Three differential phenotypic clusters (hierarchical clustering, scikit-learn library for Python, and agglomerative methods) according to systemic biomarkers: neutrophil, eosinophil, and lymphocyte counts, C reactive protein, and hemoglobin were obtained in a patient large-cohort (n = 1092). Clusters #1-3 were named as mild, moderate, and severe on the basis of disease severity scores. Patients in cluster #3 were significantly more severe (FEV1, age, colonization, extension, dyspnea (FACED), exacerbation (EFACED), and bronchiectasis severity index (BSI) scores) than patients in clusters #1 and #2. Exacerbation and hospitalization numbers, Charlson index, and blood inflammatory markers were significantly greater in cluster #3 than in clusters #1 and #2. Chronic colonization by Pseudomonas aeruginosa and COPD prevalence were higher in cluster # 3 than in cluster #1. Airflow limitation and diffusion capacity were reduced in cluster #3 compared to clusters #1 and #2. Multivariate ordinal logistic regression analysis further confirmed these results. Similar results were obtained after excluding COPD patients. Clustering analysis offers a powerful tool to better characterize patients with bronchiectasis. These results have clinical implications in the management of the complexity and heterogeneity of bronchiectasis patients.
• dc.description.sponsorship This study has been supported by FIS 21/00215 (FEDER, ISC-III) & CIBERES (ISC-III), SEPAR 2020, and ZAMBON-PHARMA (Spain). JGO was supported by the Spanish Ministry of Science and Innovation and FEDER (project PGC 2018-101251-B-I00 and Maria de Maeztu Programme for Units of Excellence in R&D, grant CEX2018-000792-M), and by the Generalitat de Catalunya (ICREA Academia programme).
• dc.format.mimetype application/pdf
• dc.identifier.citation Wang X, Villa C, Dobarganes Y, Olveira C, Girón R, García-Clemente M, Máiz L, Sibila O, Golpe R, Menéndez R, Rodríguez-López J, Prados C, Martinez-García MA, Rodriguez JL, de la Rosa D, Duran X, Garcia-Ojalvo J, Barreiro E. Systemic inflammatory biomarkers define specific clusters in patients with bronchiectasis: A large-cohort study. Biomedicines. 2022 Jan 21;10(2):225. DOI: 10.3390/biomedicines10020225
• dc.identifier.doi http://dx.doi.org/10.3390/biomedicines10020225
• dc.identifier.issn 2227-9059
• dc.identifier.uri http://hdl.handle.net/10230/52634
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Biomedicines. 2022 Jan 21;10(2):225
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PGC2018-101251-B-I00
• dc.rights © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword C reactive protein
• dc.subject.keyword Blood neutrophil
• dc.subject.keyword Clinical outcomes
• dc.subject.keyword Disease severity scores
• dc.subject.keyword Eosinophil
• dc.subject.keyword Hemoglobin
• dc.subject.keyword Hierarchical clustering
• dc.subject.keyword Lymphocyte counts
• dc.subject.keyword Multivariate analyses
• dc.subject.keyword Non-cystic fibrosis bronchiectasis
• dc.subject.keyword Phenotypic clusters
• dc.title Systemic inflammatory biomarkers define specific clusters in patients with bronchiectasis: A large-cohort study
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion