How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers?
Background and Aims Asthma is a heterogeneous respiratory disease that encompasses different inflammatory and functional endophenotypes. Many non-invasive biomarkers has been investigated to its pathobiology. Heany et al proposed a clinical algorithm that classifies severe asthmatic patients into li...
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| Format: | Article |
| Status: | Published version |
| Publication date: | 2022 |
| Country: | España |
| Institution: | Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau) |
| Repository: | r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau |
| OAI Identifier: | oai:iibsantpau.fundanetsuite.com:p12275 |
| Online Access: | https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=12275 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391921 |
| Access Level: | Open access |
| Keyword: | asthma biomarkers eosinophils exhaled nitric oxide non-eosinophilic phenotypes sputum |
| _version_ | 1878739867632926720 |
|---|---|
| author | Betancor, D |
| author2 | Olaguibel, JM Rodrigo-Munoz, JM Arismendi, E Barranco, P Barroso, B Bobolea, I Cardaba, B Cruz, MJ Curto, E Del Pozo, V Gonzalez-Barcala, FJ Martinez-Rivera, C Mullol, J Munoz, X Picado, C Plaza, V Quirce, S Rial, MJ Soto, L Valero, A Valverde-Monge, M Sastre, J |
| author2_role | author author author author author author author author author author author author author author author author author author author author author author |
| author_browse | Arismendi, E Barranco, P Barroso, B Betancor, D Bobolea, I Cardaba, B Cruz, MJ Curto, E Del Pozo, V Gonzalez-Barcala, FJ Martinez-Rivera, C Mullol, J Munoz, X Olaguibel, JM Picado, C Plaza, V Quirce, S Rial, MJ Rodrigo-Munoz, JM Sastre, J Soto, L Valero, A Valverde-Monge, M |
| author_facet | Betancor, D Olaguibel, JM Rodrigo-Munoz, JM Arismendi, E Barranco, P Barroso, B Bobolea, I Cardaba, B Cruz, MJ Curto, E Del Pozo, V Gonzalez-Barcala, FJ Martinez-Rivera, C Mullol, J Munoz, X Picado, C Plaza, V Quirce, S Rial, MJ Soto, L Valero, A Valverde-Monge, M Sastre, J |
| author_role | author |
| collection | r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau |
| description | Background and Aims Asthma is a heterogeneous respiratory disease that encompasses different inflammatory and functional endophenotypes. Many non-invasive biomarkers has been investigated to its pathobiology. Heany et al proposed a clinical algorithm that classifies severe asthmatic patients into likely-eosinophilic phenotypes, based on accessible biomarkers: PBE, current treatment, FeNO, presence of nasal polyps (NP) and age of onset. Materials and Methods We assessed the concordance between the algorithm proposed by Heany et al. with sputum examination, the gold standard, in 145 asthmatic patients of the MEGA cohort with varying grades of severity. Results No correlation was found between both classifications 0.025 (CI = 0.013-0.037). Moreover, no relationship was found between sputum eosinophilia and peripheral blood eosinophilia count in the total studied population. Discussion and Conclusion In conclusion, our results suggest that grouping the biomarkers proposed by Heany et al. are insufficient to diagnose eosinophilic phenotypes in asthmatic patients. Sputum analysis remains the gold standard to assess airway inflammation. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | ES_c976ef93aa40e6fbc012b2d1fafbb577 |
| institution | Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau) |
| instname_str | Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau) |
| network_acronym_str | ES |
| network_name_str | España |
| oai_identifier_str | oai:iibsantpau.fundanetsuite.com:p12275 |
| publishDate | 2022 |
| publishDateSort | 2022 |
| publisher | WILEY |
| publisherStr | WILEY |
| reponame_str | r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau |
| spelling | How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers? Betancor, D Olaguibel, JM Rodrigo-Munoz, JM Arismendi, E Barranco, P Barroso, B Bobolea, I Cardaba, B Cruz, MJ Curto, E Del Pozo, V Gonzalez-Barcala, FJ Martinez-Rivera, C Mullol, J Munoz, X Picado, C Plaza, V Quirce, S Rial, MJ Soto, L Valero, A Valverde-Monge, M Sastre, J asthma biomarkers eosinophils exhaled nitric oxide non-eosinophilic phenotypes sputum Background and Aims Asthma is a heterogeneous respiratory disease that encompasses different inflammatory and functional endophenotypes. Many non-invasive biomarkers has been investigated to its pathobiology. Heany et al proposed a clinical algorithm that classifies severe asthmatic patients into likely-eosinophilic phenotypes, based on accessible biomarkers: PBE, current treatment, FeNO, presence of nasal polyps (NP) and age of onset. Materials and Methods We assessed the concordance between the algorithm proposed by Heany et al. with sputum examination, the gold standard, in 145 asthmatic patients of the MEGA cohort with varying grades of severity. Results No correlation was found between both classifications 0.025 (CI = 0.013-0.037). Moreover, no relationship was found between sputum eosinophilia and peripheral blood eosinophilia count in the total studied population. Discussion and Conclusion In conclusion, our results suggest that grouping the biomarkers proposed by Heany et al. are insufficient to diagnose eosinophilic phenotypes in asthmatic patients. Sputum analysis remains the gold standard to assess airway inflammation. WILEY https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=12275 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391921 |
| spellingShingle | How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers? Betancor, D asthma biomarkers eosinophils exhaled nitric oxide non-eosinophilic phenotypes sputum |
| status_str | publishedVersion |
| title | How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers? |
| title_full | How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers? |
| title_fullStr | How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers? |
| title_full_unstemmed | How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers? |
| title_short | How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers? |
| title_sort | How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers? |
| topic | asthma biomarkers eosinophils exhaled nitric oxide non-eosinophilic phenotypes sputum |
| topic_facet | asthma biomarkers eosinophils exhaled nitric oxide non-eosinophilic phenotypes sputum |
| url | https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=12275 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391921 |