Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/14334 |
Resumo: | Background Refined phenotyping of allergic diseases may unravel novel phenotypes. Conjunctivitis as an independent disorder has never been approached. Aim To identify distinct classes of allergic respiratory diseases using latent class analysis (LCA) and distinguish each class using classification and regression tree (CART) analysis. Methods Seven hundred and twenty‐eight adults from the Portuguese general population study ICAR had a structured medical interview combined with blood collection, skin prick tests, spirometry with bronchodilation, and exhaled nitric oxide. LCA was applied to 19 variables. The CART algorithm selected the most likely variables distinguishing LCA‐classes. Results A six‐class model was obtained. Class 1 (25%): nonallergic participants without bronchial or ocular symptoms. Classes 2 (22%) and 3 (11%): nasal and ocular (low levels) symptoms without nasal impairment, monosensitized (Class 2) or polysensitized (Class 3). Class 4 (13%): polysensitized participants with high levels of nasal and ocular symptoms, and nasal impairment. Classes 5 (16%) and 6 (14%): high level of nasal, bronchial and ocular symptoms with nasal impairment (non‐allergic or polysensitized, respectively). Participants in classes 5 and 6 had more bronchial exacerbations and unscheduled medical visits (P < 0.001). Ocular symptoms were significantly higher in classes with nasal impairment, compared to those without impairment (P < 0.001) or no nasal symptom (P < 0.001). CART highlighted ocular symptoms as the most relevant variable in distinguishing LCA‐classes. Conclusion Novel severe phenotypes of participants with co‐occurrence of ocular, nasal and bronchial symptoms, and exacerbation‐prone were identified. The tree algorithm showed the importance of the ocular symptoms in the expression of allergic diseases phenotypes. |
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Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypesAirways symptomsAllergic sensitizationCluster analysisOcular symptomsBackground Refined phenotyping of allergic diseases may unravel novel phenotypes. Conjunctivitis as an independent disorder has never been approached. Aim To identify distinct classes of allergic respiratory diseases using latent class analysis (LCA) and distinguish each class using classification and regression tree (CART) analysis. Methods Seven hundred and twenty‐eight adults from the Portuguese general population study ICAR had a structured medical interview combined with blood collection, skin prick tests, spirometry with bronchodilation, and exhaled nitric oxide. LCA was applied to 19 variables. The CART algorithm selected the most likely variables distinguishing LCA‐classes. Results A six‐class model was obtained. Class 1 (25%): nonallergic participants without bronchial or ocular symptoms. Classes 2 (22%) and 3 (11%): nasal and ocular (low levels) symptoms without nasal impairment, monosensitized (Class 2) or polysensitized (Class 3). Class 4 (13%): polysensitized participants with high levels of nasal and ocular symptoms, and nasal impairment. Classes 5 (16%) and 6 (14%): high level of nasal, bronchial and ocular symptoms with nasal impairment (non‐allergic or polysensitized, respectively). Participants in classes 5 and 6 had more bronchial exacerbations and unscheduled medical visits (P < 0.001). Ocular symptoms were significantly higher in classes with nasal impairment, compared to those without impairment (P < 0.001) or no nasal symptom (P < 0.001). CART highlighted ocular symptoms as the most relevant variable in distinguishing LCA‐classes. Conclusion Novel severe phenotypes of participants with co‐occurrence of ocular, nasal and bronchial symptoms, and exacerbation‐prone were identified. The tree algorithm showed the importance of the ocular symptoms in the expression of allergic diseases phenotypes.WileyRepositório Científico do Instituto Politécnico do PortoAmaral, RitaBousquet, JeanPereira, Ana M.Araújo, Luís M.Sá‐Sousa, AnaJacinto, TiagoAlmeida, RuteDelgado, LuísFonseca, João A.2020-05-02T00:30:30Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/14334engAmaral, R., Bousquet, J., Pereira, A. M., Araújo, L. M., Sá-Sousa, A., Jacinto, T., Almeida, R., Delgado, L., & Fonseca, J. A. (2019). Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes. Allergy, 74(4), 698–708. https://doi.org/10.1111/all.1367010.1111/all.13670info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-17T01:47:04Zoai:recipp.ipp.pt:10400.22/14334Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:34:11.280340Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes |
title |
Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes |
spellingShingle |
Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes Amaral, Rita Airways symptoms Allergic sensitization Cluster analysis Ocular symptoms |
title_short |
Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes |
title_full |
Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes |
title_fullStr |
Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes |
title_full_unstemmed |
Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes |
title_sort |
Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes |
author |
Amaral, Rita |
author_facet |
Amaral, Rita Bousquet, Jean Pereira, Ana M. Araújo, Luís M. Sá‐Sousa, Ana Jacinto, Tiago Almeida, Rute Delgado, Luís Fonseca, João A. |
author_role |
author |
author2 |
Bousquet, Jean Pereira, Ana M. Araújo, Luís M. Sá‐Sousa, Ana Jacinto, Tiago Almeida, Rute Delgado, Luís Fonseca, João A. |
author2_role |
author author author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Amaral, Rita Bousquet, Jean Pereira, Ana M. Araújo, Luís M. Sá‐Sousa, Ana Jacinto, Tiago Almeida, Rute Delgado, Luís Fonseca, João A. |
dc.subject.por.fl_str_mv |
Airways symptoms Allergic sensitization Cluster analysis Ocular symptoms |
topic |
Airways symptoms Allergic sensitization Cluster analysis Ocular symptoms |
description |
Background Refined phenotyping of allergic diseases may unravel novel phenotypes. Conjunctivitis as an independent disorder has never been approached. Aim To identify distinct classes of allergic respiratory diseases using latent class analysis (LCA) and distinguish each class using classification and regression tree (CART) analysis. Methods Seven hundred and twenty‐eight adults from the Portuguese general population study ICAR had a structured medical interview combined with blood collection, skin prick tests, spirometry with bronchodilation, and exhaled nitric oxide. LCA was applied to 19 variables. The CART algorithm selected the most likely variables distinguishing LCA‐classes. Results A six‐class model was obtained. Class 1 (25%): nonallergic participants without bronchial or ocular symptoms. Classes 2 (22%) and 3 (11%): nasal and ocular (low levels) symptoms without nasal impairment, monosensitized (Class 2) or polysensitized (Class 3). Class 4 (13%): polysensitized participants with high levels of nasal and ocular symptoms, and nasal impairment. Classes 5 (16%) and 6 (14%): high level of nasal, bronchial and ocular symptoms with nasal impairment (non‐allergic or polysensitized, respectively). Participants in classes 5 and 6 had more bronchial exacerbations and unscheduled medical visits (P < 0.001). Ocular symptoms were significantly higher in classes with nasal impairment, compared to those without impairment (P < 0.001) or no nasal symptom (P < 0.001). CART highlighted ocular symptoms as the most relevant variable in distinguishing LCA‐classes. Conclusion Novel severe phenotypes of participants with co‐occurrence of ocular, nasal and bronchial symptoms, and exacerbation‐prone were identified. The tree algorithm showed the importance of the ocular symptoms in the expression of allergic diseases phenotypes. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 2018-01-01T00:00:00Z 2020-05-02T00:30:30Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/14334 |
url |
http://hdl.handle.net/10400.22/14334 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Amaral, R., Bousquet, J., Pereira, A. M., Araújo, L. M., Sá-Sousa, A., Jacinto, T., Almeida, R., Delgado, L., & Fonseca, J. A. (2019). Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes. Allergy, 74(4), 698–708. https://doi.org/10.1111/all.13670 10.1111/all.13670 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Wiley |
publisher.none.fl_str_mv |
Wiley |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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