Cargando…

Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts

BACKGROUND: Bronchiolitis is the leading cause of infants hospitalization in the U.S. and Europe. Additionally, bronchiolitis is a major risk factor for the development of childhood asthma. Growing evidence suggests heterogeneity within bronchiolitis. We sought to identify distinct, reproducible bro...

Descripción completa

Detalles Bibliográficos
Autores principales: Fujiogi, Michimasa, Dumas, Orianne, Hasegawa, Kohei, Jartti, Tuomas, Camargo, Carlos A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8741473/
https://www.ncbi.nlm.nih.gov/pubmed/35028545
http://dx.doi.org/10.1016/j.eclinm.2021.101257
_version_ 1784629498153533440
author Fujiogi, Michimasa
Dumas, Orianne
Hasegawa, Kohei
Jartti, Tuomas
Camargo, Carlos A.
author_facet Fujiogi, Michimasa
Dumas, Orianne
Hasegawa, Kohei
Jartti, Tuomas
Camargo, Carlos A.
author_sort Fujiogi, Michimasa
collection PubMed
description BACKGROUND: Bronchiolitis is the leading cause of infants hospitalization in the U.S. and Europe. Additionally, bronchiolitis is a major risk factor for the development of childhood asthma. Growing evidence suggests heterogeneity within bronchiolitis. We sought to identify distinct, reproducible bronchiolitis subgroups (profiles) and to develop a decision rule accurately predicting the profile at the highest risk for developing asthma. METHODS: In three multicenter prospective cohorts of infants (age < 12 months) hospitalized for bronchiolitis in the U.S. and Finland (combined n = 3081) in 2007–2014, we identified clinically distinct bronchiolitis profiles by using latent class analysis. We examined the association of the profiles with the risk for developing asthma by age 6–7 years. By performing recursive partitioning analyses, we developed a decision rule predicting the profile at highest risk for asthma, and measured its predictive performance in two separate cohorts. FINDINGS: We identified four bronchiolitis profiles (profiles A–D). Profile A (n = 388; 13%) was characterized by a history of breathing problems/eczema and non–respiratory syncytial virus (non-RSV) infection. In contrast, profile B (n = 1064; 34%) resembled classic RSV-induced bronchiolitis. Profile C (n = 993; 32%) was comprised of the most severely ill group. Profile D (n = 636; 21%) was the least-ill group. Profile A infants had a significantly higher risk for asthma, compared to profile B infants (38% vs. 23%, adjusted odds ratio [adjOR] 2⋅57, 95%confidence interval [CI] 1⋅63–4⋅06). The derived 4-predictor (RSV infection, history of breathing problems, history of eczema, and parental history of asthma) decision rule strongly predicted profile A—e.g., area under the curve [AUC] of 0⋅98 (95%CI 0⋅97–0⋅99), sensitivity of 1⋅00 (95%CI 0⋅96–1⋅00), and specificity of 0⋅90 (95%CI 0⋅89–0⋅93) in a validation cohort. INTERPRETATION: In three prospective cohorts of infants with bronchiolitis, we identified clinically distinct profiles and their longitudinal relationship with asthma risk. We also derived and validated an accurate prediction rule to determine the profile at highest risk. The current results should advance research into the development of profile-specific preventive strategies for asthma.
format Online
Article
Text
id pubmed-8741473
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-87414732022-01-12 Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts Fujiogi, Michimasa Dumas, Orianne Hasegawa, Kohei Jartti, Tuomas Camargo, Carlos A. EClinicalMedicine Article BACKGROUND: Bronchiolitis is the leading cause of infants hospitalization in the U.S. and Europe. Additionally, bronchiolitis is a major risk factor for the development of childhood asthma. Growing evidence suggests heterogeneity within bronchiolitis. We sought to identify distinct, reproducible bronchiolitis subgroups (profiles) and to develop a decision rule accurately predicting the profile at the highest risk for developing asthma. METHODS: In three multicenter prospective cohorts of infants (age < 12 months) hospitalized for bronchiolitis in the U.S. and Finland (combined n = 3081) in 2007–2014, we identified clinically distinct bronchiolitis profiles by using latent class analysis. We examined the association of the profiles with the risk for developing asthma by age 6–7 years. By performing recursive partitioning analyses, we developed a decision rule predicting the profile at highest risk for asthma, and measured its predictive performance in two separate cohorts. FINDINGS: We identified four bronchiolitis profiles (profiles A–D). Profile A (n = 388; 13%) was characterized by a history of breathing problems/eczema and non–respiratory syncytial virus (non-RSV) infection. In contrast, profile B (n = 1064; 34%) resembled classic RSV-induced bronchiolitis. Profile C (n = 993; 32%) was comprised of the most severely ill group. Profile D (n = 636; 21%) was the least-ill group. Profile A infants had a significantly higher risk for asthma, compared to profile B infants (38% vs. 23%, adjusted odds ratio [adjOR] 2⋅57, 95%confidence interval [CI] 1⋅63–4⋅06). The derived 4-predictor (RSV infection, history of breathing problems, history of eczema, and parental history of asthma) decision rule strongly predicted profile A—e.g., area under the curve [AUC] of 0⋅98 (95%CI 0⋅97–0⋅99), sensitivity of 1⋅00 (95%CI 0⋅96–1⋅00), and specificity of 0⋅90 (95%CI 0⋅89–0⋅93) in a validation cohort. INTERPRETATION: In three prospective cohorts of infants with bronchiolitis, we identified clinically distinct profiles and their longitudinal relationship with asthma risk. We also derived and validated an accurate prediction rule to determine the profile at highest risk. The current results should advance research into the development of profile-specific preventive strategies for asthma. Elsevier 2022-01-04 /pmc/articles/PMC8741473/ /pubmed/35028545 http://dx.doi.org/10.1016/j.eclinm.2021.101257 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Fujiogi, Michimasa
Dumas, Orianne
Hasegawa, Kohei
Jartti, Tuomas
Camargo, Carlos A.
Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts
title Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts
title_full Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts
title_fullStr Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts
title_full_unstemmed Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts
title_short Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three prospective cohorts
title_sort identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: analysis of three prospective cohorts
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8741473/
https://www.ncbi.nlm.nih.gov/pubmed/35028545
http://dx.doi.org/10.1016/j.eclinm.2021.101257
work_keys_str_mv AT fujiogimichimasa identifyingandpredictingseverebronchiolitisprofilesathighriskfordevelopingasthmaanalysisofthreeprospectivecohorts
AT dumasorianne identifyingandpredictingseverebronchiolitisprofilesathighriskfordevelopingasthmaanalysisofthreeprospectivecohorts
AT hasegawakohei identifyingandpredictingseverebronchiolitisprofilesathighriskfordevelopingasthmaanalysisofthreeprospectivecohorts
AT jarttituomas identifyingandpredictingseverebronchiolitisprofilesathighriskfordevelopingasthmaanalysisofthreeprospectivecohorts
AT camargocarlosa identifyingandpredictingseverebronchiolitisprofilesathighriskfordevelopingasthmaanalysisofthreeprospectivecohorts