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Identifying and predicting severe bronchiolitis profiles at high risk for developing asthma: Analysis of three
Michimasa Fujiogi1, Orianne Dumas2, Kohei Hasegawa1
1Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, 125 Nashua Street, Suite 920, Boston, MA 02114-1101, USA.
Insights
This study identified four infant bronchiolitis profiles, with one profile significantly increasing asthma risk. A validated decision rule accurately predicts this high-risk profile for targeted asthma prevention.
Area of Science:
- Pediatric respiratory medicine
- Clinical epidemiology
- Asthma research
Background:
- Bronchiolitis is a leading cause of infant hospitalization and a major risk factor for childhood asthma.
- Evidence suggests significant heterogeneity within bronchiolitis, necessitating subgroup identification.
- Understanding these subgroups is crucial for predicting asthma development.
Purpose of the Study:
- To identify distinct, reproducible bronchiolitis subgroups (profiles) in infants.
- To determine the association between these profiles and the risk of developing asthma.
- To develop and validate a decision rule for predicting the highest-risk profile for asthma.
Main Methods:
- Latent class analysis of three multicenter prospective cohorts (n=3081) of infants hospitalized for bronchiolitis.
- Examination of profile association with asthma risk up to age 6-7 years.
- Recursive partitioning analysis to create and validate a predictive decision rule for the highest-risk profile.
Main Results:
- Four distinct bronchiolitis profiles (A-D) were identified, varying in severity and associated factors.
- Profile A, characterized by a history of breathing problems/eczema and non-RSV infection, showed a significantly higher risk for asthma (38% vs. 23%).
- A 4-predictor decision rule (RSV infection, breathing problems, eczema, parental asthma history) demonstrated high predictive accuracy (AUC 0.98) for the high-risk profile.
Conclusions:
- Distinct infant bronchiolitis profiles exist, with varying longitudinal relationships to asthma risk.
- An accurate and validated prediction rule can identify infants at highest risk for asthma development.
- These findings support the development of profile-specific preventive strategies for childhood asthma.
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.
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