Real-world phenotyping and risk assessment of childhood asthma burden using national registries
Kjell Erik Julius Håkansson1, Nada Alabdulkarim2, Silvia Cabrera Guerrero3
1Department of Respiratory Medicine, Copenhagen University Hospital - Hvidovre, Hvidovre, Denmark.
Insights
Childhood asthma risk is better classified using routine clinical data to identify T2 (eosinophils, IgE) and non-T2 factors. This approach improves adverse outcome prediction in pediatric asthma management.
Area of Science:
- Pediatric Allergy and Immunology
- Respiratory Medicine
- Clinical Data Science
Background:
- Asthma phenotype classification aids risk assessment, but prior studies focused on adults and research settings.
- Clinical applicability of asthma phenotype classification in pediatric populations remains underexplored.
Purpose of the Study:
- To evaluate the utility of routinely collected clinical data for classifying childhood asthma phenotypes.
- To assess the association of identified phenotypes with asthma severity, control, and exacerbation risk in children.
Main Methods:
- Utilized a Danish nationwide database of 29,851 children (aged 2-17) with inhaled corticosteroid-treated asthma.
- Classified phenotypes based on T2 markers (blood eosinophils, IgE) and non-T2 factors (in utero tobacco, viral infections).
- Employed logistic regression to analyze associations between risk factors and asthma outcomes over two years.
Main Results:
- 85.8% of children exhibited at least one T2 risk factor; 29.3% had mixed T2/non-T2 factors.
- Elevated eosinophils and IgE were significantly linked to increased exacerbations and asthma severity.
- A dose-dependent relationship was observed between biomarker levels and adverse outcomes, with cumulative risk factors increasing adverse outcomes (OR 3.13).
Conclusions:
- Asthma phenotypic markers from research protocols are reliably applicable using routine clinical data.
- This real-world data approach enhances the classification of adverse asthma outcomes in children.
- Routine data enables more accurate risk stratification for pediatric asthma management.
Background:
Phenotype classification contributes to risk assessment of asthma. Previous studies have applied this concept primarily to adult populations and in the setting of research protocol assessments which may not be applicable to clinical settings.
Objective:
Exploring the value of routinely collected clinical data for phenotype classification and risk assessment of childhood asthma.
Methods:
Using hospital and laboratory data, 29,851 children in a Danish nationwide database aged 2-17 years with ICS-treated asthma in 2015 followed for two years (730 days) were classified to have T2 (elevated blood eosinophils (>300 cells/μL) and/or elevated total- or specific-IgE), and/or non-T2 risk factors (in utero tobacco exposure and/or severe viral infections). Logistic regression was applied to quantify associations of risk factors with asthma severity, control, and exacerbation risk.
Results:
In a complete case analysis, 85.8 % children had at least one T2 risk factor and 29.3 % had mixed T2/non-T2 risk factors. Elevated blood eosinophils and total/specific IgE were associated with exacerbations (ORs 1.55 (1.38-1.73) and 1.41 (1.20-1.66) and higher asthma severity (1.42 (1.24-1.63) and 1.31 (1.08-1.60)), respectively. Dose-dependency was observed between blood eosinophil counts, total IgE levels, and risk of adverse outcomes. Furthermore, accumulation of risk factors demonstrated an increasing risk, with children with all four risk factors having a high risk of any adverse asthma-related outcome (OR 3.13 (2.03-4.82) CONCLUSION: Asthma phenotypic markers defined in research protocols can be reliably applied in real-world settings by utilizing data collected during routine clinical care and enable better classification of risk of adverse asthma outcomes.
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