ArticlePediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology2025
Early-life prediction of school-age asthma among recurrent Wheezers in preschoolers: The WHEEP study.
Article in Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Preschool Oscillometry and Later Asthma-Related Outcomes: A Systematic Review of Longitudinal Studies.Children (Basel, Switzerland) · 2026Review
- Early-life prediction of school-age asthma among recurrent Wheezers in preschoolers: The WHEEP study.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
14 authors.
Funding
Abstract
backgroundEarly identification of childhood asthma is critical to prevent over- and undertreatment. Previous asthma prediction models often rely on subjective outcomes, limiting generalizability. This study aimed to develop an asthma prediction model using objective measures.
methodsThis study was embedded in a multicenter prospective cohort of children aged 1-4 years with recurrent wheezing presenting at pediatric secondary care clinics who were followed up for 12 months and re-assessed between ages 6 and 12 years. Candidate predictors included demographic, environmental, and asthma-related factors. Asthma at school age was defined as at least two of the three criteria: asthma medication use, spirometry with bronchodilator reversibility, and elevated fractional exhaled nitric oxide levels. LASSO regression was applied to identify the most predictive variables in an optimal and parsimonious model, and model performance was evaluated.
resultsOf 144 children with recurrent wheezing at age 1-4 years, 25% were classified as having asthma at school age. The optimal model for predicting asthma at school age demonstrated good predictive performance (area under the curve (AUC) (95% CI): 0.83 (0.73-0.93), sensitivity: 0.69, specificity: 0.86, positive predictive value (PPV): 0.66, and negative predictive value (NPV): 0.88). The parsimonious model showed slightly lower performance (AUC (95% CI): 0.82 (0.71-0.94), sensitivity: 0.67, specificity: 0.86, PPV: 0.65, NPV: 0.87).
conclusionOur models highlight the importance of using objectively defined asthma in early prediction of asthma at school age, as demonstrated by their high discriminative performance. Future studies should validate these models and incorporate clearly defined objective outcome measures when developing new models for pediatric secondary care clinics.
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