Development and external validation of a risk prediction tool for recurrent wheeze attacks in preschool children in England.
7 affiliations
- 1Division of Respiratory Sciences, University of Leicester, Leicester, UK.
- 2Division of Public Health and Epidemiology, University of Leicester, Leicester, UK.
- 3School of Public Health, Imperial College London, London, UK.
- 4Usher Institute, The University of Edinburgh, Edinburgh, UK.
- 5Leicester Real World Evidence Unit, University of Leicester, Leicester, UK.
- 6Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK.
- 7Paediatric Respiratory Medicine, University Hospitals of Leicester, Leicester, UK.
Abstract
Introduction
Almost half of all children experience wheeze before their sixth birthday, with a subset experiencing recurrent attacks that increase healthcare burden. Early identification of children at high risk could enable timely interventions, but diagnostic tools are limited. The aim of the present study was to develop and validate a prognostic model predicting the risk of recurrent wheeze attacks (primary outcome) and hospitalisations (secondary outcome) within 12 months of an initial preschool acute wheeze presentation.Methods
We developed a multivariable logistic regression model using primary care data from 42 820 children in England aged up to 5 years with acute wheeze episodes recorded in the Clinical Practice Research Datalink. Predictors included demographics, clinical history and treatment patterns. The model was validated internally via bootstrapping and externally using the Secure Anonymised Information Linkage Databank in Wales (9703 children). Model performance was assessed using calibration and discrimination metrics.Results
In the CPRD development cohort, 39.6% experienced a subsequent wheeze attack and 17.4% were hospitalised. Key predictors were the healthcare setting of initial acute wheeze, prior wheeze history and reliever prescriptions; inhaled corticosteroid prescriptions reduced risk. The model demonstrated excellent calibration across internal bootstrap validation and two external validation cohorts (calibration slope=1.00, 0.94 and 0.86, respectively, calibration-in-the-large=0.00, 0.035 and -0.143) and moderate discrimination (C-statistic=0.634, 0.625 and 0.638 for wheeze).Conclusions
Using routinely collected data, the prognostic model shows strong calibration and moderate discrimination for predicting recurrent wheeze in preschool children. Implementation as a web tool could support early risk stratification and guide preventative management.
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BibTeX
@article{broomfield2026development,
title = {{Development and external validation of a risk prediction tool for recurrent wheeze attacks in preschool children in England.}},
author = {Jonathan Broomfield and Erol A Gaillard and Jennifer K Quint and Hilary Pinnock and Clare L Gillies and Mohammad A Al Sallakh and Gwyneth A Davies and David K H Lo},
journal = {ERJ open research},
year = {2026},
month = sep,
doi = {10.1183/23120541.00337-2026},
url = {https://europepmc.org/article/MED/42898782},
note = {CC BY},
}
RIS
TY - JOUR
TI - Development and external validation of a risk prediction tool for recurrent wheeze attacks in preschool children in England.
AU - Jonathan Broomfield
AU - Erol A Gaillard
AU - Jennifer K Quint
AU - Hilary Pinnock
AU - Clare L Gillies
AU - Mohammad A Al Sallakh
AU - Gwyneth A Davies
AU - David K H Lo
PY - 2026
DA - 2026/09/01
JO - ERJ open research
DO - 10.1183/23120541.00337-2026
UR - https://europepmc.org/article/MED/42898782
AB - Introduction Almost half of all children experience wheeze before their sixth birthday, with a subset experiencing recurrent attacks that increase healthcare burden. Early identification of children at high risk could enable timely interventions, but diagnostic tools are limited. The aim of the present study was to develop and validate a prognostic model predicting the risk of recurrent wheeze attacks (primary outcome) and hospitalisations (secondary outcome) within 12 months of an initial preschool acute wheeze presentation.Methods We developed a multivariable logistic regression model using primary care data from 42 820 children in England aged up to 5 years with acute wheeze episodes recorded in the Clinical Practice Research Datalink. Predictors included demographics, clinical history and treatment patterns. The model was validated internally via bootstrapping and externally using the Secure Anonymised Information Linkage Databank in Wales (9703 children). Model performance was assessed using calibration and discrimination metrics.Results In the CPRD development cohort, 39.6% experienced a subsequent wheeze attack and 17.4% were hospitalised. Key predictors were the healthcare setting of initial acute wheeze, prior wheeze history and reliever prescriptions; inhaled corticosteroid prescriptions reduced risk. The model demonstrated excellent calibration across internal bootstrap validation and two external validation cohorts (calibration slope=1.00, 0.94 and 0.86, respectively, calibration-in-the-large=0.00, 0.035 and -0.143) and moderate discrimination (C-statistic=0.634, 0.625 and 0.638 for wheeze).Conclusions Using routinely collected data, the prognostic model shows strong calibration and moderate discrimination for predicting recurrent wheeze in preschool children. Implementation as a web tool could support early risk stratification and guide preventative management.
SN - 2312-0541
ER -