Peer-reviewed article
Development and external validation of a risk prediction tool for recurrent wheeze attacks in preschool children in England.
Broomfield J, Gaillard EA, Quint JK, Pinnock H, Gillies CL et al. ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001Researchers developed and tested a tool to predict which preschool children in England are at high risk of repeated wheeze attacks within 12 months. The tool uses information from medical records including a child's age, previous wheeze history, and the medicines they have been prescribed. The tool worked well when tested on similar groups of children in England and Wales, though its ability to predict who would be affected was moderate.
Key points
- Nearly 40% of preschool children with an acute wheeze episode experienced another attack within 12 months in the study cohort
- Key risk factors for recurrent wheeze were the healthcare setting where the initial wheeze was treated, prior wheeze history, and being prescribed reliever medications
- Children prescribed inhaled corticosteroids had reduced risk of recurrent wheeze
- The model showed excellent calibration (meaning predictions matched actual outcomes) across three datasets
- The model showed moderate discrimination (C-statistic around 0.63), meaning it could distinguish between children who would and would not have recurrent wheeze, but not perfectly
Limitations
This study only describes the development and validation of a prediction tool; it does not evaluate whether using the tool to guide treatment decisions actually improves children's health outcomes. The study is based on routinely collected primary care data from England and Wales, so results may not apply to other healthcare settings or countries with different clinical practices.
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.