{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T14:27:32Z","timestamp":1782743252827,"version":"3.54.5"},"reference-count":31,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T00:00:00Z","timestamp":1677196800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pediatric Pulmonology"],"published-print":{"date-parts":[[2023,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>To develop and validate a clinical prediction model to identify school\u2010age asthma in preschool asthmatic children.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Design<\/jats:title><jats:p>In this retrospective prognosis cohort study, asthmatic children aged 3\u20135 years were enrolled with at least 2 years of follow\u2010up, and their potential variables at baseline and the prognosis of school\u2010age asthma were collected from medical records. A clinical prediction model was developed using Logistic regression. The performance of prediction model was assessed and quantified by discrimination of the area under the receiver operating characteristic curve (AUC) and calibration of Brier score. The model was validated by the temporal\u2010validation method.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In the development dataset, 2748 preschool asthmatic children were included for model development, and 883 (32.13%) children were translated to school\u2010age asthma. The independent prognostic variables with an increased risk for school\u2010age asthma were used to develop the prediction model, including: age, parental asthma, early frequent wheezing, allergic rhinitis, eczema, allergic conjunctivitis, obesity, and aeroallergen of dust mite. While assessing model performance, the discrimination power of AUC was moderate [0.788 (0.770\u20130.805)] with sensitivity (81.5%) and specificity (60.9%), and the calibration of Brier score was 0.169, supporting the calibration ability. In the temporal\u2010validation dataset of 583 preschool asthmatic children, our model showed satisfactory discrimination (AUC 0.818) and calibration (Brier score 0.150). The prediction model was presented by the web\u2010based calculator (<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/casthma.shinyapps.io\/dynnomapp\/\">https:\/\/casthma.shinyapps.io\/dynnomapp\/<\/jats:ext-link>) and a nomogram for clinical application.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>In preschool asthmatic children, our prediction model could be used to predict the risk of school\u2010age asthma.<\/jats:p><\/jats:sec>","DOI":"10.1002\/ppul.26331","type":"journal-article","created":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T04:24:55Z","timestamp":1674707095000},"page":"1391-1400","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Development and validation of a prediction model to predict school\u2010age asthma in preschool 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