atopic march<\/a>\u201d, a progression that can lead to asthma and allergic rhinitis.<\/p>\nHowever, clinicians have historically struggled to determine which young children will go on to develop more severe, long-term respiratory disease. This uncertainty has limited opportunities for early intervention and personalised care.<\/p>\n
Machine Learning Asthma Prediction Models Show Strong Accuracy<\/p>\n
Researchers conducted a large retrospective birth cohort study using electronic health record data from 10,688 children diagnosed with atopic dermatitis before the age of three.<\/p>\n
Two machine learning asthma prediction models were developed: a comprehensive model using detailed clinical variables, and a simplified model based on routinely available clinical data.<\/p>\n
Both models demonstrated strong performance in predicting moderate-to-severe persistent asthma between the ages of five and 11.<\/p>\n
The comprehensive model achieved an area under the curve (AUC) of 0.893, while the simplified model showed nearly identical discrimination (AUC: 0.892). At 95% specificity, sensitivity reached 40.4% and 36.2%, respectively, with positive predictive values of 39.3% and 33.8%.<\/p>\n
Predicting Allergic Rhinitis and Risk Stratification<\/p>\n
In addition to asthma, the models were also applied to predict allergic rhinitis.<\/p>\n
Performance was more moderate, with AUC values of 0.793 and 0.773. However, positive predictive values were notably high in higher-risk groups, reaching over 70% in the comprehensive model.<\/p>\n
Importantly, both the comprehensive and simplified models for asthma and allergic rhinitis showed good calibration, particularly among children classified as highest risk.<\/p>\n
This suggests that machine learning prediction tools may be effective for stratifying patients and identifying those who could benefit from closer monitoring or preventive strategies.<\/p>\n
Implications for Early, Personalised Care<\/p>\n
These findings highlight the potential of machine learning prediction to transform paediatric allergy care. By leveraging early-life clinical data, clinicians may be able to move beyond reactive treatment and instead adopt proactive, individualised approaches.<\/p>\n
The study was limited by its retrospective design and reliance on data from a single healthcare system, which may affect generalisability. Future research will be needed to validate these models across diverse populations and assess their impact in real-world clinical settings.<\/p>\n
If confirmed, such tools could play a key role in identifying high-risk children earlier, enabling targeted interventions that may alter the trajectory of the atopic march.<\/p>\n
Reference<\/p>\n
Chen W et al. Machine learning prediction of asthma and allergic rhinitis in children with early-onset atopic dermatitis. J Allergy Clin Immunol. 2026;DOI:10.1016\/j.jaci.2026.03.025.<\/p>\n
Featured image: Evgeniia Primavera on Adobe Stock<\/p>\n","protected":false},"excerpt":{"rendered":"A NEW study showed that machine learning prediction models could identify which children with early-onset eczema were most…\n","protected":false},"author":2,"featured_media":418599,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[103,61,60],"class_list":{"0":"post-418598","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-health","8":"tag-health","9":"tag-ie","10":"tag-ireland"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/418598","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/comments?post=418598"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/418598\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media\/418599"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media?parent=418598"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/categories?post=418598"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/tags?post=418598"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}