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Lancet Respir Med. 2015 Dec;3(12):973-84. doi: 10.1016/S2213-2600(15)00428-2. Epub 2015 Nov 18.

Childhood asthma prediction models: a systematic review.

Author information

1
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands. Electronic address: H.A.Smit@umcutrecht.nl.
2
Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Hospital del Mar Research Institute (IMIM), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain; Department of Experimental and Health Sciences, University of Pompeu Fabra (UPF), Barcelona, Spain.
3
Institute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Germany; Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany.
4
WHO Collaborating Center for Asthma and Rhinitis, Montpellier, France; University Hospital of Montpellier, Hôpital Arnaud de Villeneuve, Montpellier, France.
5
Department of Paediatrics, Oslo University Hospital and University of Oslo, Oslo, Norway.
6
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands; Dutch Cochrane Centre, Julius Centre for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands.

Abstract

Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.

PMID:
26597131
DOI:
10.1016/S2213-2600(15)00428-2
[Indexed for MEDLINE]

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