Prediction models for childhood asthma: a systematic review

Background The inability to objectively diagnose childhood asthma before age five often results in both under‐treatment and over‐treatment of asthma in preschool children. Prediction tools for estimating a child's risk of developing asthma by school‐age could assist physicians in early asthma care for preschool children. This review aimed to systematically identify and critically appraise studies which either developed novel or updated existing prediction models for predicting school‐age asthma. Methods Three databases (MEDLINE, Embase and Web of Science Core Collection) were searched up to July 2019 to identify studies utilizing information from children ≤5 years of age to predict asthma in school‐age children (6‐13 years). Validation studies were evaluated as a secondary objective. Results Twenty‐four studies describing the development of 26 predictive models published between 2000 and 2019 were identified. Models were either regression‐based (n = 21) or utilized machine learning approaches (n = 5). Nine studies conducted validations of six regression‐based models. Fifteen (out of 21) models required additional clinical tests. Overall model performance, assessed by area under the receiver operating curve (AUC), ranged between 0.66 and 0.87. Models demonstrated moderate ability to either rule in or rule out asthma development, but not both. Where external validation was performed, models demonstrated modest generalizability (AUC range: 0.62‐0.83). Conclusion Existing prediction models demonstrated moderate predictive performance, often with modest generalizability when independently validated. Limitations of traditional methods have shown to impair predictive accuracy and resolution. Exploration of novel methods such as machine learning approaches may address these limitations for future school‐age asthma predictio

Inhaled corticosteroids in childhood asthma: the story continues

Inhaled corticosteroids (ICS) are the most effective anti-inflammatory drugs for the treatment of persistent asthma in children. Treatment with ICS decreases asthma mortality and morbidity, reduces symptoms, improves lung function, reduces bronchial hyperresponsiveness and reduces the number of exacerbations. The efficacy of ICS in preschool wheezing is controversial. A recent task force from the European Respiratory Society on preschool wheeze defined two different phenotypes: episodic viral wheeze, wheeze that occurs only during respiratory viral infections, and multiple-trigger wheeze, where wheeze also occurs in between viral episodes. Treatment with ICS appears to be more efficacious in the latter phenotype. Small particle ICS may offer a potential benefit in preschool children because of the favourable spray characteristics. However, the efficacy of small particle ICS in preschool children has not yet been evaluated in prospective clinical trials. The use of ICS in school children with asthma is safe with regard to systemic side effects on the hypothalamic–pituitary–adrenal axis, growth and bone metabolism, when used in low to medium doses. Although safety data in wheezing preschoolers is limited, the data are reassuring. Also for this age group, adverse events tend to be minimal when the ICS is used in appropriate doses

Predicting asthma in preschool children with asthma symptoms: study rationale and design

<p>Abstract</p> <p>Background</p> <p>In well-child care it is difficult to determine whether preschool children with asthma symptoms actually have or will develop asthma at school age. The PIAMA (Prevention and Incidence of Asthma and Mite Allergy) Risk Score has been proposed as an instrument that predicts asthma at school age, using eight easy obtainable parameters, assessed at the time of first asthma symptoms at preschool age. The aim of this study is to present the rationale and design of a study 1) to externally validate and update the PIAMA Risk Score, 2) to develop an Asthma Risk Appraisal Tool to predict asthma at school age in (specific subgroups of) preschool children with asthma symptoms and 3) to test implementation of the Asthma Risk Appraisal Tool in well-child care.</p> <p>Methods and design</p> <p>The study will be performed within the framework of Generation R, a prospective multi-ethnic cohort study. In total, consent for postnatal follow-up was obtained from 7893 children, born between 2002 and 2006. At preschool age the PIAMA Risk Score will be assessed and used to predict asthma at school age. Discrimination (C-index) and calibration will be assessed for the external validation. We will study whether the predictive ability of the PIAMA Risk Score can be improved by removing or adding predictors (e.g. preterm birth). The (updated) PIAMA Risk Score will be converted to the Asthma Risk Appraisal Tool- to predict asthma at school age in preschool children with asthma symptoms. Additionally, we will conduct a pilot study to test implementation of the Asthma Risk Appraisal Tool in well-child care.</p> <p>Discussion</p> <p>Application of the Asthma Risk Appraisal Tool in well-child care will help to distinguish preschool children at high- and low-risk of developing asthma at school age when asthma symptoms appear.</p> <p>This study will increase knowledge about the validity of the PIAMA risk score and might improve risk assessment of developing asthma at school age in (specific subgroups of) preschool children, who present with asthma symptoms at well-child care.</p