Abstract

A reliable asthma diagnosis is difficult in wheezing preschool children. To assess whether exhaled biomarkers, expression of inflammation genes, and early lung function measurements can improve a reliable asthma prediction in preschool wheezing children. Two hundred two preschool recurrent wheezers (aged 2-4 yr) were prospectively followed up until 6 years of age. At 6 years of age, a diagnosis (asthma or transient wheeze) was based on symptoms, lung function, and asthma medication use. The added predictive value (area under the receiver operating characteristic curve [AUC]) of biomarkers to clinical information (assessed with the Asthma Predictive Index [API]) assessed at preschool age in diagnosing asthma at 6 years of age was determined with a validation set. Biomarkers in exhaled breath condensate, exhaled volatile organic compounds (VOCs), gene expression, and airway resistance were measured. At 6 years of age, 198 children were diagnosed (76 with asthma, 122 with transient wheeze). Information on exhaled VOCs significantly improved asthma prediction (AUC, 89% [increase of 28%]; positive predictive value [PPV]/negative predictive value [NPV], 82/83%), which persisted in the validation set. Information on gene expression of toll-like receptor 4, catalase, and tumor necrosis factor-α significantly improved asthma prediction (AUC, 75% [increase of 17%]; PPV/NPV, 76/73%). This could not be confirmed after validation. Biomarkers in exhaled breath condensate and airway resistance (pre- and post- bronchodilator) did not improve an asthma prediction. The combined model with VOCs, gene expression, and API had an AUC of 95% (PPV/NPV, 90/89%). Adding information on exhaled VOCs and possibly expression of inflammation genes to the API significantly improves an accurate asthma diagnosis in preschool children. Clinical trial registered with www.clinicaltrial.gov (NCT 00422747).

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