Bronchial allergen challenges in children – safety and predictors. Issue 1 (20th January 2013) - Schulze, Johannes; Reinmüller, Wanda; Herrmann, Eva; Rosewich, Martin; Rose, Markus A.; Zielen, Stefan
Abstract: Background: In allergic asthma, the diagnosis of house dust mite (HDM) allergy is mainly based on the patient's history, allergy testing by the skin prick test (SPT) or the levels of allergen‐specific IgE. We retrospectively analysed data from 350 bronchial provocations with HDM and related it to the following parameters: specific IgE, bronchial hyperresponsiveness (BHR) to methacholine testing (MCT) and exhaled NO (eNO). Methods: Approximately 350 patients (5–18 yr of age) with allergic asthma and a positive SPT to HDMs were included. To define the sensitivity and specificity for the detection method of an early asthmatic response (EAR), a receiver‐operating characteristic (ROC) curve was plotted. The accuracy was measured by the area under the ROC curve (AUC). A logistic regression model was used to predict the individual probability of a positive challenge. The results of the regression model were validated in a prospective group of n = 75 patients. Results: The following cut‐off values showed the best combination of sensitivity and specificity: specific IgE Dermatophagoides farinae 19.6 kU/l (AUC, 0.88), PD20 FEV1 0.13 mg methacholine (AUC, 0.73) and eNO 20.1 ppb (AUC, 0.71). The following equation predicted the individual probability of a positive challenge in the retrospective and prospective group: p = 1 . [1 + exp[−(−1.78 + 2.46. 10 log D. far  − 1.25 .10 logPD20 metha)]] −1, (AUC = 0.88). Conclusions: The value of using the specific IgE and MCT as predictors was confirmed in a large number of patients. We also showed, for the first time, that the eNO predicted the EAR. The logistic regression model is repeatable with a good accuracy. Abstract :