Development of a tool predicting severity of allergic reaction during peanut challenge

开发一种预测花生激发试验中过敏反应严重程度的工具

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Abstract

BACKGROUND: Reliable prognostic markers for predicting severity of allergic reactions during oral food challenges (OFCs) have not been established. OBJECTIVE: To develop a predictive algorithm of a food challenge severity score (CSS) to identify those at higher risk for severe reactions to a standardized peanut OFC. METHODS: Medical history and allergy test results were obtained for 120 peanut allergic participants who underwent double-blind, placebo-controlled food challenges. Reactions were assigned a CSS between 1 and 6 based on cumulative tolerated dose and a severity clinical indicator. Demographic characteristics, clinical features, peanut component IgE values, and a basophil activation marker were considered in a multistep analysis to derive a flexible decision rule to understand risk during peanut of OFC. RESULTS: A total of 18.3% participants had a severe reaction (CSS >4). The decision rule identified the following 3 variables (in order of importance) as predictors of reaction severity: ratio of percentage of CD63(hi) stimulation with peanut to percentage of CD63(hi) anti-IgE (CD63 ratio), history of exercise-induced asthma, and ratio of forced expiratory volume in 1 second to forced vital capacity (FEV(1)/FVC) ratio. The CD63 ratio alone was a strong predictor of CSS (P < .001). CONCLUSION: The CSS is a novel tool that combines dose thresholds and allergic reactions to understand risks associated with peanut OFCs. Laboratory values (CD63 ratio), along with clinical variables (exercise-induced asthma and FEV(1)/FVC ratio) contribute to the predictive ability of the severity of reaction to peanut OFCs. Further testing of this decision rule is needed in a larger external data source before it can be considered outside research settings. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02103270.

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