Scientific Study

Background: Peanut allergy (PA) is associated with an economic and psychologic burden on patients and families. Its diagnosis includes tests for peanut specific IgE (sIgE), the values of which usually are categorized as positive or negative using a predefined cutoff (usually 0.35kU/L). With the use of Bayes theorem, this categorization can be replaced with a continuous interpretation if sIgE which accounts for the prevalence of PA and history of ingestion. Objective: We performed a pilot investigation with the results of oral food challenges (OFC) to evaluate a method for estimating the likelihood ratio (LR) for each value of sIgE. The LR could be used to estimate the probability of PA. Methods: OFC outcomes and serum IgE values from 117 children seen in an allergy clinic between January 2017 to November 2019 were obtained. Polynomial regression of the Receiver Operation Characteristics (ROC) curve was used to determine a LR for each value of sIgE. Linear regression was used to estimate a LR for each of value of sIgE. Results: sIgE ranged from <0.1kU/L to 35kU/L. Bayes' theorem and a ROC curve was used to estimate LRs for each value of peanut sIgE. The value of IgE associated with a LR of 1 was 0.22kU/L, which is comparable to other studies that used a value of 0.35kU/L to separate positive from negative results. Conclusion: When combined with estimates of pretest probability, this method should permit development of computerized decision-making algorithms to estimate the probability that a patient has peanut allergy.