L23:
Predicting Peanut Allergy in an Unbiased Allergy Clinic Population Using Peanut Specific IgE Levels Measured in Two Independent Assays: Immunocap and Immulite 2000
Monday, March 5, 2018
South Hall A2 (Convention Center)
Carah B. Santos, MD, Bruce J. Lanser, MD, Matthew J. Strand, PhD, Erwin W. Gelfand, MD FAAAAI
Rationale: Prior studies establishing diagnostic decision points associated with high probability of failing a double-blind, placebo-controlled oral food challenge (DBPCOFC) utilized selected, highly atopic populations, and food allergy was not consistently confirmed via OFC. We assessed the performance characteristics of two diagnostic tests to predict peanut allergy (PA) determined by DBPCOFC in children representing a more general allergy clinic population.

Methods: Patients with a history of physician-diagnosed PA and positive skin prick test and/or detectable serum specific IgE (sIgE) by ImmunoCAP were recruited for this prospective study. Patients with severe atopic dermatitis or asthma were excluded. Subjects had ImmunoCAP and IMMULITE sIgE levels drawn and underwent graded, DBPCOFC to peanut. A fitted logistic regression model expressed the probability of an allergic reaction; 95% positive predictive values (PPVs) and 50% negative predictive values were calculated. Receiver operating curves were constructed and area under the curve computed to compare each test’s ability to predict clinical PA.

Results: 51 subjects, ages 3-20 years (median=8) underwent peanut DBPCOFC; 30 subjects failed (58.8%). IMMULITE peanut sIgE and ImmunoCAP Ara h 2 component testing performed similarly and were superior to ImmunoCAP crude peanut sIgE in predicting PA. Our resultant 95% PPV for PA via ImmunoCAP (80.3 kUA/L) is higher than previously published values.

Conclusions: These results, generated from a unique population, proved valuable for the diagnosis of PA in a general allergy clinic population. This suggests that sIgE to Ara h 2 by ImmunoCAP or peanut sIgE by IMMULITE may be the most accurate tests for diagnosing and predicting PA.