Clinical factors associated with peanut allergy in a high‐risk infant cohort

Abstract

Prognostication of peanut allergy (PNA) is relevant for early interventions. We aimed to determine baseline parameters associated with development of PNA in 3–15 month olds with likely egg and/or milk allergy, and/or moderate-severe atopic dermatitis (AD) and a positive egg/milk skin prick test (SPT), but no known PNA. The primary endpoint was PNA [confirmed/convincing diagnosis or last classified as serologic PNA (<2 yrs, ≥5 kUA/L, otherwise ≥14 kUA/L, peanut-IgE)] among 511 participants (median follow-up, 7.3 years). Associations were explored with univariate logistic regression; factors with p<0.15 were analyzed by stepwise multiple logistic regression, using data stratified by PNA status and randomly assigned to development and validation datasets. 205/511 (40.1%) had PNA. Univariate factors associated with PNA (p<0.01) included: increased AD severity, larger egg and peanut SPT, greater egg, milk, peanut, Ara h1-h3 IgE, higher peanut IgG and IgG4, and increased pregnancy peanut consumption. P-values were between 0.01 and 0.05 for younger age, non-white race, lack of breastfeeding, and increased lactation peanut consumption. Using a development dataset, the multivariate model identified younger age at enrollment, greater peanut and Ara h2 IgE, and lack of breastfeeding as prognosticators. The final model predicted 79% in the development and 75% in the validation dataset (AUC=0.83 for both). Models using stricter or less strict PNA criteria both found Ara h2 as predictive. Key factors associated with PNA in this high risk population included lack of breastfeeding, age, and greater Ara h2 and peanut-specific IgE, which can be used to prognosticate outcomes.