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

Background: Prognostication of peanut allergy (PNA) is relevant for early interventions. We aimed to determine baseline parameters associated with the development of PNA in 3- to 15-month-olds with likely egg and/or milk allergy, and/or moderate to severe atopic dermatitis (AD) and a positive egg/milk skin prick test (SPT), but no known PNA. Methods: The primary endpoint was PNA [confirmed/convincing diagnosis or last classified as serologic PNA (<2 years, ≥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. Results: 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. Conclusions: 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.