Prediction of food allergy reaction severity: biomarkers and host factors

Prediction of food allergy reaction severity remains a challenging clinical dilemma, with no single biomarker or patient factor serving as a definitive predictor. Clinically, being able to accurately estimate future reaction severity would be a key advancement in terms of risk-stratifying patients who might most benefit from specific immunotherapy, anti-IgE therapy, or at minimum, ensuring this population always has autoinjectable epinephrine. This mini-review explores advancements in two key domains: biomarkers and host factors. Biomarker studies highlight the predictive limitations of IgE sensitization levels, while emerging tools such as basophil activation tests (BAT) and bead-based epitope assays (BBEA) are promising but are not yet in widespread use. Specifically, BAT demonstrates superior discriminatory power for severe peanut and baked egg reactions, whereas Arah2 component level above 1.4 kU/L suggest a more severe peanut allergy phenotype. Host factors, including comorbid conditions, age, and behavioral variables, further complicate severity prediction. While asthma has frequently been assumed to be involved in more severe reactions, recent meta-analyses refute this association unless asthma is poorly controlled. Similarly, a history of anaphylaxis does not reliably predict future reaction severity. Age emerges as a significant variable, with adolescents through the fourth decade of life displaying a higher risk for severe reactions. Additionally, cofactors such as exercise, alcohol, and certain medications may modulate reaction severity, albeit with varying degrees of evidence. Despite these advances, significant knowledge gaps remain in predicting reaction severity with high confidence. The future likely lies in a multifactorial approach. Understanding the interplay of biomarkers and host factors will be crucial in developing more accurate predictive models, ultimately enhancing food allergy management and patient safety.