Background: The heterogeneity and lack of validation of existing severity scores for food allergic reactions limit standardization of case management and research advances. We aimed to develop and validate a severity score for food allergic reactions.Methods: Following a multidisciplinary experts consensus, it was decided to develop a food allergy severity score (FASS) with ordinal (oFASS) and numerical (nFASS) formats. oFASS with 3 and 5 grades were generated through expert consensus, and nFASS by mathematical modeling. Evaluation was performed in the EuroPrevall outpatient clinic cohort (8232 food reactions) by logistic regression with request of emergency care and medications used as outcomes. Discrimination, classification, and calibration were calculated. Bootstrapping internal validation was followed by external validation (logistic regression) in 5 cohorts (3622 food reactions). Correlation of nFASS with the severity classification done by expert allergy clinicians by Best‐Worst Scaling of 32 food reactions was calculated.Results: oFASS and nFASS map consistently, with nFASS having greater granularity. With the outcomes emergency care, adrenaline and critical medical treatment, oFASS and nFASS had a good discrimination (receiver operating characteristic area under the curve [ROC‐AUC]>0.80), classification (sensitivity 0.87–0.92, specificity 0.73–0.78), and calibration. Bootstrapping over ROC‐AUC showed negligible biases (1.0 × 10⁻⁶–1.23 × 10⁻³). In external validation, nFASS performed best with higher ROC‐AUC. nFASS was strongly correlated (R 0.89) to best‐worst scoring of 334 expert clinicians.Conclusion: FASS is a validated and reliable method to measure severity of food allergic reactions. The ordinal and numerical versions that map onto each other are suitable for use by different stakeholders in different settings.

Cow’s milk allergy (CMA) is the most common food allergy in infants. This study aimed to identify peptide biomarkers predictive of tolerance in a Spanish population of children with CMA. We investigated specific IgE and IgG4 binding to sequential epitopes of the five major CM allergens (α-s1-, α-s2-, β-, and κ-caseins as well as β-lactoglobulin) using a microarray-based immunoassay. Microarray analysis was performed in 118 patients at baseline and after 6, 18, 30, 42, and 54 months. Most patients tolerated CM at 6 months (40.7%) and 18 months (35.4%). We found significant differences in IgE and IgG4 binding intensity and diversity between allergic and tolerant patients. No differences were observed at baseline. Combining baseline IgE and IgG4 serology variables and peptide microarray analysis results, a predictive model was developed using the XGBoost algorithm to classify tolerance status at different time points. The generated models showed high predictive value at 6 and 30 months with AUCs of 0.883 and 0.833, respectively. Therefore, using IgE and IgG4 antibody-binding peptides at baseline, we generated two models predicting tolerance in children with cow’s milk allergy at 6 and 30 months.

Background: The consumption of plant‐based food has lately largely increased, raising concerns about allergic reactions from ingredients which are currently not subject to mandatory labelling. Methods: We analysed the frequency and severity of allergic reactions to non‐mandatory labelled allergenic foods (pea, lentil, bean, chickpea, fenugreek, pine nut, sunflower‐, poppy‐, pumpkin seed, buckwheat) from two large European cohorts: The Anaphylaxis Registry (NORA) and EuroPrevall outpatient clinic study. Severity was assessed using the Food Allergy Severity Score (FASS) and compared with reactions to mandatory labelled allergenic foods. Results: Among 589 reactions from both cohorts, sunflower seed was the most frequent trigger ( n = 126). In NORA, pine nut (1.0% of food‐induced allergic reactions) was most common followed by pea and buckwheat (0.7% each); in EuroPrevall, sunflower seed (1.2%), poppy seed (0.6%) and lentil (0.6%) predominated. After adjusting for age and sex, the severity of reactions to mandatory labelled seeds and legumes (excluding peanut) were not different (nFASS median: 4.39 vs. 4.43 and 4.56 vs. 4.49). Whereas, cereal‐induced reactions (6.47) were significantly more severe than buckwheat (4.77). In Nora, the number of reactions to fenugreek and pumpkin seed were 7.4‐ and 3.7‐fold higher in 2015–2022 versus 2007–2014. Conclusion: Non‐mandatory labelled allergenic foods were identified to cause severe allergic reactions in two large European cohorts. The frequent involvement of sunflower seed, pine nut, pea and lentil, but also rising numbers of reactions to fenugreek and pumpkin seed, indicates their potential risk. These allergenic foods warrant close monitoring and consideration in future allergen labelling revisions.

Background: Food allergy (FA) significantly impairs health‐related quality of life (HRQL), yet its key determinants remain unclear. This study aimed to identify factors associated with poor HRQL in FA using machine‐learning analysis. Methods: Within the Spanish multicentre BIOGRIAL study, well‐phenotyped patients with IgE‐mediated FA were enrolled. Participants aged ≥ 8 y were included to allow self‐completion of the Food Allergy Quality of Life Questionnaire (FAQLQ). Clinical variables included atopic comorbidities, number and type of food allergies, age at onset, FA duration, need for urgent treatment, and reaction severity graded with the Food Allergy Severity Score. Poor FA‐HRQL was defined as FAQLQ ≥ 5 (range 1–7). Determinants were identified using logistic regression and decision trees. Results: A total of 502 patients were included (63.9% female, 86% adults, 7.4% adolescents, 6.6% children). Median FAQLQ was 4.55. Adults and females had poorer FA‐HRQL than younger participants and males, respectively. Logistic regression identified female sex, multiple allergies, severe reactions, and vegetable allergy as independent predictors. Decision trees identified adult age, female sex, number of food allergies, need for urgent care, reaction severity, and FA onset < 18 y as determinants of poor FA‐HRQL. Adult females with ≥ 7 food allergies had the worst FA‐HRQL (mean FAQLQ 5.93), and 79% of patients with FAQLQ ≥ 5 were adult females. Conclusions: HRQL of people with FA is impaired by multiple determinants that should be addressed through psychosocial support, dietary management and education. Being female was the determinant with the highest negative impact, and adult women with multiple FAs have the poorest FA‐HRQL and require targeted personalised interventions.