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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.

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. © 2021 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.

Background: Walnut allergy is common across the globe, but data on the involvement of individual walnut components are scarce. Objectives: To identify geographical differences in walnut component sensitization across Europe, explore cosensitization and cross-reactivity, and assess associations of clinical and serological determinants with severity of walnut allergy. Methods: As part of the EuroPrevall outpatient surveys in 12 European cities, standardized clinical evaluation was conducted in 531 individuals reporting symptoms to walnut, with sensitization to all known walnut components assessed in 202 subjects. Multivariable Lasso regression was applied to investigate predictors for walnut allergy severity. Results: Birch-pollen–related walnut sensitization (Jug r 5) dominated in Northern and Central Europe and lipid transfer protein sensitization (Jug r 3) in Southern Europe. Profilin sensitization (Jug r 7) was prominent throughout Europe. Sensitization to storage proteins (Jug r 1, 2, 4, and 6) was detected in up to 10% of subjects. The walnut components that showed strong correlations with pollen and other foods differed between centers. The combination of determinants best predicting walnut allergy severity were symptoms upon skin contact with walnut, atopic dermatitis (ever), family history of atopic disease, mugwort pollen allergy, sensitization to cat or dog, positive skin prick test result to walnut, and IgE to Jug r 1, 5, 7, or carbohydrate determinants (area under the curve = 0.81; 95% CI, 0.73-0.89). Conclusions: Walnut-allergic subjects across Europe show clear geographical differences in walnut component sensitization and cosensitization patterns. A predictive model combining results from component-based serology testing with results from extract-based testing and information on clinical background allows for good discrimination between mild to moderate and severe walnut allergy. © 2020 The Authors

BACKGROUND: Walnut allergy is common across the globe, but data on the involvement of individual walnut components are scarce.OBJECTIVES: To identify geographical differences in walnut component sensitization across Europe, explore cosensitization and cross-reactivity, and assess associations of clinical and serological determinants with severity of walnut allergy.METHODS: As part of the EuroPrevall outpatient surveys in 12 European cities, standardized clinical evaluation was conducted in 531 individuals reporting symptoms to walnut, with sensitization to all known walnut components assessed in 202 subjects. Multivariable Lasso regression was applied to investigate predictors for walnut allergy severity.RESULTS: Birch-pollen-related walnut sensitization (Jug r 5) dominated in Northern and Central Europe and lipid transfer protein sensitization (Jug r 3) in Southern Europe. Profilin sensitization (Jug r 7) was prominent throughout Europe. Sensitization to storage proteins (Jug r 1, 2, 4, and 6) was detected in up to 10% of subjects. The walnut components that showed strong correlations with pollen and other foods differed between centers. The combination of determinants best predicting walnut allergy severity were symptoms upon skin contact with walnut, atopic dermatitis (ever), family history of atopic disease, mugwort pollen allergy, sensitization to cat or dog, positive skin prick test result to walnut, and IgE to Jug r 1, 5, 7, or carbohydrate determinants (area under the curve = 0.81; 95% CI, 0.73-0.89).CONCLUSIONS: Walnut-allergic subjects across Europe show clear geographical differences in walnut component sensitization and cosensitization patterns. A predictive model combining results from component-based serology testing with results from extract-based testing and information on clinical background allows for good discrimination between mild to moderate and severe walnut allergy.

Background: Component-resolved diagnosis (CRD) has revealed significant associations between IgE against individual allergens and severity of hazelnut allergy. Less attention has been given to combining them with clinical factors in predicting severity. Aim: To analyze associations between severity and sensitization patterns, patient characteristics and clinical history, and to develop models to improve predictive accuracy. Methods: Patients reporting hazelnut allergy (n = 423) from 12 European cities were tested for IgE against individual hazelnut allergens. Symptoms (reported and during Double-blind placebo-controlled food challenge [DBPCFC]) were categorized in mild, moderate, and severe. Multiple regression models to predict severity were generated from clinical factors and sensitization patterns (CRD- and extract-based). Odds ratios (ORs) and areas under receiver-operating characteristic (ROC) curves (AUCs) were used to evaluate their predictive value. Results: Cor a 9 and 14 were positively (OR 10.5 and 10.1, respectively), and Cor a 1 negatively (OR 0.14) associated with severe symptoms during DBPCFC, with AUCs of 0.70-073. Combining Cor a 1 and 9 improved this to 0.76. A model using a combination of atopic dermatitis (risk), pollen allergy (protection), IgE against Cor a 14 (risk) and walnut (risk) increased the AUC to 0.91. At 92% sensitivity, the specificity was 76.3%, and the positive and negative predictive values 62.2% and 95.7%, respectively. For reported symptoms, associations and generated models proved to be almost identical but weaker. Conclusion: A model combining CRD with clinical background and extract-based serology is superior to CRD alone in assessing the risk of severe reactions to hazelnut, particular in ruling out severe reactions. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

BACKGROUND: Component-resolved diagnosis (CRD) has revealed significant associations between IgE against individual allergens and severity of hazelnut allergy. Less attention has been given to combining them with clinical factors in predicting severity. AIM: To analyze associations between severity and sensitization patterns, patient characteristics and clinical history, and to develop models to improve predictive accuracy. METHODS: Patients reporting hazelnut allergy (n = 423) from 12 European cities were tested for IgE against individual hazelnut allergens. Symptoms (reported and during Double-blind placebo-controlled food challenge [DBPCFC]) were categorized in mild, moderate, and severe. Multiple regression models to predict severity were generated from clinical factors and sensitization patterns (CRD- and extract-based). Odds ratios (ORs) and areas under receiver-operating characteristic (ROC) curves (AUCs) were used to evaluate their predictive value. RESULTS: Cor a 9 and 14 were positively (OR 10.5 and 10.1, respectively), and Cor a 1 negatively (OR 0.14) associated with severe symptoms during DBPCFC, with AUCs of 0.70-073. Combining Cor a 1 and 9 improved this to 0.76. A model using a combination of atopic dermatitis (risk), pollen allergy (protection), IgE against Cor a 14 (risk) and walnut (risk) increased the AUC to 0.91. At 92% sensitivity, the specificity was 76.3%, and the positive and negative predictive values 62.2% and 95.7%, respectively. For reported symptoms, associations and generated models proved to be almost identical but weaker. CONCLUSION: A model combining CRD with clinical background and extract-based serology is superior to CRD alone in assessing the risk of severe reactions to hazelnut, particular in ruling out severe reactions.

BACKGROUND: We tested the hypothesis that specific molecular sensitization patterns correlate with the clinical data/manifestation in a European peanut allergic population characterized under a common protocol. METHODS: 68 peanut allergic subjects and 82 tolerant controls from 11 European countries were included. Allergy to peanut and lowest symptom-eliciting-dose were established by double-blind placebo-controlled food-challenge in all but anaphylactic subjects. Information of early or late (before or after 14 years of age) onset of peanut allergy was obtained from standardized questionnaires. IgE to peanut allergens rAra h 1-3, 6, 8-9, profilin and CCD were determined using ImmunoCAP. RESULTS: 78% of peanut allergics were sensitised to peanut extract and 90% to at least one peanut component. rAra h 2 was the sole major allergen for the peanut allergic population. Geographic differences were observed for rAra h 8 and rAra h 9, which were major allergens for central/western and southern Europeans, respectively. Sensitisation to rAra h 1 and 2 were exclusively observed in early onset peanut allergy. Peanut tolerant subjects were frequently sensitised to rAra h 8 or 9 but not to storage proteins. Sensitisation to Ara h 2 ≥1.0 kUA /L conferred a 97% probability for a systemic reaction (p=0.0002). Logistic regression revealed a significant influence of peanut extract sensitization and region on the occurrence of systemic reactions (p=0.0185 and p=0.0436 respectively). CONCLUSION: Sensitization to Ara h 1, 2 and 3 is usually acquired in childhood. IgE to Ara h 2 ≥1.0 kUA /L is significantly associated with the development of systemic reactions to peanut. This article is protected by copyright. All rights reserved.

Kiwifruit is a common cause of food allergy. Symptoms range from mild to anaphylactic reactions. We sought to elucidate geographic differences across Europe regarding clinical patterns and sensitization to kiwifruit allergens. Factors associated with the severity of kiwifruit allergy were identified, and the diagnostic performance of specific kiwifruit allergens was investigated. This study was part of EuroPrevall, a multicenter European study investigating several aspects of food allergy. Three hundred eleven patients with kiwifruit allergy from 12 countries representing 4 climatic regions were included. Specific IgE to 6 allergens (Act d 1, Act d 2, Act d 5, Act d 8, Act d 9, and Act d 10) and kiwifruit extract were tested by using ImmunoCAP. Patients from Iceland were mainly sensitized to Act d 1 (32%), those from western/central and eastern Europe were mainly sensitized to Act d 8 (pathogenesis-related class 10 protein, 58% and 44%, respectively), and those from southern Europe were mainly sensitized to Act d 9 (profilin, 31%) and Act d 10 (nonspecific lipid transfer protein, 22%). Sensitization to Act d 1 and living in Iceland were independently and significantly associated with severe kiwifruit allergy (odds ratio, 3.98 [P = .003] and 5.60 [P < .001], respectively). Using a panel of 6 kiwifruit allergens in ImmunoCAP increased the diagnostic sensitivity to 65% compared with 20% for skin prick tests and 46% ImmunoCAP using kiwi extract. Kiwifruit allergen sensitization patterns differ across Europe. The use of specific kiwifruit allergens improved the diagnostic performance compared with kiwifruit extract. Sensitization to Act d 1 and living in Iceland are strong risk factors for severe kiwifruit allergy

BACKGROUND: Fish allergens represent one of the most common causes of adverse reactions to food worldwide. Double-blind placebo-controlled food challenges (DBPCFC) are the gold standard for food allergy diagnosis. However, no standardised recipes are available for common food allergens such as fish, and a well trained dietitian is essential for creating and standardising them. The present study aimed to create and standardise recipes for use in DBPCFCs to fish. METHODS: Three recipes were prepared. Employing a standardised procedure, a total of 35 panelists evaluated the different matrices using an evaluation form. A paired comparison test was used to estimate total evaluation's outcome. Fish allergic patients were challenged with different fish species blinded with the selected matrix and evaluated the recipe using the same form. RESULTS: From a base recipe and step-by-step modifications, a low fat recipe was selected among other recipes tested, which proved to be appropriate for fish blinding, in terms of taste, odour, appearance and blinding. Patients challenged with the final matrix found it acceptable, no matter which fish type was used. CONCLUSIONS: In this pilot study, a recipe with satisfactory organoleptic characteristics was developed and validated for DBPCFC to fish.