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Modeling the conversion between specific IgE test platforms for nut allergens in children and adolescents
Author(s) -
Hoang Jennifer A.,
Celik Alper,
Lupinek Christian,
Valenta Rudolf,
Duan Lucy,
Dai Ruixue,
Brydges May G.,
Dubeau Aimée,
Lépine Claire,
Wong Samantha,
AlexanianFarr Mara,
Magder Ahuva,
Subbarao Padmaja,
Upton Julia E. M.,
Schmidthaler Klara,
Szépfalusi Zsolt,
Ramani Arun,
Eiwegger Thomas
Publication year - 2021
Publication title -
allergy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.363
H-Index - 173
eISSN - 1398-9995
pISSN - 0105-4538
DOI - 10.1111/all.14529
Subject(s) - immunoglobulin e , allergen , allergy , peanut allergy , medicine , multiplex , immunology , multivariate statistics , cohort , statistics , mathematics , biology , antibody , bioinformatics
Background Multiplex tests allow for measurement of allergen‐specific IgE responses to multiple extracts and molecular allergens and have several advantages for large cohort studies. Due to significant methodological differences, test systems are difficult to integrate in meta‐analyses/systematic reviews since there is a lack of datasets with direct comparison. We aimed to create models for statistical integration of allergen‐specific IgE to peanut/tree nut allergens from three IgE test platforms. Methods Plasma from Canadian and Austrian children/adolescents with peanut/tree nut sensitization and a cohort of sensitized, high‐risk, pre‐school asthmatics (total n = 166) were measured with three R&D multiplex IgE test platforms: Allergy Explorer version 1 (ALEX) (Macro Array Dx), MeDALL‐chip (Mechanisms of Development of Allergy) (Thermo Fisher), and EUROLINE (EUROIMMUN). Skin prick test (n = 51) and ImmunoCAP (Thermo Fisher) (n = 62) results for extracts were available in a subset. Regression models (Multivariate Adaptive Regression Splines, local polynomial regression) were applied if >30% of samples were positive to the allergen. Intra‐test correlations between PR‐10 and nsLTP allergens were assessed. Results Using two regression methods, we demonstrated the ability to model allergen‐specific relationships with acceptable measures of fit ( r 2 = 94%‐56%) for peanut and tree nut sIgE testing at the extract and molecular‐level, in order from highest to lowest: Ara h 2, Ara h 6, Jug r 1, Ana o 3, Ara h 1, Jug r 2, and Cor a 9. Conclusion Our models support the notion that quantitative conversion is possible between sIgE multiplex platforms for extracts and molecular allergens and may provide options to aggregate data for future meta‐analysis.