UCLA

Introduction

While a specific number and type of antigens are recognized to detect perennial inhalant allergies, the optimal number and combination of allergens to reliably identify seasonal allergic sensitization is unclear due to limited national data. This study analyzed aeroallergen testing data from a large US clinical reference laboratory to provide guidance for optimizing seasonal allergen test selection.

Methods

The 2019 serum IgE tests for seasonal inhalant allergens were identified from the Quest Diagnostics database. Patients with results for at least 1 of 31 seasonal allergens across 4 allergen classes (11 trees, 7 weeds, 5 grasses, and 8 molds) were analyzed. A step-by-step conditional approach was employed to determine the minimum number and species of allergens needed to identify at least 98% of sensitized patients for each class.

Results

Of 88,042 patients tested for ≥1 seasonal allergen, 1.5%, 1.8%, 1.3%, and 1.6% were tested for all trees, weeds, grasses, and molds, respectively. Of those tested for all allergens within a class, 40.4%, 38.6%, 29.5%, and 21.2% were sensitized to at least one tree, weed, grass, or mold allergen, respectively. Identification of ≥98% of sensitized patients within a class required 8 allergens for trees (mountain cedar, maple box elder, walnut, white ash, elm, birch, cottonwood, and hickory/pecan), 5 for weeds (common ragweed short, rough pigweed, English plantain, lamb's quarters/goosefoot, and Russian thistle), 3 for grasses (June/Kentucky blue grass, Johnson grass, and Bermuda grass), and 7 for molds (Alternaria alternata, Aspergillus fumigatus, Mucor racemosus, Epicoccum purpurascens, Penicillium notatum, Helminthosporium halodes, and Fusarium moniliforme).

Conclusion

A minimum of 23 antigens is required to optimally detect sensitization to four classes of seasonal allergens (i.e., ≥98% identification). The addition of these allergens to unique perennial allergens (cat, dog, mouse, cockroach, and 2 dust mite species) results in a comprehensive elucidation of inhalant allergen sensitization. This knowledge provides a pivotal guide for clinical laboratories as they construct allergen panels to optimize diagnostic yield.