Acrylate Patch Testing for Allergic Contact Dermatitis Over 28 Years: Hierarchical Clustering for Subgroup Analysis and Computational Optimization for Patch Test Selection.

BACKGROUND

Acrylate allergy is rising, with many patients showing patch test positivity to multiple acrylates. Understanding acrylate sensitivity can guide avoidance and optimize screening.

OBJECTIVES

To quantify acrylate patch test positivity, define subgroups using hierarchical clustering, and algorithmically optimize acrylate patch testing series.

METHODS

We conducted a retrospective review of 27 acrylate allergens patch tested at 3 Mayo Clinic sites (Arizona, Florida, Minnesota) from 1997 to 2024; 14 had ≥1% positivity. Pairwise copositivity rates were background-corrected and analyzed using hierarchical clustering, followed by computational optimization for patch test screening.

RESULTS

Among 17,148 patients, 90,818 tests yielded 1,557 positives (1.71%). Most frequent positive reactions were 2-hydroxyethyl acrylate 0.1% (HEA, 5.4%), 2-hydroxypropyl methacrylate 2% (HPMA, 5.0%), and 2-hydroxyethyl methacrylate 2% (HEMA, 4.6%). Clustering revealed 2 general subgroups, with ethyl cyanoacrylate 10% (ECA) showing minimal copositivity to other acrylates. Optimization analysis for screening showed that one allergen (HEMA) captured 49.4% of sensitized patients; 2 (HEMA + ECA) captured 72.2%. Four allergens, including HEMA, ECA, HEA, and diethylene glycol diacrylate 0.1% (DEGDA), captured >90%, and a 7-allergen series captured 100%, with no higher yield from additional acrylates in standard screening.

CONCLUSIONS

Acrylate allergy is heterogeneous, comprising 2 subgroups, with cyanoacrylates co-reacting separately. Algorithm-guided series refinement improves diagnostic efficiency by prioritizing high-yield allergens for screening while minimizing unnecessary testing.