Authors
JennaKay Colquitt, James A Yiannias, Mark D P Davis, Matthew R Hall, Molly J Youssef, Yul W Yang
Published in
Dermatitis : contact, atopic, occupational, drug. Pages 17103568261479501. Aug 21, 2026. Epub Aug 21, 2026.
Abstract
Acrylate allergy is rising, with many patients showing patch test positivity to multiple acrylates. Understanding acrylate sensitivity can guide avoidance and optimize screening.
To quantify acrylate patch test positivity, define subgroups using hierarchical clustering, and algorithmically optimize acrylate patch testing series.
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.
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.
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.
PMID:
42629958
Bibliographic data and abstract were imported from PubMed on 22 Aug 2026.
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