Journal of cosmetic dermatology · 2026
Facial Skincare Adverse Event Atlas and Safety Signals From openFDA Cosmetic Reports: A Disproportionality Analysis.
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Sun Zhe, Xiang Huiqiong, Fan Zhuo
Аннотация
OBJECTIVE: To construct a facial-skincare adverse event atlas and detect category-level safety signals using the US FDA openFDA Cosmetic Adverse Events database.
METHODS: We analyzed publicly available openFDA cosmetic adverse event reports (downloaded 2025-12-15; meta.last_updated 2025-12-10). Suspect products were classified into 12 facial-skincare subcategories using keyword rules, excluding hair, makeup, nail, fragrance, oral, deodorant, and bath/body cleansing products. MedDRA preferred terms were grouped into nine clinically interpretable reaction clusters. Reporting odds ratios (RORs) with 95% confidence intervals were computed versus the full database (primary) and within-cohort comparators (sensitivity), with false discovery rate (FDR) control. We performed "case-check" analyses for five prioritized signals to assess product concentration and temporal patterns.
RESULTS: The broad facial cohort comprised 2927 reports and the strict facial sensitivity cohort 1573 reports. The strongest full-database signals were eye-area products with ocular symptoms (ROR 61.67; 95% CI 46.13-82.43), masks with burn-related events (ROR 27.95; 20.39-38.31), retinoid/anti-aging with swelling/angioedema (ROR 21.94; 17.20-28.00), serum/essence with ocular symptoms (ROR 17.82; 13.74-23.10), and exfoliant/peel/scrub with burn-related events (ROR 13.39; 9.68-18.53). Within-cohort comparators attenuated effect sizes but preserved core signals (e.g., eye-area × ocular symptoms within-broad ROR 9.14; 6.68-12.49). Case-check analyses showed low product-name concentration across signals, supporting category-level interpretation.
CONCLUSIONS: openFDA cosmetovigilance data can be leveraged to map facial-skincare adverse event patterns and prioritize plausible safety signals. Eye-area products showed especially strong ocular-related signals, and leave-on products (masks, retinoid/anti-aging, serum/essence) showed coherent burn- and swelling-related signals.
METHODS: We analyzed publicly available openFDA cosmetic adverse event reports (downloaded 2025-12-15; meta.last_updated 2025-12-10). Suspect products were classified into 12 facial-skincare subcategories using keyword rules, excluding hair, makeup, nail, fragrance, oral, deodorant, and bath/body cleansing products. MedDRA preferred terms were grouped into nine clinically interpretable reaction clusters. Reporting odds ratios (RORs) with 95% confidence intervals were computed versus the full database (primary) and within-cohort comparators (sensitivity), with false discovery rate (FDR) control. We performed "case-check" analyses for five prioritized signals to assess product concentration and temporal patterns.
RESULTS: The broad facial cohort comprised 2927 reports and the strict facial sensitivity cohort 1573 reports. The strongest full-database signals were eye-area products with ocular symptoms (ROR 61.67; 95% CI 46.13-82.43), masks with burn-related events (ROR 27.95; 20.39-38.31), retinoid/anti-aging with swelling/angioedema (ROR 21.94; 17.20-28.00), serum/essence with ocular symptoms (ROR 17.82; 13.74-23.10), and exfoliant/peel/scrub with burn-related events (ROR 13.39; 9.68-18.53). Within-cohort comparators attenuated effect sizes but preserved core signals (e.g., eye-area × ocular symptoms within-broad ROR 9.14; 6.68-12.49). Case-check analyses showed low product-name concentration across signals, supporting category-level interpretation.
CONCLUSIONS: openFDA cosmetovigilance data can be leveraged to map facial-skincare adverse event patterns and prioritize plausible safety signals. Eye-area products showed especially strong ocular-related signals, and leave-on products (masks, retinoid/anti-aging, serum/essence) showed coherent burn- and swelling-related signals.