Drug-induced vitiligo: a real-world pharmacovigilance analysis of the FAERS database

N Nonger Shen Q Qingxia Fang Y Yue Wu (Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.) L Lan Lan (Department of Chemical Engineering, School of Engineering) F Fangfang Ma

Abstract

Background In recent years, with the expanding use of novel therapeutics such as immune checkpoint inhibitors and monoclonal antibodies, reports of drug-induced vitiligo have been increasing. This study aimed to identify drugs associated with vitiligo using the FDA Adverse Event Reporting System (FAERS). Methods A retrospective disproportionality analysis was performed on FAERS reports from the first quarter of 2004 to the fourth quarter of 2024. Disproportionality signals were assessed using the Reporting odds ratio (ROR) and Bayesian confidence propagation neural network (BCPNN). Results The present study identified 1,910 cases of vitiligo, with a median age of 54 years (interquartile range [IQR]: 40.0–66.0). The gender distribution among these cases was 45.9% female, 35.9% male, and 18.3% with undetermined gender. The three most frequently reported drugs were nivolumab (152 cases), pembrolizumab (132 cases), and dupilumab (77 cases). Forty-six drugs showed significant positive vitiligo signals. The three strongest signals (based on ROR) were mogamulizumab (ROR 73.93, 95% confidence interval [CI] 39.62–137.94; the lower 95% CI for the information component [IC025] 2.40), imiquimod (ROR 72.00, 95% CI 43.24–119.89; IC025 3.00) and chloroquine (ROR 53.33, 95% CI 17.13–166.02; IC025 0.47). Notably, 80.4% (37/46) of these drugs lacked vitiligo warnings in their FDA-approved labels. Conclusion This study has uncovered an extensive catalog of drugs with the potential to induce vitiligo. While these findings are based on pharmacovigilance signals and require further validation, patients receiving these medications should be closely monitored for the development of vitiligo.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 9
Published September 08, 2025
Pages e0332079
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (5)

N

Nonger Shen

Q

Qingxia Fang

Y

Yue Wu

Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.

L

Lan Lan

Department of Chemical Engineering, School of Engineering

F

Fangfang Ma