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Demographics, Overlap, and Latency of Severe Cutaneous Adverse Reactions in an FDA Database
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Demographics, Overlap, and Latency of Severe Cutaneous Adverse Reactions in an FDA Database

Eric Milan Mukherjee, Dodie Park, Amir Asiaee, Matthew S. Krantz, Cosby A. Stone, Michelle Martin-Pozo and Elizabeth J. Phillips
medRxiv
Cold Spring Harbor Laboratory Press, 1.4
2025
DOI: https://doi.org/10.1101/2025.03.05.25323441
PMID: 40093226
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Open Access CC BY-NC-ND V4.0

Abstract

Acute Generalized Exanthematous Pustulosis Drug Reaction with Eosinophilia and Systemic Symptoms FAERS Pharmacovigilance Severe Cutaneous Adverse Reactions Stevens-Johnson Syndrome Toxic Epidermal Necrolysis
Importance Severe cutaneous adverse reactions (SCARs), including Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS-TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), acute generalized exanthematous pustulosis (AGEP), and generalized bullous fixed drug eruption (GBFDE), are rare but life-threatening drug hypersensitivity syndromes. Due to their low incidence and diagnostic complexity, large-scale characterization of SCAR is challenging. Objective To characterize the demographics, causative agents, trends, latency, and phenotypic overlap of SCAR using a large-scale, sanitized pharmacovigilance dataset from FAERS (FDA Adverse Event Reporting System). Design Cross-sectional study of spontaneous adverse event reports. Cases were drawn from the U.S. Food and Drug Administration Adverse Event Reporting System (FDA FAERS) from January 2004 to December 2023 and subjected to sanitization and deduplication. Disproportionality analysis was used to characterize causative agents. Machine learning (random forest classifiers) was used to analyze predictors of drug latency and mortality. Setting Global pharmacovigilance reports submitted to FAERS. Participants A total of 56,683 deduplicated SCAR reports were identified, representing 0.33% of reports during the study period. Exposures Suspected causative drugs, including both small molecules and biologics. Main outcomes and measures Main outcomes included the frequency and distribution of SCAR syndromes, reporting trends over time, latency from drug start to reaction onset, drug-specific disproportionality (PRR, ROR, IC), and co-reporting between SCAR types and related conditions. Results A total of 56,683 unique SCAR reports were identified, including SJS-TEN (28,871), DRESS (22,444), AGEP (6,183), and GBFDE (150). We identified 237 drugs with significant disproportionality for SCAR overall. Co-reporting between SCARs was significantly enriched (p < 1e-200), suggesting overlapping phenotypes. Latency varied by drug and syndrome (median: GBFDE 3 days, AGEP 4 days, SJS-TEN 12 days, DRESS 20 days). Conclusions and relevance SCAR syndromes display distinct but overlapping phenotypes, with variable latency and diverse causative agents. These findings, based on the largest SCAR dataset to date, highlight the need for improved classification frameworks and molecular validation. Large-scale pharmacovigilance, integrated with genomic and histopathologic data, will be critical to improving diagnosis, mechanistic understanding, and clinical management of SCAR.

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