# Real-World Data on Severe Cutaneous Adverse Reactions to Drugs

## TL;DR

This study identifies drugs commonly linked to severe skin reactions using real-world data from a Russian pharmacovigilance database.

## Contribution

The study provides real-world evidence of drug-induced severe cutaneous adverse reactions using Russian spontaneous reporting data.

## Key findings

- Antibacterial drugs, antineoplastic agents, and antiepileptics were the most frequently reported drug classes linked to SCARs.
- Linagliptin, clindamycin, and piperacillin with beta-lactamase inhibitor showed the strongest signals for causing SCARs.
- Pharmacovigilance databases are effective in identifying SCARs and their associated drugs to improve clinical outcomes.

## Abstract

Background/Objectives: Cutaneous adverse drug reactions (CADRs) represent the most common manifestations of drug-induced allergy, with most unfavorable clinical outcomes seen in severe cutaneous adverse reactions (SCARs). To manage SCARs immediate cessation of the offending drug is needed; therefore, it is crucial to identify the list of medications associated with SCARs in real-world clinical practice. The objective of this study was to evaluate the structure of drugs associated with SCARs and to analyze drug-induced SCAR signals by calculating the reporting odds ratio (ROR) and proportional reporting ratio (PRR) based on spontaneous reports extracted from the Russian national pharmacovigilance database. Methods: A retrospective, descriptive pharmacoepidemiological analysis of spontaneous reports (SRs) registered in the pharmacovigilance database from 1 April 2019 to 31 March 2025. Results: A total of 7011 SRs with SCARs were finally revealed, with 907 identified drug triggers. The most frequently reported were antibacterial drugs for systemic use (22.8%), antineoplastic agents (17.8%), and antiepileptics (6.0%). The top five drugs involved in SCARs were dupilumab (2.14%, n = 244), piperacillin and beta-lactamase inhibitor (2.0%, n = 227), pembrolizumab (1.98%, n = 225), levofloxacin (1.95%, n = 222), and linagliptin (1.93%, n = 220). The strongest signals were detected for linagliptin (PRR = 15.37, 95% CI: 13.54–17.44; ROR = 17.24, 95% CI: 14.95–19.88), followed by clindamycin (PRR = 12.44, 95% CI: 10.89–14.21; ROR = 13.62, 95% CI: 11.77–15.77) and by piperacillin and beta-lactamase inhibitor (PRR = 10.02, 95% CI: 8.86–11.43; ROR = 10.81, 95% CI: 9.42–12.40). Conclusions: Pharmacovigilance databases facilitate the identification of diverse phenotypes of SCARs and the list of culprit drugs. The accumulated data serve as a valuable tool to enhance clinical practice outcomes and strengthen overall healthcare monitoring.