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Cutaneous Leishmaniasis in the Dorsal Skin of Hamsters: a Useful Model for the Screening of Antileishmanial Drugs
Published on: April 21, 2012
Real-World Data on Severe Cutaneous Adverse Reactions to Drugs
Sergey Zyryanov1, Elizaveta Terehina1,2, Olga Butranova1
1Department of General and Clinical Pharmacology, Peoples' Friendship University of Russia Named After Patrice Lumumba (RUDN University), 6 Miklukho-Maklaya St., 117198 Moscow, Russia.
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.
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