Severe cutaneous adverse reactions to drugs: A real-world pharmacovigilance study using the FDA Adverse Event Reporting System database - Li, Dongxuan; Gou, Jinghui; Zhu, Jun; Zhang, Tongyan; Liu, Feng; Zhang, Daojun; Dai, Liyang; Li, Wenjun; Liu, Qinglong; Qin, Chunmeng; Du, Qian; Liu, Songqing (Frontiers in Pharmacology, 2023)
Background: Sound drug safety information is important to optimize patient management, but the widely recognized comprehensive landscape of culprit-drug for severe cutaneous adverse reactions (SCARs) is currently lacking. Objective: Provide a comprehensive landscape of culprit-drug of SCARs to guide clinical practice. Methods: We analyzed reports associated with SCARs in the FDA Adverse Event Reporting System (FAERS) database between January 1, 2004, and December 31, 2021, compiled a list of drugs with potentially serious skin toxicity. According to this list, we summarized the reporting proportions of different drugs and drug class and conducted disproportionality analysis for all the drugs. In addition, the risk characteristic of SCARs due to different drugs and drug class was summarized by positive–negative distribution based on the results of the disproportionality analysis. Results: A total of 77,789 reports in FAERS were considered SCARs-related, of which lamotrigine (6.2%) was the most reported single drug followed by acetaminophen (5.8%) and allopurinol (5.8%), and antibacterials (20.6%) was the most reported drug class followed by antiepileptics (16.7%), antineoplastics (11.3%). A total of 1,219 drugs were reported as culprit-drug for SCARs in those reports, and the largest number of drugs belonged to antineoplastics. In disproportionality analysis, 776 drugs showed at least one positive pharmacovigilance signals. Drugs with the most positive signals are lamotrigine, acetaminophen, furosemide and sulfamethoxazole/trimethoprim. Conclusion: Our study provided a real-world overview of SCARs to drugs, and the investigation of SCARs positive–negative distribution across different drugs revealed its risk characteristic, which may help optimize patient management.