Niu Yandong, Lu Haitao, He Lei, Wang Zhanbo, Duan Xinsuo
Department of Dermatology, The Affiliated Hospital of Chengde Medical University, Chengde, Hebei, P.R. China.
Department of Pediatric Surgery, The Affiliated Hospital of Chengde Medical University, Chengde, Hebei, P.R. China.
Medicine (Baltimore). 2025 Sep 12;104(37):e44497. doi: 10.1097/MD.0000000000044497.
Pemphigus is a rare yet serious autoimmune skin disease. This study aimed to identify the drugs most commonly associated with pemphigus risk using the Federal drug administration adverse event reporting system (FAERS) database. Data on drugs and adverse events between 2004 and the second quarter of 2024 were obtained from the FAERS database. The medical dictionary for regulatory activities (MedDRA) was used to identify pemphigus cases, whereas the DrugBank database was used to determine the generic names of the medications. Four signal quantification methods were used for the analysis: odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and empirical Bayesian geometric mean. Additionally, the timing of drug-induced pemphigus was calculated using Weibull shape parameters. Finally, potential factors affecting pemphigus were identified in the FAERS database using univariate and multivariate logistic regression analyses. Of the 7315 adverse event reports linked to pemphigus, diclofenac sodium was involved in 1227 cases, which was the highest number. Disproportionality analysis Disproportionality analysis identified the top 5 drugs that caused adverse reactions: diclofenac sodium, abatacept, tocilizumab, and alendronate sodium. Based on the time to onset of drug-induced pemphigus, the Weibull shape parameter (0.60) indicated that pemphigus induced by this class of drugs was classified as an early failure. Seven independent risk factors related to drugs were identified through multivariable analysis, including diclofenac sodium, abatacept, tocilizumab, alendronate sodium, secukinumab, cetirizine, and chlorhexidine, odds ratio >1 for each. FAERS database was analyzed to identify drugs with strong pemphigus signals, which can be used as a guide for standardizing drug use in clinical practice.
天疱疮是一种罕见但严重的自身免疫性皮肤病。本研究旨在使用美国食品药品监督管理局不良事件报告系统(FAERS)数据库,确定与天疱疮风险最常相关的药物。2004年至2024年第二季度期间的药物和不良事件数据来自FAERS数据库。使用监管活动医学词典(MedDRA)来识别天疱疮病例,而使用药物银行数据库来确定药物的通用名称。采用四种信号量化方法进行分析:比值比、比例报告比、贝叶斯置信传播神经网络和经验贝叶斯几何均值。此外,使用威布尔形状参数计算药物性天疱疮的发生时间。最后,在FAERS数据库中使用单变量和多变量逻辑回归分析确定影响天疱疮的潜在因素。在7315份与天疱疮相关的不良事件报告中,双氯芬酸钠涉及1227例,数量最多。不成比例分析 不成比例分析确定了导致不良反应的前5种药物:双氯芬酸钠、阿巴西普、托珠单抗和阿仑膦酸钠。根据药物性天疱疮的发病时间,威布尔形状参数(0.60)表明此类药物引起的天疱疮被归类为早期失效。通过多变量分析确定了7个与药物相关的独立危险因素,包括双氯芬酸钠、阿巴西普、托珠单抗、阿仑膦酸钠、司库奇尤单抗、西替利嗪和氯己定,每种药物的比值比均>1。对FAERS数据库进行分析,以识别具有强烈天疱疮信号的药物,可为临床实践中规范用药提供指导。