Robiyanto Robiyanto, Barrett Jim W, Sandberg Lovisa, Raemaekers Boukje C, Norén G Niklas, Schuiling-Veninga Catharina C M, Hak Eelko, van Puijenbroek Eugène P
Department of PharmacoTherapy, -Epidemiology, and -Economics, Groningen Research Institute of Pharmacy, University of Groningen, Antonius Deusinglaan 1, 9713 AV, Groningen, The Netherlands.
Program Studi Farmasi, Fakultas Kedokteran, Universitas Tanjungpura, Pontianak, Indonesia.
Drug Saf. 2025 Sep 2. doi: 10.1007/s40264-025-01607-9.
Adverse event reporting systems are an important source of safety signals for drug use in pregnancy, but their usefulness in the identification of potential drug-drug interactions (DDIs) remains unclear.
Our objective was to explore the reliability of signal detection for pharmacokinetic DDIs during pregnancy in adverse event reporting systems, focusing on potential interactions between antipsychotics (APs) or antidepressants (ADs) and drugs modifying cytochrome P450 (CYP450) activity, increasing the occurrence of gestational diabetes mellitus (GDM).
Reports related to the use of drugs during pregnancy were identified in VigiBase, the World Health Organization (WHO) global database of adverse event reports. Potential interacting drugs were selected based on WHO Drug Standardised Drug Groupings for CYP450 isoenzymes involved in the metabolic pathway of the AP or AD of interest. We conducted statistical interaction analysis using the omega disproportionality measure and including concomitant medication to identify potential DDIs, followed by a case series review for supporting evidence. Evaluation was subjective by author consensus.
Of the 30 drug-drug-event combinations considered, statistical signals emerged for escitalopram, citalopram, and sertraline and the simultaneous use of CYP2D6 inhibitors with a higher relative reporting rate of GDM. However, case series review of reports did not support the existence of these DDIs because of uncertainties regarding the actual timing of medication use reported as concomitant.
Statistical signals of DDIs between ADs and potential interacting drugs during pregnancy were identified but not pursued further after case reviews. Uncertainty around medication use and event timing affected the reliability of the outcomes. These findings highlight the need to validate signals using detailed report data and stress the importance of accurate medication reporting.
不良事件报告系统是孕期用药安全信号的重要来源，但其在识别潜在药物相互作用（DDIs）方面的效用仍不明确。
我们的目的是探讨不良事件报告系统中孕期药代动力学DDIs信号检测的可靠性，重点关注抗精神病药物（APs）或抗抑郁药物（ADs）与改变细胞色素P450（CYP450）活性的药物之间的潜在相互作用，这些相互作用会增加妊娠期糖尿病（GDM）的发生风险。
在世界卫生组织（WHO）全球不良事件报告数据库VigiBase中识别与孕期用药相关的报告。根据WHO针对参与感兴趣的AP或AD代谢途径的CYP450同工酶的药物标准化分组来选择潜在的相互作用药物。我们使用ω不成比例度量进行统计相互作用分析，并纳入合并用药以识别潜在的DDIs，随后进行病例系列回顾以获取支持证据。评估由作者达成共识后主观进行。
在所考虑的30种药物 - 药物 - 事件组合中，艾司西酞普兰、西酞普兰和舍曲林以及同时使用CYP2D6抑制剂出现了统计学信号，且GDM的相对报告率较高。然而，由于报告中作为合并用药的实际用药时间存在不确定性，对报告的病例系列回顾不支持这些DDIs的存在。
识别出了孕期ADs与潜在相互作用药物之间DDIs的统计学信号，但病例审查后未进一步探究。用药和事件时间的不确定性影响了结果的可靠性。这些发现凸显了使用详细报告数据验证信号的必要性，并强调了准确用药报告的重要性。
