Naing Cho, Aung Kyan, Ahmed Syed Imran, Mak Joon Wah
School of Medical Sciences, International Medical University, Kuala Lumpur, Malaysia.
Drug Healthc Patient Saf. 2012;4:87-92. doi: 10.2147/DHPS.S34493. Epub 2012 Aug 3.
For all medications, there is a trade-off between benefits and potential for harm. It is important for patient safety to detect drug-event combinations and analyze by appropriate statistical methods. Mefloquine is used as chemoprophylaxis for travelers going to regions with known chloroquine-resistant Plasmodium falciparum malaria. As such, there is a concern about serious adverse events associated with mefloquine chemoprophylaxis. The objective of the present study was to assess whether any signal would be detected for the serious adverse events of mefloquine, based on data in clinicoepidemiological studies.
We extracted data on adverse events related to mefloquine chemoprophylaxis from the two published datasets. Disproportionality reporting of adverse events such as neuropsychiatric events and other adverse events was presented in the 2 × 2 contingency table. Reporting odds ratio and corresponding 95% confidence interval [CI] data-mining algorithm was applied for the signal detection. The safety signals are considered significant when the ROR estimates and the lower limits of the corresponding 95% CI are ≥2.
Two datasets addressing adverse events of mefloquine chemoprophylaxis (one from a published article and one from a Cochrane systematic review) were included for analyses. Reporting odds ratio 1.58, 95% CI: 1.49-1.68 based on published data in the selected article, and 1.195, 95% CI: 0.94-1.44 based on data in the selected Cochrane review. Overall, in both datasets, the reporting odds ratio values of lower 95% CI were less than 2.
Based on available data, findings suggested that signals for serious adverse events pertinent to neuropsychiatric event were not detected for mefloquine. Further studies are needed to substantiate this.
对于所有药物而言，在益处与潜在危害之间都存在权衡。检测药物 - 事件组合并通过适当的统计方法进行分析对于患者安全至关重要。甲氟喹被用作前往已知有耐氯喹恶性疟原虫疟疾地区旅行者的化学预防药物。因此，人们担心与甲氟喹化学预防相关的严重不良事件。本研究的目的是基于临床流行病学研究数据，评估是否能检测到甲氟喹严重不良事件的任何信号。
我们从两个已发表的数据集中提取了与甲氟喹化学预防相关的不良事件数据。在2×2列联表中呈现了神经精神事件和其他不良事件等不良事件的不成比例报告情况。应用报告比值比及相应的95%置信区间[CI]数据挖掘算法进行信号检测。当比值比估计值和相应95%CI的下限≥2时，安全信号被认为具有显著性。
纳入了两个涉及甲氟喹化学预防不良事件的数据集（一个来自已发表文章，一个来自Cochrane系统评价）进行分析。根据所选文章中的已发表数据，报告比值比为1.58，95%CI：1.49 - 1.68；根据所选Cochrane评价中的数据，报告比值比为1.195，95%CI：0.94 - 1.44。总体而言，在两个数据集中，95%CI下限的报告比值比均小于2。
基于现有数据，研究结果表明未检测到与甲氟喹相关的神经精神事件严重不良事件信号。需要进一步研究来证实这一点。
