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美国阿片类药物不良药物事件的差异。

Variation in adverse drug events of opioids in the United States.

作者信息

Liu Edward Y, McCall Kenneth L, Piper Brian J

机构信息

Department of Medical Education, Geisinger Commonwealth School of Medicine, Scranton, PA, United States.

Department of Pharmacy Practice, Binghamton University, Binghamton, NY, United States.

出版信息

Front Pharmacol. 2023 Mar 24;14:1163976. doi: 10.3389/fphar.2023.1163976. eCollection 2023.

DOI:10.3389/fphar.2023.1163976
PMID:37033633
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10079914/
Abstract

The United States (US) ranks high, nationally, in opioid consumption. The ongoing increase in the misuse and mortality amid the opioid epidemic has been contributing to its rising cost. The worsening health and economic impact of opioid use disorder in the US warrants further attention. We, therefore, assessed commonly prescribed opioids to determine the opioids that were over-represented versus under-represented for adverse drug events (ADEs) to better understand their distribution patterns using the Food and Drug Administration's Adverse Event Reporting System (FAERS) while correcting for distribution using the Drug Enforcement Administration's Automation of Reports and Consolidated Orders System (ARCOS). Comparing the ratio of the percentage of adverse drug events as reported by the FAERS relative to the percentage of distribution as reported by the ARCOS database is a novel approach to evaluate post-marketing safety surveillance and may inform healthcare policies and providers to better regulate the use of these opioids. We analyzed the adverse events for 11 prescription opioids, when correcting for distribution, and their ratios for three periods, 2006-2010, 2011-2016, and 2017-2021, in the US. The opioids include buprenorphine, codeine, fentanyl, hydrocodone, hydromorphone, meperidine, methadone, morphine, oxycodone, oxymorphone, and tapentadol. Oral morphine milligram equivalents (MMEs) were calculated by conversions relative to morphine. The relative ADEs of the selected opioids, opioid distributions, and ADEs relative to distribution ratios were analyzed for the 11 opioids. Oxycodone, fentanyl, and morphine accounted for over half of the total number of ADEs ( = 667,969), while meperidine accounted for less than 1%. Opioid distributions were relatively constant over time, with methadone repeatedly accounting for the largest proportions. Many ADE-to-opioid distribution ratios increased over time, with meperidine (60.6), oxymorphone (11.1), tapentadol (10.3), and hydromorphone (7.9) being the most over-represented for ADEs in the most recent period. Methadone was under-represented (<0.20) in all the three periods. The use of the FAERS with the ARCOS provides insights into dynamic changes in ADEs of the selected opioids in the US. There is further need to monitor and address the ADEs of these drugs.

摘要

美国在全国范围内的阿片类药物消费量很高。阿片类药物流行期间滥用情况和死亡率的持续上升导致成本不断增加。美国阿片类药物使用障碍对健康和经济造成的影响日益恶化,值得进一步关注。因此,我们评估了常用的阿片类药物,以确定在药物不良事件(ADEs)中占比过高或过低的阿片类药物,以便利用美国食品药品监督管理局的不良事件报告系统(FAERS)更好地了解它们的分布模式,同时使用美国缉毒局的报告自动化和综合命令系统(ARCOS)对分布情况进行校正。比较FAERS报告的药物不良事件百分比与ARCOS数据库报告的分布百分比的比率,是一种评估上市后安全监测的新方法,可能会为医疗政策和医疗服务提供者提供信息,以便更好地规范这些阿片类药物的使用。我们分析了美国11种处方阿片类药物在校正分布后的不良事件及其在2006 - 2010年、2011 - 2016年和2017 - 2021年三个时期的比率。这些阿片类药物包括丁丙诺啡、可待因、芬太尼、氢可酮、氢吗啡酮、哌替啶、美沙酮、吗啡、羟考酮、奥施康定和曲马多。口服吗啡毫克当量(MMEs)通过相对于吗啡的换算来计算。分析了11种阿片类药物的选定阿片类药物的相对ADEs、阿片类药物分布以及ADEs相对于分布的比率。羟考酮、芬太尼和吗啡占ADEs总数(= 667,969)的一半以上,而哌替啶占比不到1%。阿片类药物的分布随时间相对稳定,美沙酮的占比一直最大。许多ADE与阿片类药物的分布比率随时间增加,在最近一个时期,哌替啶(60.6)、奥施康定(11.1)、曲马多(10.3)和氢吗啡酮(7.9)在ADEs中占比过高最为明显。美沙酮在所有三个时期的占比都过低(<0.20)。将FAERS与ARCOS结合使用,可以深入了解美国选定阿片类药物ADEs的动态变化。进一步需要监测和处理这些药物的ADEs。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81af/10079914/d58a4bccb87f/fphar-14-1163976-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81af/10079914/61b067d31fb0/fphar-14-1163976-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81af/10079914/739e79391d58/fphar-14-1163976-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81af/10079914/d58a4bccb87f/fphar-14-1163976-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81af/10079914/61b067d31fb0/fphar-14-1163976-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81af/10079914/739e79391d58/fphar-14-1163976-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81af/10079914/d58a4bccb87f/fphar-14-1163976-g003.jpg

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