Center for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Center for Therapeutic Effectiveness Research, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Center for Pharmacoepidemiology Research and Training, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Biomed Pharmacother. 2020 Oct;130:110531. doi: 10.1016/j.biopha.2020.110531. Epub 2020 Jul 30.
Efforts to minimize harms from opioid drug interactions may be hampered by limited evidence on which drugs, when taken concomitantly with opioids, result in adverse clinical outcomes.
To identify signals of opioid drug interactions by identifying concomitant medications (precipitant drugs) taken with individual opioids (object drugs) that are associated with unintentional traumatic injury DESIGN: We conducted pharmacoepidemiologic screening of Optum Clinformatics Data Mart, identifying drug interaction signals by performing confounder-adjusted self-controlled case series studies for opioid + precipitant pairs and injury.
Beneficiaries of a major United States-based commercial health insurer during 2000-2015 PATIENTS: Persons aged 16-90 years co-dispensed an opioid and ≥1 precipitant drug(s), with an unintentional traumatic injury event during opioid therapy, as dictated by the case-only design EXPOSURE: Precipitant-exposed (vs. precipitant-unexposed) person-days during opioid therapy.
Emergency department or inpatient International Classification of Diseases discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to generate confounder adjusted rate ratios. We accounted for multiple estimation via semi-Bayes shrinkage.
We identified 25,019, 12,650, and 10,826 new users of hydrocodone, tramadol, and oxycodone who experienced an unintentional traumatic injury. Among 464, 376, and 389 hydrocodone-, tramadol-, and oxycodone-precipitant pairs examined, 20, 17, and 16 (i.e., 53 pairs, 34 unique precipitants) were positively associated with unintentional traumatic injury and deemed potential drug interaction signals. Adjusted rate ratios ranged from 1.23 (95 % confidence interval: 1.05-1.44) for hydrocodone + amoxicillin-clavulanate to 4.21 (1.88-9.42) for oxycodone + telmisartan. Twenty (37.7 %) of 53 signals are currently reported in a major drug interaction knowledgebase.
Potential for reverse causation, confounding by indication, and chance CONCLUSIONS: We identified previously undescribed and/or unappreciated signals of opioid drug interactions associated with unintentional traumatic injury. Subsequent etiologic studies should confirm (or refute) and elucidate these potential drug interactions.
由于缺乏关于哪些药物与阿片类药物同时使用会导致不良临床后果的证据，因此，减少阿片类药物药物相互作用造成的危害的努力可能会受到阻碍。
通过确定与个体阿片类药物（目标药物）同时使用的伴随药物（引发药物）来识别阿片类药物药物相互作用的信号，这些信号与非故意的创伤性损伤有关。
我们通过对 Optum Clinformatics Data Mart 进行药物流行病学筛查，针对阿片类药物+引发药物对和损伤进行混杂因素调整的自我对照病例系列研究，来识别药物相互作用信号。
一家主要的美国商业健康保险公司的受益人在 2000-2015 年期间
16-90 岁人群同时服用阿片类药物和≥1 种引发药物，并且在阿片类药物治疗期间发生非故意的创伤性损伤事件，这是由病例对照设计决定的
在阿片类药物治疗期间，暴露于引发药物（与未暴露于引发药物相比）的人-天。
根据国际疾病分类的急诊或住院出院诊断，发生非故意的创伤性损伤。我们使用条件泊松回归生成混杂因素调整后的率比。我们通过半贝叶斯收缩来考虑多次估计。
我们确定了 25019 名、12650 名和 10826 名新的氢可酮、曲马多和羟考酮使用者，他们经历了非故意的创伤性损伤。在 464 对、376 对和 389 对氢可酮、曲马多和羟考酮引发药物对中，有 20 对（34 种独特的引发剂）、17 对（29 种独特的引发剂）和 16 对（即 53 对，34 种独特的引发剂）与非故意的创伤性损伤呈正相关，被认为是潜在的药物相互作用信号。调整后的率比范围从氢可酮+阿莫西林克拉维酸的 1.23（95%置信区间：1.05-1.44）到羟考酮+替米沙坦的 4.21（1.88-9.42）。53 个信号中的 20 个（37.7%）目前在一个主要的药物相互作用知识库中报告。
存在反向因果关系、指示性混杂和偶然性
我们发现了以前未描述和/或未被认识到的与非故意的创伤性损伤相关的阿片类药物药物相互作用的信号。随后的病因学研究应该确认（或反驳）并阐明这些潜在的药物相互作用。
