Methadone and buprenorphine have pharmacologic properties that are concerning for a high risk of drug–drug interactions (DDIs). We performed high-throughput screening for clinically relevant DDIs with methadone or buprenorphine by combining pharmacoepidemiologic and pharmacokinetic approaches. We conducted pharmacoepidemiologic screening via a series of self-controlled case series studies (SCCS) in Optum claims data from 2000 to 2019. We included persons 18 years or older who experienced an outcome of interest during target drug treatment. Exposures were all overlapping medications (i.e., the candidate precipitants) during target drug treatment. Outcomes were opioid overdose, non-overdose adverse effects, and cardiac arrest. We used conditional Poisson regression to calculate rate ratios, accounting for multiple comparisons with semi-Bayes shrinkage. We explored the impact of key study design choices in analyses that varied the exposure definitions of the target drugs and the candidate precipitant drugs. Pharmacokinetic screening was conducted by incorporating published data on CYP enzyme metabolism into an equation-based static model. In SCCS analysis, 1,432 events were included from 248,069 new users of methadone or buprenorphine. In the primary analysis, statistically significant DDIs included gabapentinoids with either methadone or buprenorphine; baclofen with methadone; and benzodiazepines with methadone. In sensitivity analysis, additional statistically significant DDIs included methocarbamol, quetiapine, or simvastatin with methadone. Pharmacokinetic screening identified two moderate-to-strong potential DDIs (clonidine and fluconazole with buprenorphine). The combination of clonidine and buprenorphine was also associated with a significantly increased risk of opioid overdose in pharmacoepidemiologic screening. These DDI signals may be the most important targets for future confirmation studies.

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确定与美沙酮和丁丙诺啡的临床相关药物相互作用：信号检测的转化方法

美沙酮和丁丙诺啡的药理学特性与药物相互作用 (DDI) 的高风险有关。我们通过结合药物流行病学和药代动力学方法，对美沙酮或丁丙诺啡的临床相关 DDI 进行了高通量筛查。我们通过一系列自我对照病例系列研究 (SCCS) 在 2000 年至 2019 年的 Optum 索赔数据中进行了药物流行病学筛查。我们纳入了 18 岁或以上的人，他们在靶向药物治疗期间经历了感兴趣的结果。在靶向药物治疗期间，暴露都是重叠的药物（即候选沉淀剂）。结果是阿片类药物过量、非过量不良反应和心脏骤停。我们使用条件泊松回归来计算比率，考虑与半贝叶斯收缩的多重比较。我们探讨了关键研究设计选择在分析中的影响，这些分析改变了目标药物和候选沉淀药物的暴露定义。药代动力学筛选是通过将已发表的 CYP 酶代谢数据纳入基于方程的静态模型中进行的。在 SCCS 分析中，包括来自 248,069 名美沙酮或丁丙诺啡新使用者的 1,432 起事件。在初步分析中，具有统计学意义的 DDI 包括加巴喷丁类药物和美沙酮或丁丙诺啡；巴氯芬与美沙酮；和苯二氮卓类药物与美沙酮。在敏感性分析中，其他具有统计学意义的 DDI 包括美索巴莫、喹硫平或辛伐他汀与美沙酮。药代动力学筛选确定了两种中度至强烈的潜在 DDI（可乐定和氟康唑与丁丙诺啡）。在药物流行病学筛查中，可乐定和丁丙诺啡的组合也与阿片类药物过量风险显着增加有关。这些 DDI 信号可能是未来确认研究的最重要目标。