Calculating prescription rates and addiction probabilities for the four most commonly prescribed opioids and evaluating their impact on addiction using compartment modelling
Calculating prescription rates and addiction probabilities for the four most commonly prescribed opioids and evaluating their impact on addiction using compartment modelling
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计算四种最常用阿片类药物的处方率和成瘾概率，并使用室模型评估其对成瘾的影响
DOI：
10.1093/imammb/dqab001
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Goldwyn, Eli E
中科院分区：
文献类型：
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作者：
Rivas, Samantha R;Tessner, Alex C;Goldwyn, Eli E
2016年，超过1100万美国人滥用处方阿片类药物。美国国家药物滥用研究所认为，阿片类药物危机是一种全国性的成瘾流行病，因为每年受到影响的人数不断增加。利用在传染病数学建模中开发的框架，我们创建并分析了一个由常微分方程系统组成的室状阿片类药物滥用模型。由于阿片类药物过量是由处方阿片类药物引起的，我们的模型包括四种最常用的阿片类药物的处方室，以及易感人群、成瘾人群和康复人群。虽然现有的研究主要集中在一般的药物滥用模型和具有一个处方隔间的阿片类药物模型上，但以前没有进行过比较最常用的阿片类药物在危机中所起作用的工作。通过将药物滥用和精神健康服务管理局（追踪使用或滥用四种阿片类药物之一的人的比例）的数据与疾病控制和预防中心（计算处方总数）的数据相结合，我们估计了四种最常用的阿片类药物的处方率和成瘾概率。此外，我们进行敏感性分析并重新分配处方，以确定哪种阿片类药物对流行病的影响最大。我们的研究结果表明，羟考酮处方最容易导致成瘾，对流行病规模的影响最大，而氢可酮处方的影响最小。
In 2016, more than 11 million Americans abused prescription opioids. The National Institute on Drug Abuse considers the opioid crisis a national addiction epidemic, as an increasing number of people are affected each year. Using the framework developed in mathematical modelling of infectious diseases, we create and analyse a compartmental opioid-abuse model consisting of a system of ordinary differential equations. Sinceof opioid overdoses are caused by prescription opioids, our model includes prescription compartments for the four most commonly prescribed opioids, as well as for the susceptible, addicted and recovered populations. While existing research has focused on drug abuse models in general and opioid models with one prescription compartment, no previous work has been done comparing the roles that the most commonly prescribed opioids have had on the crisis. By combining data from the Substance Abuse and Mental Health Services Administration (which tracked the proportion of people who used or misused one of the four individual opioids) with data from the Centers of Disease Control and Prevention (which counted the total number of prescriptions), we estimate prescription rates and probabilities of addiction for the four most commonly prescribed opioids. Additionally, we perform a sensitivity analysis and reallocate prescriptions to determine which opioid has the largest impact on the epidemic. Our results indicate that oxycodone prescriptions are both the most likely to lead to addiction and have the largest impact on the size of the epidemic, while hydrocodone prescriptions had the smallest impact.