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美国工作年龄成年人向新发慢性阿片类药物治疗转变的预测因素

Predictors of Transitioning to Incident Chronic Opioid Therapy Among Working-Age Adults in the United States.

作者信息

Thornton J Douglas, Dwibedi Nilanjana, Scott Virginia, Ponte Charles D, Ziedonis Douglas, Sambamoorthi Nethra, Sambamoorthi Usha

机构信息

Assistant Professor, College of Pharmacy, Department of Pharmaceutical Health Outcomes and Policy, University of Houston, TX.

Assistant Professor, School of Pharmacy, Department of Pharmaceutical Systems and Policy, West Virginia University, Morgantown.

出版信息

Am Health Drug Benefits. 2018 Feb;11(1):12-21.

Abstract

BACKGROUND

Opioids have been prescribed and used for chronic noncancer pain at prolific rates in the United States during the past 2 decades. Patients who transition to incident chronic opioid therapy are at increased risk for significant negative health consequences, including cardiovascular risk, endocrine disorders, opioid use disorder, and death.

OBJECTIVE

To identify the leading predictors associated with transitioning to incident chronic opioid therapy among working-age adults without cancer.

METHOD

This retrospective observational cohort study is based on medical and pharmacy claims of a nationally representative sample of adults enrolled in commercial health insurance plans. Standard parametric (logistic regressions) and nonparametric methods based on a decision tree were used for prediction. To facilitate comparison with the available published literature, we also present adjusted odds ratios (AORs) and 95% confidence intervals (CIs). The 10% random sample of 491,442 patients included in the study who were working-age adults (age, 28-63 years) were insured in a commercial health plan, did not have cancer, and initiated opioid therapy between January 2007 and May 2015. Transition to incident chronic opioid therapy was defined as having claims for at least a 90-day supply of opioids within 120 days after the index date (ie, initiation of opioid therapy). Predictive models used for the analysis comprised a comprehensive list of factors available in the claims data, including opioid regimen characteristics, pain conditions, physical and mental health conditions, concomitant medications use (ie, benzodiazepine, stimulants, nonopioid analgesics, and polypharmacy), patient characteristics, and health insurance type.

RESULTS

In our sample, the transition to incident chronic opioid therapy was 1.3% and pain-specific diagnoses were documented for only one-third (31.7%) of patients. The 4 leading predictors of chronic opioid therapy were opioid duration of action (AOR, 12.28; 95% CI, 8.06-18.72), the parent opioid compound (eg, tramadol vs codeine; AOR, 7.26; 95% CI, 5.20-10.13), the presence of conditions that are very likely to cause chronic pain (AOR, 5.47; 95% CI, 3.89-7.68), and drug use disorders (AOR, 4.02; 95% CI, 2.53-6.40).

CONCLUSION

The initial opioid regimen's characteristics are powerful predictors of chronic opioid therapy. Predictive algorithms created from readily available claims data can be used to develop real-time predictions of the future risk for a patient's transition to chronic opioid use.

摘要

背景

在过去20年里,美国大量开具并使用阿片类药物治疗慢性非癌性疼痛。转为接受阿片类药物长期治疗的患者出现严重负面健康后果的风险增加,包括心血管疾病风险、内分泌紊乱、阿片类药物使用障碍和死亡。

目的

确定无癌症的工作年龄成年人转为接受阿片类药物长期治疗的主要预测因素。

方法

这项回顾性观察队列研究基于参加商业健康保险计划的具有全国代表性的成年人群体的医疗和药房理赔数据。使用基于决策树的标准参数方法(逻辑回归)和非参数方法进行预测。为便于与现有已发表文献进行比较,我们还给出了调整后的比值比(AOR)和95%置信区间(CI)。该研究纳入的491442名患者的10%随机样本为工作年龄成年人(年龄28 - 63岁),他们参加了商业健康保险计划,无癌症,且在2007年1月至2015年5月期间开始接受阿片类药物治疗。转为接受阿片类药物长期治疗的定义为在索引日期(即开始阿片类药物治疗)后的120天内有至少90天阿片类药物供应的理赔记录。用于分析的预测模型包括理赔数据中可用的一系列综合因素,包括阿片类药物治疗方案特征、疼痛状况、身心健康状况、合并用药情况(即苯二氮䓬类药物、兴奋剂、非阿片类镇痛药和多种药物联用)、患者特征和健康保险类型。

结果

在我们的样本中,转为接受阿片类药物长期治疗的比例为1.3%,仅三分之一(31.7%)的患者有特定疼痛诊断记录。阿片类药物长期治疗的4个主要预测因素为阿片类药物作用持续时间(AOR,12.28;95% CI,8.06 - 18.72)、阿片类母体化合物(如曲马多与可待因;AOR,7.26;95% CI,5.20 - 10.13)、极有可能导致慢性疼痛的疾病的存在(AOR,5.47;95% CI,3.89 - 7.68)以及药物使用障碍(AOR,4.02;95% CI,2.53 - 6.40)。

结论

初始阿片类药物治疗方案的特征是阿片类药物长期治疗的有力预测因素。利用现成的理赔数据创建的预测算法可用于对患者转为长期使用阿片类药物的未来风险进行实时预测。

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