Coutinho Anna D, Gandhi Kavita, Fuldeore Rupali M, Landsman-Blumberg Pamela B, Gandhi Sanjay
Xcenda LLC, Palm Harbor, Florida.
Director, Global HEOR, Teva Pharmaceuticals, Frazer, Pennsylvania.
J Opioid Manag. 2018 Mar/Apr;14(2):131-141. doi: 10.5055/jom.2018.0440.
Identify opioid abuse risk factors among chronic noncancer pain (CNCP) patients receiving long-term opioid therapy and assess healthcare resource use (HRU) among patients at elevated abuse risk.
Data were obtained from an integrated administrative claims database. Classification and Regression Tree (CART) analysis identified risk factors potentially predictive of opioid abuse, which were used to classify the overall population into cohorts defined by levels of abuse risk. Multivariable logistic regression compared HRU across risk cohorts.
Retrospective cohort study.
PATIENTS, PARTICIPANTS: 21,072 patients aged ≥18 years diagnosed with ≥1 of 5 types of CNCP and a prescription for Schedule II or III/IV opioid medication used long-term (≥90 days).
(1) Opioid abuse risk factors; (2) HRU differences between risk cohorts.
CART analysis identified four groups at elevated opioid abuse risk defined by three factors (age, daily opioid dose, and total days' supply of opioids); sensitivity: 70.3 percent, specificity: 74.1 percent, and positive predictive value: 5.6 percent. The analysis results were used to classify patients into low-risk (72.5 percent), at-risk (25.4 percent), and opioid-abuser (2.2 percent) cohorts. In multivariable analysis, emergency department (ED) use was higher among at-risk vs low-risk patients (odds ratio [OR]: 1.14; p<0.05); hospitalization and ED visits were higher for opioid-abusers vs low-risk patients (OR: 2.33 and 2.14, respectively; p<0.05).
This study identifies a subpopulation of CNCP patients at risk of opioid abuse. However, limited sensitivity and specificity of criteria defining this subpopulation reinforce the importance of physician discretion in patient-level treatment decisions.
确定接受长期阿片类药物治疗的慢性非癌性疼痛（CNCP）患者中的阿片类药物滥用风险因素，并评估滥用风险较高患者的医疗资源使用情况（HRU）。
数据来自一个综合行政索赔数据库。分类与回归树（CART）分析确定了可能预测阿片类药物滥用的风险因素，这些因素被用于将总体人群分为由滥用风险水平定义的队列。多变量逻辑回归比较了不同风险队列的医疗资源使用情况。
回顾性队列研究。
患者、参与者：21072名年龄≥18岁的患者，被诊断患有5种类型的CNCP中的至少1种，并长期（≥90天）开具了II类或III/IV类阿片类药物处方。
（1）阿片类药物滥用风险因素；（2）风险队列之间的医疗资源使用差异。
CART分析确定了由三个因素（年龄、每日阿片类药物剂量和阿片类药物的总供应天数）定义的四个阿片类药物滥用风险较高的组；敏感性：70.3%，特异性：74.1%，阳性预测值：5.6%。分析结果被用于将患者分为低风险（72.5%）、有风险（25.4%）和阿片类药物滥用者（2.2%）队列。在多变量分析中，有风险的患者与低风险患者相比，急诊室（ED）使用更高（优势比[OR]：1.14；p<0.05）；阿片类药物滥用者与低风险患者相比，住院和急诊室就诊更高（OR分别为2.33和2.14；p<0.05）。
本研究确定了有阿片类药物滥用风险的CNCP患者亚群。然而，定义该亚群的标准敏感性和特异性有限，这强化了医生在患者层面治疗决策中酌情权的重要性。
