Pauly V, Lapeyre-Mestre M, Braunstein D, Rueter M, Thirion X, Jouanjus E, Micallef J
Laboratoire de Santé Publique EA 3279, Faculté de Médecine Centre d'Evaluation de la Pharmacodépendance-Addictovigilance (CEIP-A) de Marseille (PACA-Corse) Associé, Aix Marseille Université, 27 Boulevard Jean Moulin, 13005, Marseille, France.
Eur J Clin Pharmacol. 2015 Feb;71(2):229-36. doi: 10.1007/s00228-014-1783-x. Epub 2014 Nov 20.
Prescription drug abuse and dependence is a widespread phenomenon in many countries. The use of disproportionality measures in drug abuse surveillance is rarely performed.
The aim of this study is to determine the occurrence of signals of abuse and dependence for different psychoactive drugs in real-life settings.
Disproportionality analysis was realised from a database specifically constructed for the monitoring of drug abuse and dependence. This database provides information on approximately 5000 patients and 8000 consumption modalities for more than 100 distinct psychoactive medications for 2010 and 2011. Proportional reporting ratio (PRR) was computed in two population groups: subjects under an opiate maintenance treatment (OMT) versus those not under OMT, and focused on four types of behaviours: abuse and dependence, illegal acquisition, diverted route of administration and concomitant alcohol use.
Among the 100 psychoactive drugs for which a signal could be detected, those presenting the highest signals were the following: flunitrazepam, clonazepam, methylphenidate, ketamine, morphine sulfate, codeine and buprenorphine.
The present study shows an innovative application of disproportionality measures for drug abuse monitoring based on two cross-national, annual studies. The disproportionality analysis provided the opportunity to reveal and compare the magnitude of signals between 100 psychoactive drugs. This approach helps to compare the magnitude of abuse and dependence behaviours for a large number of drugs, and allows prioritizing actions in a context where such events are usually underreported.
处方药滥用和依赖在许多国家是一种普遍现象。在药物滥用监测中很少使用不成比例性测量方法。
本研究旨在确定在现实生活环境中不同精神活性药物的滥用和依赖信号的发生情况。
从专门构建用于监测药物滥用和依赖的数据库中进行不成比例性分析。该数据库提供了2010年和2011年100多种不同精神活性药物的约5000名患者和8000种消费模式的信息。在两个人群组中计算比例报告率（PRR）：接受阿片类维持治疗（OMT）的受试者与未接受OMT的受试者，并关注四种行为类型：滥用和依赖、非法获取、给药途径转移和同时饮酒。
在能够检测到信号的100种精神活性药物中，信号最强的药物如下：氟硝西泮、氯硝西泮、哌醋甲酯、氯胺酮、硫酸吗啡、可待因和丁丙诺啡。
本研究展示了基于两项跨国年度研究的不成比例性测量方法在药物滥用监测中的创新应用。不成比例性分析提供了揭示和比较100种精神活性药物之间信号强度的机会。这种方法有助于比较大量药物的滥用和依赖行为的强度，并在这类事件通常报告不足的情况下确定行动的优先级。
