Beyond abstinence and relapse: cluster analysis of drug-use patterns during treatment as an outcome measure for clinical trials.
Beyond abstinence and relapse: cluster analysis of drug-use patterns during treatment as an outcome measure for clinical trials.
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DOI：
10.1007/s00213-020-05618-5
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发表时间：
2020-11
影响因子：
3.4
通讯作者：
Preston KL
中科院分区：
文献类型：
--
作者：
Panlilio LV;Stull SW;Bertz JW;Burgess-Hull AJ;Kowalczyk WJ;Phillips KA;Epstein DH;Preston KL
许多正在接受阿片类药物使用障碍治疗的人在治疗期间继续使用药物。这种使用模式很少符合明确定义的禁欲和复发周期。对这些模式的系统识别和评估可以加强对临床试验的分析，并提供对药物使用的洞察。为了评估这种方法，我们分析了三个美沙酮治疗参与者应急管理的随机临床试验中阿片类药物和可卡因的使用模式。使用无监督机器学习技术分析药检结果序列，包括分类结果的等级聚类(即每周是否有样本呈阳性)和定量结果的K均值纵向聚类(即每周呈阳性的比例)。根据应急管理的效果，评估了作为实验结果的集群成员资格的敏感性。集群的外部验证基于对药物的渴望和其他物质使用障碍的症状。在每项临床试验中，我们确定了四种使用模式，可描述为阿片类药物使用、可卡因使用、双重使用(阿片类药物和可卡因)以及部分/完全戒断。不同的分组技术产生了基本相似的个体参与者分类，具有很强的机率一致性。应急管理增加了药物使用水平较低和药物使用障碍症状较少的群组的成员人数。聚类分析提供了比传统结果测量更具解释性和可操作性的个人水平的输出，为临床医生可以告诉患者新治疗的成功率这一问题提供了具体的答案。
Many people being treated for opioid use disorder continue to use drugs during treatment. This use occurs in patterns that rarely conform to well-defined cycles of abstinence and relapse. Systematic identification and evaluation of these patterns could enhance analysis of clinical trials and provide insight into drug use. To evaluate such an approach, we analyzed patterns of opioid and cocaine use from three randomized clinical trials of contingency management in methadone-treated participants. Sequences of drug-test results were analyzed with unsupervised machine-learning techniques, including hierarchical clustering of categorical results (i.e., whether any samples were positive during each week) and K-means longitudinal clustering of quantitative results (i.e., the proportion positive each week). The sensitivity of cluster membership as an experimental outcome was assessed based on the effects of contingency management. External validation of clusters was based on drug craving and other symptoms of substance use disorder. In each clinical trial, we identified four clusters of use patterns, which can be described as opioid use, cocaine use, dual use (opioid and cocaine), and partial/complete abstinence. Different clustering techniques produced substantially similar classifications of individual participants, with strong above-chance agreement. Contingency management increased membership in clusters with lower levels of drug use and fewer symptoms of substance use disorder. Cluster analysis provides person-level output that is more interpretable and actionable than traditional outcome measures, providing a concrete answer to the question of what clinicians can tell patients about the success rates of new treatments.
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DOI：
10.1111/add.12721
发表时间：
2014-12
期刊：
Addiction (Abingdon, England)
影响因子：
--
作者：
Jackson D;White IR;Mason D;Sutton S
通讯作者：
Sutton S
影响因子：
5
作者：
Genberg, Becky L.;Gange, Stephen J.;Mehta, Shruti H.
通讯作者：
Mehta, Shruti H.
影响因子：
2.3
作者：
Bart G
通讯作者：
Bart G
DOI：
10.1007/978-1-4614-7138-7_10
发表时间：
2013-01-01
期刊：
INTRODUCTION TO STATISTICAL LEARNING: WITH APPLICATIONS IN R
影响因子：
--
作者：
James, Gareth;Witten, Daniela;Tibshirani, Robert
通讯作者：
Tibshirani, Robert
影响因子：
3.9
作者：
Caudy, Michael S.;Tang, Liansheng;Taxman, Faye S.
通讯作者：
Taxman, Faye S.