Beyond abstinence and relapse: cluster analysis of drug-use patterns during treatment as an outcome measure for clinical
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ORIGINAL INVESTIGATION
Beyond abstinence and relapse: cluster analysis of drug-use patterns during treatment as an outcome measure for clinical trials Leigh V. Panlilio 1 & Samuel W. Stull 1 & Jeremiah W. Bertz 1 & Albert J. Burgess-Hull 1 & William J. Kowalczyk 1,2 & Karran A. Phillips 1 & David H. Epstein 1 & Kenzie L. Preston 1 Received: 1 April 2020 / Accepted: 21 July 2020 / Published online: 29 September 2020 # This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020
Abstract Rationale 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. Objectives 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. Methods 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. Results 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. Conclusions 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. Keywords Opioids . Cocaine . Substance use disorder . Contingency management . Cluster analysis . Treatment outcomes . Methadone
Introduction Agonist therapy for opioid-use disorder is one of the great success stories of behavioral medicine: it improves quality Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00213-020-05618-5) contains supplementary material, which is available to authorized users. * Leigh V. Panlilio [email protected] 1
Intramural Research Program, National Institute on Drug Abuse, 251 Bayview Blvd., Suite 200, Baltimore, MD 21224, USA
2
Department of Psychology, Hartwick College, Oneonta, NY 13820, USA
of life and decreases drug use
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