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Research Articles

Assessing Drug Use during Follow-Up: Direct Comparison of Candidate Outcome Definitions in Pooled Analyses of Addiction Treatment Studies

, M.S.P.H., Ph.D., , M.P.H., Ph.D., , M.S., , M.S., , Ph.D., , Ph.D. & , M.D., Ph.D. show all
Pages 358-366 | Published online: 22 Aug 2011
 

Abstract

Background: Selection of appropriate outcome measures is important for clinical studies of drug addiction treatment. Researchers use various methods for collecting drug use outcomes and must consider substances to be included in a urine drug screen (UDS); accuracy of self-report; use of various instruments and procedures for collecting self-reported drug use; and timing of outcome assessments. Objectives: We sought to define a set of candidate measures to (1) assess their intercorrelation and (2) identify any differences in results. Methods: Data were combined from completed protocols in the National Institute on Drug Abuse Clinical Trials Network (CTN), with a total of 1897 participants. We defined nine outcome measures based on UDS, self-report, or a combination. Multivariable, multilevel generalized estimating equation models were used to assess subgroup differences in intervention success, controlling for baseline differences and accounting for clustering by CTN protocols. Results: There were high correlations among all candidate outcomes. All outcomes showed consistent overall results with no significant intervention impact on drug use during follow-up. However, with most UDS variables, but not with self-report or “corrected self-report,” we observed a significant gender–ethnicity interaction with benefit shown in African American women, White women, and Hispanic men. Conclusion: Despite strong associations between candidate measures, we found some important differences in results. Scientific Significance: In this study, we demonstrated the potential utility and impact of combining UDS and self-report data for drug use assessment. Our results suggest possible differences in intervention efficacy by gender and ethnicity, but highlight the need to cautiously interpret observed interactions.

ACKNOWLEDGMENTS

This work was supported by grant 5 U10 DA013727.

Declaration of Interest

Kathleen Brady lists the following: Consultant: Pfizer, Eli Lilly, Abbott, GlaxoSmithKline, Forest, Ovation, Marinus, Novartis; Speakers’ Bureau: Pfizer, Eli Lilly, Abbott, GlaxoSmithKline, Forest; Research Support: Abbott, GlaxoSmithKline, Forest; Scientific Advisory Board: Embera NeuroTherapeutics; Independent Contractor: Medscape; Investigator: Titan Pharmaceuticals. The authors report no other conflicts of interest. The authors alone are responsible for the content and writing of the article.

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