title: Assessing drug use during follow-up: direct comparison of candidate outcome definitions in pooled analyses of addiction treatment studies.
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.
  
  
  OBJECTIVE
  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.
  
  
  CONCLUSIONS
  Despite strong associations between candidate measures, we found some important differences in results.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Division of Biostatistics and Epidemiology, Department of Medicine, Medical University of South Carolina, Charleston, 29425, USA. korte@musc.edu
authors.forename: Jeffrey E
authors.initials: JE
authors.lastname: Korte
authors.forename: Kathryn M
authors.initials: KM
authors.lastname: Magruder
authors.forename: Codruta C
authors.initials: CC
authors.lastname: Chiuzan
authors.forename: Sarah L
authors.initials: SL
authors.lastname: Logan
authors.forename: Therese
authors.initials: T
authors.lastname: Killeen
authors.forename: Dipankar
authors.initials: D
authors.lastname: Bandyopadhyay
authors.forename: Kathleen T
authors.initials: KT
authors.lastname: Brady
mesh_terms: D002986:Clinical Trials as Topic / Q000379:methods*; D016000:Cluster Analysis; D005006:Ethnicity; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D054577:National Institute on Drug Abuse (U.S.); D017063:Outcome Assessment, Health Care; D012737:Sex Factors; D015813:Substance Abuse Detection / Q000379:methods*; D019966:Substance-Related Disorders / Q000534:rehabilitation*; D013997:Time Factors; D014481:United States