Archive for February, 2012

Selecting Appropriate Outcome Measures in Drug Dependence Treatment Research

February 29, 2012

Addiction coverThe new issue of Addiction (vol 107(4)) features two articles (one by PN Node Lead Investigator Dennis Donovan) about a NIDA-sponsored meeting of a panel of experts (including CTN researchers and clinicians) who sat down together in 2011 to attempt to come up with recommendations for common primary and secondary outcome measures for drug dependence treatment clinical trials:

Donovan DM et al. Primary outcome indices in illicit drug dependence treatment research: Systematic approach to selection and measurement of drug use end-points in clinical trials. Addiction 2012;107(4):694-708.

Tiffany ST et al. Beyond drug use: A systematic consideration of other outcomes in evaluations of treatments for substance use disorders. Addiction 2012;107(4):709-718.

After the two articles, a series of commentary pieces, written by Frances Del Boca, Jack Darkes, Ambros Uchtenhagen, and Gerhard Buhringer, agreed that drug use by itself is an inadequate metric for gauging the impact of treatment, but had additional suggestions for outcome domains as well as questions about some of the recommendations made in the papers. Both Dr. Donovan and Dr. Tiffany respond.


Find all three pieces in the CTN Dissemination Library!

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Approaches to Missing Data in Substance Abuse Treatment Research

February 21, 2012

ECP CoverThis article, currently in-press at Experimental and Clinical Psychopharmacology, was written by Sterling McPherson, Celestina Barbosa-Leiker, G. Leonard Burns, Donelle Howell, and John Roll, all from Washington State University in the Pacific Northwest Node.

It is an ancillary study that used data from protocol CTN-0003 (buprenorphine taper) to compare two common procedures for the treatment of missing information (listwise deletion and positive urine analysis (UA) imputation) to a possible alternative, multiple imputation (MI) procedure.

The analysis determined that although the MI procedure resulted in a significant effect, the effect size was meaningfully smaller and the standard errors meaningfully larger when compared to the positive UA procedure. This study demonstrates that the researcher can obtain markedly different results depending on how missing data are handled.

Conclusions: Missing data theory suggests that listwise deletion and single imputation procedures should not be used to account for missing information, and that MI has advantages with respect to internal and external validity when the assumption of missing at random can be reasonably supported.

Citation: McPherson S, Barbosa-Leiker C, Burns GL, Howell D, Roll JM. Missing Data in Substance Abuse Treatment Research: Current Methods and Modern Approaches. Experimental and Clinical Psychopharmacology 2012 (in press).


Find it in the CTN Dissemination Library!