Evaluation of heterogeneity in pharmacotherapy trials for drug dependence: a Bayesian approach.
OBJECTIVE
Difficulty identifying effective pharmacotherapies for cocaine dependence has led to suggestions that subgroup differences may account for some of the heterogeneity in treatment response. Well-attested methodological difficulties associated with these analyses recommend the use of Bayesian statistical reasoning for evaluation of salient interaction effects.


METHODS
A secondary data analysis of a previously published, double-blind, randomized controlled trial examines the interaction of decision-making, as measured by the Iowa Gambling Task, and citalopram in increasing longest sustained abstinence from cocaine use.


RESULTS
Bayesian analysis indicated that there was a 99% chance that improved decision-making enhances response to citalopram. Given the strong positive nature of this finding, a formal, quantitative Bayesian approach to evaluate the result from the perspective of a skeptic was applied.


CONCLUSIONS
Bayesian statistical reasoning provides a formal means of weighing evidence for the presence of an interaction in scenarios where conventional, Frequentist analyses may be less informative. [Supplementary materials are available for this article. Go to the publisher's online edition of The American Journal of Drug and Alcohol Abuse for the following free supplemental resource: Appendix 1].
Green
C E
CE
Center for Clinical Research & Evidence-Based Medicine, University of Texas, Houston, 77030, USA. Charles.Green@uth.tmc.edu
Moeller
F G
FG
Schmitz
J M
JM
Lucke
J F
JF
Lane
S D
SD
Swann
A C
AC
Lasky
R E
RE
Carbonari
J P
JP