Evaluation of Heterogeneity in Pharmacotherapy Trials for Drug Dependence: A Bayesian Approach Export

@article{citeulike:4230658, abstract = {<i>Aims</i>: 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. <i>Methods</i>: 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. <i>Results</i>: 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. <i>Conclusions</i>: 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 <i>The American Journal of Drug and Alcohol Abuse</i> for the following free supplemental resource: Appendix 1]}, author = {Green, C. E. and Moeller, F. G. and Schmitz, J. M. and Lucke, J. F. and Lane, S. D. and Swann, A. C. and Lasky, R. E. and Carbonari, J. P.}, citeulike-article-id = {4230658}, citeulike-linkout-0 = {http://dx.doi.org/10.1080/00952990802647503}, doi = {10.1080/00952990802647503}, journal = {The American Journal of Drug and Alcohol Abuse}, keywords = {addiction, cocaine, decision-making}, number = {2}, pages = {95--102}, posted-at = {2009-03-27 14:05:47}, priority = {4}, publisher = {Informa Healthcare}, title = {Evaluation of Heterogeneity in Pharmacotherapy Trials for Drug Dependence: A Bayesian Approach}, url = {http://dx.doi.org/10.1080/00952990802647503}, volume = {35}, year = {2009} }

TY - JOUR ID - citeulike:4230658 L3 - citeulike-article-id:4230658 N2 - <i>Aims</i>: 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. <i>Methods</i>: 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. <i>Results</i>: 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. <i>Conclusions</i>: 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 <i>The American Journal of Drug and Alcohol Abuse</i> for the following free supplemental resource: Appendix 1] IS - 2 JF - The American Journal of Drug and Alcohol Abuse EP - 102 TI - Evaluation of Heterogeneity in Pharmacotherapy Trials for Drug Dependence: A Bayesian Approach PB - Informa Healthcare VL - 35 SP - 95 KW - addiction KW - cocaine KW - decision-making AU - Green, CE AU - Moeller, FG AU - Schmitz, JM AU - Lucke, JF AU - Lane, SD AU - Swann, AC AU - Lasky, RE AU - Carbonari, JP PY - 2009/// UR - http://dx.doi.org/10.1080/00952990802647503 ER -