Incremental validity of estimated cannabis grams as a predictor of problems and cannabinoid biomarkers: Evidence from a clinical trial. (1st January 2018)

• Record Type: Journal Article
• Authors: Tomko, Rachel L.; Baker, Nathaniel L.; McClure, Erin A.; Sonne, Susan C.; McRae-Clark, Aimee L.; Sherman, Brian J.; Gray, Kevin M.
• Is Part Of: Drug and alcohol dependence. Volume 182(2018)
• Page Start: 1
• Page End: 7
• Publication Date: 2018-01-01
• Subjects: Cannabis -- Marijuana -- Timeline Followback -- Quantitative cannabinoid level; Drug abuse -- Periodicals; Alcoholism -- Periodicals; 616.86
• DOI: 10.1016/j.drugalcdep.2017.09.035
• Languages: English
• ISSNs: 0376-8716

Abstract

Highlights: Cannabis use is difficult to quantify due to variability in products/modes of use. A method for estimating grams of cannabis use has been previously developed. The method predicts outcomes beyond simpler frequency counts of cannabis use alone. This method may be refined further, including estimates of cannabinoid strength. Abstract: Background: Quantifying cannabis use is complex due to a lack of a standardized packaging system that contains specified amounts of constituents. A laboratory procedure has been developed for estimating physical quantity of cannabis use by utilizing a surrogate substance to represent cannabis, and weighing the amount of the surrogate to determine typical use in grams. Method: This secondary analysis utilized data from a multi-site, randomized, controlled pharmacological trial for adult cannabis use disorder (N = 300), sponsored by the National Drug Abuse Treatment Clinical Trials Network, to test the incremental validity of this procedure. In conjunction with the Timeline Followback, this physical scale-based procedure was used to determine whether average grams per cannabis administration predicted urine cannabinoid levels (11-nor-9-carboxy-Δ9-tetrahydrocannabinol) and problems due to use, after accounting for self-reported number of days used (in the past 30 days) and number of administrations per day in a 12-week clinical trial for cannabis use disorder. Results: Likelihood ratio tests suggest that model fit was significantly improved when grams per administration and relevant interactions were included in the model predicting urine cannabinoid level (X 2 = 98.3; p < 0.05) and in the model predicting problems due to cannabis use (X 2 = 6.4; p < 0.05), relative to a model that contained only simpler measures of quantity and frequency. Conclusions: This study provides support for the use of a scale-based method for quantifying cannabis use in grams. This methodology may be useful when precise quantification is necessary (e.g., measuring reduction in use in a clinical trial).