Differentiating new cannabis use from residual urinary cannabinoid excretion in chronic, daily cannabis users

Authors

  • Eugene W. Schwilke,

    1. Chemistry and Drug Metabolism, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Biomedical Research Center, Baltimore, MD, USA
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  • Rod G. Gullberg,

    1. Washington State Patrol, Breath Test Section, Seattle, WA, USA
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  • William D. Darwin,

    1. Chemistry and Drug Metabolism, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Biomedical Research Center, Baltimore, MD, USA
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  • C. Nora Chiang,

    1. Division of Pharmacotherapies and Medical Consequences of Drug Abuse, National Institute on Drug Abuse, National Institutes of Health, Rockville, MD, USA
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  • Jean Lud Cadet,

    1. Molecular Neuropsychiatry, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Biomedical Research Center, Baltimore, MD, USA
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  • David A. Gorelick,

    1. Office of the Scientific Director, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Biomedical Research Center, Baltimore, MD, USA
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  • Harrison G. Pope,

    1. McLean Hospital, Harvard University, Belmont, MA, USA
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  • Marilyn A. Huestis

    Corresponding author
    1. Chemistry and Drug Metabolism, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Biomedical Research Center, Baltimore, MD, USA
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Marilyn A. Huestis, Chemistry and Drug Metabolism, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, 251 Bayview Boulevard, Suite 200, Room 05A-721, Baltimore, MD 21146, USA. E-mail: mhuestis@intra.nida.nih.gov

ABSTRACT

Aims  To develop and validate empirically a mathematical model for identifying new cannabis use in chronic, daily cannabis smokers.

Design  Models were based on urinary creatinine-normalized (CN) cannabinoid excretion in chronic cannabis smokers.

Setting  For model development, participants resided on a secure research unit for 30 days. For model validation, participants were abstinent with daily observed urine specimens for 28 days.

Participants  A total of 48 (model development) and 67 (model validation) daily cannabis smokers were recruited.

Measurements  All voided urine was collected and analyzed for 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THCCOOH) by gas chromatography-mass spectrometry (GCMS; limit of quantification 2.5 ng/ml) and creatinine (mg/ml). Urine THCCOOH was normalized to creatinine, yielding ng/mg CN-THCCOOH concentrations. Urine concentration ratios were determined from 123 513 specimen pairs collected 2–30 days apart.

Findings  A mono-exponential model (with two parameters, initial urine specimen CN-THCCOOH concentration and time between specimens), based on the Marquardt–Levenberg algorithm, provided a reasonable data fit. Prediction intervals with varying probability levels (80, 90, 95, 99%) provide upper ratio limits for each urine specimen pair. Ratios above these limits suggest cannabis re-use. Disproportionate numbers of ratios were higher than expected for some participants, prompting development of two additional rules that avoid misidentification of re-use in participants with unusual CN-THCCOOH excretion patterns.

Conclusions  For the first time, a validated model is available to aid in the differentiation of new cannabis use from residual creatinine-normalized 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (CN-THCCOOH) excretion in chronic, daily cannabis users. These models are valuable for clinicians, toxicologists and drug treatment staff and work-place, military and criminal justice drug-testing programs.

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