Advertisement

Measuring Within-Individual Cannabis Reduction in Clinical Trials: a Review of the Methodological Challenges

  • Rachel L. TomkoEmail author
  • Kevin M. Gray
  • Marilyn A. Huestis
  • Lindsay M. Squeglia
  • Nathaniel L. Baker
  • Erin A. McClure
Cannabis (A McRae-Clark B Sherman, Section Editors)
Part of the following topical collections:
  1. Topical Collection on Cannabis

Abstract

Purpose of Review

Cannabis abstinence, traditionally, is the primary outcome in cannabis use disorder (CUD) treatment trials. Due to the changing legality of cannabis, patient goals, and preliminary evidence suggesting that individuals who reduce their cannabis use may show functional improvements, cannabis reduction is a desirable alternative outcome in CUD trials. We review challenges in measuring cannabis reduction and the evidence to support various definitions of reduction.

Recent Findings

Reduction in number of cannabis use days was associated with improvements in functioning across several studies. Reductions in quantity of cannabis used was inconsistently associated with improvements in functioning, though definitions of quantity varied across studies. Different biomarkers may be used depending on the reduction outcome.

Summary

Biologically confirmed reductions in frequency of cannabis use days may represent a viable endpoint in clinical trials for cannabis use disorder. Additional research is needed to better quantify reduction in cannabis amounts.

Keywords

Cannabis use disorder Harm reduction Cannabis quantification Randomized controlled trial Biomarkers Δ9-tetrahydrocannabinol 

Notes

Funding Information

Effort was supported by National Institutes of Health grants from the National Institute of Drug Abuse (R01 DA042114), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (K12 HD055885), and the National Institute on Alcohol Abuse and Alcoholism (K23 AA025399).

Compliance with Ethical Standards

Conflict of Interest

Marilyn A. Huestis provides consultation to Pinney & Associates, Inc., Canopy Health Innovations, Intelligent Fingerprinting, Cannabix, Evanostics, Inc., and the Center for Forensic Science Research and Education. Kevin M. Gray provides consultation to Pfizer, Inc.

Human and Animal Rights and Informed Consent

This article does not contain any original studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Hasin DS, Saha TD, Kerridge BT, et al. Prevalence of marijuana use disorders in the United States between 2001-2002 and 2012-2013. JAMA Psychiatry. 2015;72(12):1235–42.PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    American Psychiatric Association. Diagnostic and statistical manual of mental disorders (4th edition, text revision): Washington,D,C.,American Psychiatric Pub; 2000.Google Scholar
  3. 3.
    Gates PJ, Sabioni P, Copeland J, Le Foll B, Gowing L. Psychosocial interventions for cannabis use disorder. Cochrane Database of Systematic Reviews 2016, Issue 5. Art. No.: CD005336.  https://doi.org/10.1002/14651858.CD005336.pub4
  4. 4.
    Nielsen S, Gowing L, Sabioni P, Le Foll B. Pharmacotherapies for cannabis dependence. Cochrane Database of Systematic Reviews 2019, Issue 1. Art. No.: CD008940.  https://doi.org/10.1002/14651858.CD008940.pub3.
  5. 5.
    Sherman BJ, McRae-Clark AL. Treatment of cannabis use disorder: current science and future outlook. Pharmacotherapy. 2016;36(5):511–35.PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Sahlem GL, Tomko RL, Sherman BJ, Gray KM, McRae-Clark AL. Impact of cannabis legalization on treatment and research priorities for cannabis use disorder. Int Rev Psychiatry. 2018;30(3):216–25.PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Masters MN, Haardorfer R, Windle M, Berg C. Psychosocial and cessation-related differences between tobacco-marijuana co-users and single product users in a college student population. Addict Behav. 2018;77:21–7.PubMedCrossRefPubMedCentralGoogle Scholar
  8. 8.
    McClure EA, Tomko RL, Salazar CA, Akbar SA, Squeglia LM, Herrmann E, et al. Tobacco and cannabis co-use: drug substitution, quit interest, and cessation preferences. Exp Clin Psychopharmacol. 2019;27(3):265–75.PubMedCrossRefPubMedCentralGoogle Scholar
  9. 9.
    •• Lee DC, Schlienz NJ, Peters EN, Dworkin RH, Turk DC, Strain EC, et al. Systematic review of outcome domains and measures used in psychosocial and pharmacological treatment trials for cannabis use disorder. Drug Alcohol Depend. 2019;194:500–17 This systematic review describes primary and secondary outcome measures typically assessed in psychosocial and pharmacotherapy clinical trials for cannabis use disorder. PubMedCrossRefPubMedCentralGoogle Scholar
  10. 10.
    Lozano BE, Stephens RS, Roffman RA. Abstinence and moderate use goals in the treatment of marijuana dependence. Addiction. 2006;101(11):1589–97.PubMedCrossRefPubMedCentralGoogle Scholar
  11. 11.
    •• Loflin MJE, Huestis MA, Aklin, WM, Budney AJ, D’Souza DC, Dworkin RH, Gray KM, Kiluk BD, Lee D, Le Foll B, Lile JA, Mason BJ, McRae-Clark AL, Montoya I, Peters EN, Ramey T, Turk DC, Vandrey R, Weiss RD, Strain EC. Choosing clinical endpoints for cannabis use disorder clinical trials: ACTTION meeting recommendations. Under Review. This manuscript reviews recommendations from experts in cannabis use disorder with regard to the assessment of cannabis use in clinical trials. Google Scholar
  12. 12.
    Riggs NR, Conner BT, Parnes JE, Prince MA, Shillington AM, George MW. Marijuana eCHECKUPTO GO: Effects of a personalized feedback plus protective behavioral strategies intervention for heavy marijuana-using college students. Drug Alcohol Depend. 2018;190:13–9.PubMedCrossRefPubMedCentralGoogle Scholar
  13. 13.
    Food and Drug Administration. Alcoholism: developing drugs for treatment (No FDA D-0152-001) Silver Spring. https://www.fda.gov/files/drugs/published/Alcoholism---Developing-Drugs-for-Treatment.pdf
  14. 14.
    Creswell KG, Chung T. Treatment for alcohol use disorder: progress in predicting treatment outcome and validating non-abstinent end points. Alcohol Clin Exp Res. 2018;42(10):1874–9.PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Witkiewitz K, Finney JW, Harris AH, Kivlahan DR, Kranzler HR. Recommendations for the design and analysis of treatment trials for alcohol use disorders. Alcohol Clin Exp Res. 2015;39(9):1557–70.PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    Witkiewitz K, Hallgren KA, Kranzler HR, et al. Clinical validation of reduced alcohol consumption after treatment for alcohol dependence using the World Health Organization risk drinking levels. Alcohol Clin Exp Res. 2017;41(1):179–86.PubMedCrossRefPubMedCentralGoogle Scholar
  17. 17.
    Hasin DS, Wall M, Witkiewitz K, Kranzler HR, Falk D, Litten R, et al. Change in non-abstinent WHO drinking risk levels and alcohol dependence: a 3 year follow-up study in the US general population. Lancet Psychiatry. 2017;4(6):469–76.PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Cuttler C, Spradlin A. Measuring cannabis consumption: psychometric properties of the Daily Sessions, Frequency, Age of Onset, and Quantity of Cannabis Use Inventory (DFAQ-CU). PLoS One. 2017;12(5):e0178194.PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Walden N, Earleywine M. How high: quantity as a predictor of cannabis-related problems. Harm Reduct J. 2008;5:1–8.CrossRefGoogle Scholar
  20. 20.
    Norberg MM, Mackenzie J, Copeland J. Quantifying cannabis use with the Timeline Followback approach: a psychometric evaluation. Drug Alcohol Depend. 2012;121:247–52.PubMedCrossRefGoogle Scholar
  21. 21.
    Tomko RL, Baker NL, McClure EA, Sonne SC, McRae-Clark AL, Sherman BJ, et al. Incremental validity of estimated cannabis grams as a predictor of problems and cannabinoid biomarkers: evidence from a clinical trial. Drug Alcohol Depend. 2018;182:1–7.PubMedCrossRefGoogle Scholar
  22. 22.
    Hindocha C, Norberg MM, Tomko RL. Solving the problem of cannabis quantification. Lancet Psychiatry. 2018;5(4):e8.PubMedCrossRefGoogle Scholar
  23. 23.
    Casajuana C, López-Pelayo H, Miquel L, Balcells-Oliveró MM, Colom J, Gual A. Quantitative criteria to screen for cannabis use disorder. Eur Addict Res. 2018;24(3):109–17.PubMedCrossRefGoogle Scholar
  24. 24.
    Casajuana Kögel C, Balcells-Olivero MM, López-Pelayo H, Miquel L, Teixidó L, Colom J, et al. The standard joint unit. Drug Alcohol Depend. 2017;176:109–16.PubMedCrossRefGoogle Scholar
  25. 25.
    Zeisser C, Thompson K, Stockwell T, Duff C, Chow C, Vallance K, et al. A ‘standard joint’? The role of quantity in predicting cannabis-related problems. Addict Res Theory. 2012;20(1):82–92.CrossRefGoogle Scholar
  26. 26.
    Buu A, Hu YH, Pampati S, Arterberry BJ, Lin HC. Predictive validity of cannabis consumption measures: results from a national longitudinal study. Addict Behav. 2017;73:36–40.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Hser YI, Mooney LJ, Huang D, Zhu Y, Tomko RL, McClure E, et al. Reductions in cannabis use are associated with improvements in anxiety, depression, and sleep quality, but not quality of life. J Subst Abus Treat. 2017;81:53–8.CrossRefGoogle Scholar
  28. 28.
    Brezing CA, Choi CJ, Pavlicova M, Brooks D, Mahony AL, Mariani JJ, et al. Abstinence and reduced frequency of use are associated with improvements in quality of life among treatment-seekers with cannabis use disorder. Am J Addict. 2018;27(2):101–7.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Mooney LJ, Zhu Y, Yoo C, Valdez J, Moino K, Liao JY, et al. Reduction in cannabis use and functional status in physical health, mental health, and cognition. J NeuroImmune Pharmacol. 2018;13(4):479–87.PubMedCrossRefGoogle Scholar
  30. 30.
    Liao JY, Mooney LJ, Zhu Y, Valdez J, Yoo C, Hser YI. Relationships between marijuana use, severity of marijuana-related problems, and health-related quality of life. Psychiatry Res. 2019 ; 279: 237-243.PubMedCrossRefPubMedCentralGoogle Scholar
  31. 31.
    Jonas B, Tensil MD, Tossmann P, Strüber E. Effects of treatment length and chat-based counseling in a web-based intervention for cannabis users: randomized factorial trial. J Med Internet Res. 2018;20(5):e166.PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Tossmann P, Jonas B, Tensil M, Lang P, Strüber E. A controlled trial of an internet-based intervention program for cannabis users. Cyberpsychol Behav Soc Netw. 2011;14(11):673–9.PubMedCrossRefPubMedCentralGoogle Scholar
  33. 33.
    McCambridge J, Strang J. The efficacy of single-session motivational interviewing in reducing drug consumption and perceptions of drug-related risk and harm among young people: results from a multi-site cluster randomized trial. Addiction. 2004;99(1):39–52.PubMedCrossRefPubMedCentralGoogle Scholar
  34. 34.
    • Fitzmaurice GM, Lipsitz SR, Weiss RD. Statistical considerations in the choice of endpoint for drug use disorder trials. Drug Alcohol Depend. 2017;181:219–22 This manuscript illustrates statistical and power considerations when choosing an outcome measure in substance use disorder clinical trials. PubMedPubMedCentralCrossRefGoogle Scholar
  35. 35.
    Beckstead JW. On measurements and their quality: paper 2: random measurement error and the power of statistical tests. Int J Nurs Stud. 2013;50(10):1416–22.PubMedCrossRefPubMedCentralGoogle Scholar
  36. 36.
    Shiffman S. Ecological momentary assessment (EMA) in studies of substance use. Psychol Assess. 2009;21(4):486–97.PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4:1–32.CrossRefGoogle Scholar
  38. 38.
    Wilson TD, Dunn EW. Self-knowledge: its limits, value, and potential for improvement. Annu Rev Psychol. 2004;55:493–18.PubMedCrossRefPubMedCentralGoogle Scholar
  39. 39.
    Schwarz N, Oyserman D. Asking questions about behavior: cognition, communication, and questionnaire construction. Am J Eval. 2001;22(2):127–60.CrossRefGoogle Scholar
  40. 40.
    Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases. Science. 1974;185(4157):1124–31.PubMedCrossRefPubMedCentralGoogle Scholar
  41. 41.
    Magura S, Kang SY. Validity of self-reported drug use in high risk populations: a meta-analytical review. Subst Use Misuse. 1996;31(9):1131–53.PubMedCrossRefPubMedCentralGoogle Scholar
  42. 42.
    Baker NL, Gray KM, Sherman BJ, Morella K, Sahlem GL, Wagner AM, et al. Biological correlates of self-reported new and continued abstinence in cannabis cessation treatment clinical trials. Drug Alcohol Depend. 2018;187:270–7.PubMedPubMedCentralCrossRefGoogle Scholar
  43. 43.
    Gray KM, Watson NL, Christie DK. Challenges in quantifying marijuana use. Am J Addict. 2009;18(2):178–9.PubMedPubMedCentralCrossRefGoogle Scholar
  44. 44.
    Hindocha C, Freeman TP, Curran HV. Anatomy of a joint: comparing self-reported and actual dose of cannabis and tobacco in a joint, and how these are influenced by controlled acute administration. Cannabis Cannabinoid Res. 2017:2217–23.Google Scholar
  45. 45.
    El Sohly MA, Mehmedic Z, Foster S, Gon C, Chandra S, Church JC. Changes in cannabis potency over the last 2 decades (1995–2014): analysis of current data in the United States. Biol Psychiatry. 2016;79:613–9.CrossRefGoogle Scholar
  46. 46.
    Mariani JJ, Brooks D, Haney M, Levin FR. Quantification and comparison of marijuana smoking practices:blunts, joints, and pipes. Drug Alcohol Depend. 2011;113(2-3):249–51.PubMedCrossRefPubMedCentralGoogle Scholar
  47. 47.
    Donovan DM, Bigelow GE, Brigham GS, Carroll KM, Cohen AJ, Gardin JG, 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.PubMedCrossRefPubMedCentralGoogle Scholar
  48. 48.
    •• Huestis MA, Smith ML. Cannabinoid markers in biological fluids and tissues: revealing intake. Trends Mol Med. 2018;24(2):156–72 This manuscript provides a recent review of biological matrices for assessing cannabis intake. PubMedCrossRefPubMedCentralGoogle Scholar
  49. 49.
    Huestis MA, Barnes A, Smith ML. Estimating the time of last cannabis use from plasma Δ9-tetrahydrocannabinol and 11-nor-9-carboxy- Δ9-tetrahydrocannabinol concentrations. Clin Chem. 2005;51:2289–95.PubMedCrossRefPubMedCentralGoogle Scholar
  50. 50.
    Swortwood MJ, Newmeyer MN, Andersson M, Abulseoud OA, Scheidweiler KB, Huestis MA. Cannabinoid disposition in oral fluid after controlled smoked, vaporized, and oral cannabis administration. Drug Test Anal. 2017;9(6):905–15.PubMedCrossRefGoogle Scholar
  51. 51.
    Lee D, Schwope DM, Milman G, Barnes AJ, Gorelick DA, Huestis MA. Cannabinoid disposition in oral fluid after controlled smoked cannabis. Clin Chem. 2012;58:748–56.PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Anizan S, Milman G, Desrosiers N, Barnes AJ, Gorelick DA, Huestis MA. Oral fluid cannabinoid concentrations following controlled smoked cannabis in chronic frequent and occasional smokers. Anal Bioanal Chem. 2013;405:8451–61.PubMedCrossRefPubMedCentralGoogle Scholar
  53. 53.
    Desrosiers NA, Milman G, Mendu DR, Lee D, Barnes AJ, Gorelick DA, et al. Cannabinoids in oral fluid by on-site immunoassay and by GC-MS using two different oral fluid collection devices. Anal Bioanal Chem. 2014;406(17):4117–28.PubMedPubMedCentralCrossRefGoogle Scholar
  54. 54.
    Lee D, Huestis MA. Current knowledge on cannabinoids in oral fluid. Drug Test Anal. 2014;6:88–111.PubMedCrossRefPubMedCentralGoogle Scholar
  55. 55.
    Niedbala RS, Kardos KW, Fritch DF, Kardos S, Fries T, Waga J, et al. Detection of marijuana use by oral fluid and urine analysis following single-dose administration of smoked and oral marijuana. J Anal Toxicol. 2001;25:289–303.PubMedCrossRefPubMedCentralGoogle Scholar
  56. 56.
    Toennes SW, Ramaekers JG, Theunissen EL, Moeller MR, Kauert GF. Pharmacokinetic properties of Δ9-tetrahydrocannabinol in oral fluid of occasional and chronic users. J Anal Toxicol. 2010;34:216–21.PubMedCrossRefPubMedCentralGoogle Scholar
  57. 57.
    Vandrey R, Herrmann ES, Mitchell JM, Bigelow GE, Flegel R, LoDico C, et al. Pharmacokinetic profile of oral cannabis in humans: blood and oral fluid disposition and relation to pharmacodynamic outcomes. J Anal Toxicol. 2017;41(2):83–99.PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Lovestead TM, Bruno TJ. Determination of cannabinoid vapor pressures to aid in vapor phase detection of intoxication. Forensic Chem. 2017;5:79–85.PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Himes SK, Scheidweiler KB, Beck O, Gorelick DA, Desrosiers NA, Huestis MA. Cannabinoids in exhaled breath following controlled administration of smoked cannabis. Clin Chem. 2013;59(12):1780–9.PubMedPubMedCentralCrossRefGoogle Scholar
  60. 60.
    Lynch KL, Luo YR, Hooshfar S, Yun C. Correlation of breath and blood Δ9-tetrahydrocannabinol concentrations and release kinetics following controlled administration of smoked cannabis. Clin Chem. 2019;65(9):1171–9.PubMedCrossRefGoogle Scholar
  61. 61.
    Beckham JC, Adkisson KA, Hertzberg J, Kimbrel NA, Budney AJ, Stephens RS, et al. Mobile contingency management as an adjunctive treatment for co-morbid cannabis use disorder and cigarette smoking. Addict Behav. 2018;79:86–92.PubMedCrossRefGoogle Scholar
  62. 62.
    Sherman BJ, Caruso MA, McRae-Clark AL. Exogenous progesterone for cannabis withdrawal in women: feasibility trial of a novel multimodal methodology. Pharmacol Biochem Behav. 2019;179:22–6.PubMedCrossRefGoogle Scholar
  63. 63.
    Musshoff F, Madea B. Review of biologic matrices (urine, blood, hair) as indicators of recent or ongoing cannabis use. Ther Drug Monit. 2006;28:155–63.PubMedCrossRefGoogle Scholar
  64. 64.
    D'Souza DC, Cortes-Briones J, Creatura G, Bluez G, Thurnauer H, Deaso E, et al. Efficacy and safety of a fatty acid amide hydrolase inhibitor (PF-04457845) in the treatment of cannabis withdrawal and dependence in men: a double-blind, placebo-controlled, parallel group, phase 2a single-site randomised controlled trial. Lancet Psychiatry. 2019;6(1):35–45.PubMedCrossRefGoogle Scholar
  65. 65.
    Smith ML, Barnes AJ, Huestis MA. Identifying new cannabis use with urine creatinine-normalized THCCOOH concentrations and time intervals between specimen collections. J Anal Toxicol. 2009;33(4):185–9.PubMedPubMedCentralCrossRefGoogle Scholar
  66. 66.
    Schwilke EW, Gullberg RG, Darwin WD, Chiang N, Cadet JL, Gorelick DA, et al. Differentiating new cannabis use from residual urinary cannabinoid excretion in chronic, daily cannabis users. Addiction. 2011;106:499–506.PubMedCrossRefGoogle Scholar
  67. 67.
    Huestis MA, Scheidweiler KB, Saito T, Fortner N, Abraham T, Gustafson RA, et al. Excretion of Δ9-tetrahydrocannabinol in sweat. Forensic Sci Int. 2008;174(2-3):173–7.PubMedCrossRefGoogle Scholar
  68. 68.
    Taylor M, Lees R, Henderson G, Lingford-Hughes A, Macleod J, Sullivan J, et al. Comparison of cannabinoids in hair with self-reported cannabis consumption in heavy, light and non-cannabis users. Drug Alcohol Rev. 2017;36(2):220–6.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Rachel L. Tomko
    • 1
    Email author
  • Kevin M. Gray
    • 1
  • Marilyn A. Huestis
    • 2
  • Lindsay M. Squeglia
    • 1
  • Nathaniel L. Baker
    • 3
  • Erin A. McClure
    • 1
  1. 1.Department of Psychiatry and Behavioral SciencesMedical University of South CarolinaCharlestonUSA
  2. 2.Institute of Emerging Health ProfessionsThomas Jefferson UniversityPhiladelphiaUSA
  3. 3.Department of Public Health SciencesMedical University of South CarolinaCharlestonUSA

Personalised recommendations