Skip to main content
SpringerLink
Log in

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

  • Cannabis (A McRae-Clark B Sherman, Section Editors)
  • Published:
Current Addiction Reports Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

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

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  2. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (4th edition, text revision): Washington,D,C.,American Psychiatric Pub; 2000.

  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. 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. Sherman BJ, McRae-Clark AL. Treatment of cannabis use disorder: current science and future outlook. Pharmacotherapy. 2016;36(5):511–35.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  10. Lozano BE, Stephens RS, Roffman RA. Abstinence and moderate use goals in the treatment of marijuana dependence. Addiction. 2006;101(11):1589–97.

    Article  PubMed  Google Scholar 

  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.

  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.

    Article  PubMed  Google Scholar 

  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. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Walden N, Earleywine M. How high: quantity as a predictor of cannabis-related problems. Harm Reduct J. 2008;5:1–8.

    Article  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  22. Hindocha C, Norberg MM, Tomko RL. Solving the problem of cannabis quantification. Lancet Psychiatry. 2018;5(4):e8.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  36. Shiffman S. Ecological momentary assessment (EMA) in studies of substance use. Psychol Assess. 2009;21(4):486–97.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4:1–32.

    Article  PubMed  Google Scholar 

  38. Wilson TD, Dunn EW. Self-knowledge: its limits, value, and potential for improvement. Annu Rev Psychol. 2004;55:493–18.

    Article  PubMed  Google Scholar 

  39. Schwarz N, Oyserman D. Asking questions about behavior: cognition, communication, and questionnaire construction. Am J Eval. 2001;22(2):127–60.

    Article  Google Scholar 

  40. Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases. Science. 1974;185(4157):1124–31.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Gray KM, Watson NL, Christie DK. Challenges in quantifying marijuana use. Am J Addict. 2009;18(2):178–9.

    Article  PubMed  PubMed Central  Google Scholar 

  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.

  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.

    Article  CAS  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Lee D, Huestis MA. Current knowledge on cannabinoids in oral fluid. Drug Test Anal. 2014;6:88–111.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Lovestead TM, Bruno TJ. Determination of cannabinoid vapor pressures to aid in vapor phase detection of intoxication. Forensic Chem. 2017;5:79–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

Download references

Funding

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).

Author information

Authors and Affiliations

  1. Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, MSC 861, 67 President Street, Charleston, SC, 29425-8610, USA

    Rachel L. Tomko, Kevin M. Gray, Lindsay M. Squeglia & Erin A. McClure

  2. Institute of Emerging Health Professions, Thomas Jefferson University, Philadelphia, USA

    Marilyn A. Huestis

  3. Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA

    Nathaniel L. Baker

Authors
  1. Rachel L. Tomko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kevin M. Gray
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marilyn A. Huestis
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lindsay M. Squeglia
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nathaniel L. Baker
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Erin A. McClure
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rachel L. Tomko.

Ethics declarations

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.

Additional information

Key points

1. Reduction in cannabis use is an alternative to abstinence in cannabis use disorder treatment

2. Reduction in cannabis use is challenging to assess and biologically confirm, and definitions vary across trials

3. Preliminary evidence suggests that reduced number of days of cannabis use is associated with improvements in functioning

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Cannabis

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tomko, R.L., Gray, K.M., Huestis, M.A. et al. Measuring Within-Individual Cannabis Reduction in Clinical Trials: a Review of the Methodological Challenges. Curr Addict Rep 6, 429–436 (2019). https://doi.org/10.1007/s40429-019-00290-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40429-019-00290-y

Keywords

Search

Navigation