Meta-review finds paucity of evidence for medical cannabis in mental disorders

  • Black N et al
  • Lancet Psychiatry
  • 29 Oct 2019

  • International Clinical Digest
Access to the full content of this site is available only to registered healthcare professionals. Access to the full content of this site is available only to registered healthcare professionals.

Takeaway

  • Paucity of evidence supports medical cannabis treatment of mental health disorders.
  • Editorial states included psychiatric disorders have no common cause or pathophysiology.
  • Absence of evidence may also reflect research barriers.

Why this matters

  • More research is needed before cannabinoids can be broadly recommended for symptomatic, long-term mental disorder (depression, ADHD, Tourette's syndrome, posttraumatic stress disorder [PTSD], psychosis) treatment.

Key points

  • 83 eligible studies (40 randomized controlled trials [RCTs]; n=3067) included:
    • Depression (42 studies; 23 RCTs; n=2551), anxiety (31 studies; 17 RCTs; n=605), Tourette's syndrome (8 studies; 2 RCTs; n=36), ADHD (3 studies; 1 RCT; n=30), PTSD (12 studies; 1 RCT; n=10), psychosis (11 studies; 6 RCTs; n=281).
  • Pharmaceutical tetrahydrocannabinol-cannabidiol significantly reduced anxiety symptoms vs placebo: pooled standardized mean difference (SMD), −0.25 (95% CI, −0.49 to −0.01).
  • No significant improvements in depression symptoms vs active comparators or placebo (pooled SMD, −0.05 [95% CI, −0.22 to 0.13]).
  • No significant benefit for Tourette's syndrome, ADHD.
  • Worsening negative psychosis symptoms (SMD, 0.36; 95% CI, 0.10-0.62).
  • Pooled analysis (10 studies) showed significantly more adverse events vs placebo (OR, 1.99; 95% CI, 1.20-3.29).

Study design

  • Systematic, meta-review assessing effectiveness, safety of medicinal cannabinoids for treating mental disorders, related symptoms.
  • Funding: Therapeutic Goods Administration, Australia, others.

Limitations

  • Poor-quality data.
  • Small study sizes.
  • Heterogeneity lacking.
  • Selection bias.