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Record W3198254215 · doi:10.1136/bmj.n1034

Medical cannabis or cannabinoids for chronic non-cancer and cancer related pain: a systematic review and meta-analysis of randomised clinical trials

2021· review· en· W3198254215 on OpenAlexafffund
Li Wang, Patrick Jiho Hong, Curtis May, Yasir Rehman, Yvgeniy Oparin, Chris J. Hong, Brian Y. Hong, Mahmood AminiLari, Lucas Gallo, Alka Kaushal, Samantha Craigie, Rachel Couban, Elena Kum, Harsha Shanthanna, Ira M. Price, Suneel Upadhye, Mark A. Ware, Fiona Campbell, Rachelle Buchbinder, Thomas Agoritsas, Jason W. Busse

Bibliographic record

VenueBMJ · 2021
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMcGill University Health CentreUniversity of ManitobaSickKids FoundationUniversity of TorontoMcMaster UniversityHospital for Sick ChildrenUniversity of British ColumbiaMcGill UniversityImpact
FundersUniwersytet Śląski w KatowicachChronic Pain Centre of Excellence for Canadian VeteransŚląski Uniwersytet Medyczny w KatowicachMedical Research CouncilRadboud UniversiteitCanadian Institutes of Health ResearchRadboud Universitair Medisch CentrumNational Health and Medical Research CouncilMcMaster University
KeywordsMeta-analysisCancerCannabisMedicineClinical trialSystematic reviewAlternative medicineChronic painMEDLINEPsychiatryInternal medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the benefits and harms of medical cannabis and cannabinoids for chronic pain. DESIGN: Systematic review and meta-analysis. DATA SOURCES: MEDLINE, EMBASE, AMED, PsycInfo, CENTRAL, CINAHL, PubMed, Web of Science, Cannabis-Med, Epistemonikos, and trial registries up to January 2021. STUDY SELECTION: Randomised clinical trials of medical cannabis or cannabinoids versus any non-cannabis control for chronic pain at ≥1 month follow-up. DATA EXTRACTION AND SYNTHESIS: Paired reviewers independently assessed risk of bias and extracted data. We performed random-effects models meta-analyses and used GRADE to assess the certainty of evidence. RESULTS: A total of 32 trials with 5174 adult patients were included, 29 of which compared medical cannabis or cannabinoids with placebo. Medical cannabis was administered orally (n=30) or topically (n=2). Clinical populations included chronic non-cancer pain (n=28) and cancer related pain (n=4). Length of follow-up ranged from 1 to 5.5 months. Compared with placebo, non-inhaled medical cannabis probably results in a small increase in the proportion of patients experiencing at least the minimally important difference (MID) of 1 cm (on a 10 cm visual analogue scale (VAS)) in pain relief (modelled risk difference (RD) of 10% (95% confidence interval 5% to 15%), based on a weighted mean difference (WMD) of -0.50 cm (95% CI -0.75 to -0.25 cm, moderate certainty)). Medical cannabis taken orally results in a very small improvement in physical functioning (4% modelled RD (0.1% to 8%) for achieving at least the MID of 10 points on the 100-point SF-36 physical functioning scale, WMD of 1.67 points (0.03 to 3.31, high certainty)), and a small improvement in sleep quality (6% modelled RD (2% to 9%) for achieving at least the MID of 1 cm on a 10 cm VAS, WMD of -0.35 cm (-0.55 to -0.14 cm, high certainty)). Medical cannabis taken orally does not improve emotional, role, or social functioning (high certainty). Moderate certainty evidence shows that medical cannabis taken orally probably results in a small increased risk of transient cognitive impairment (RD 2% (0.1% to 6%)), vomiting (RD 3% (0.4% to 6%)), drowsiness (RD 5% (2% to 8%)), impaired attention (RD 3% (1% to 8%)), and nausea (RD 5% (2% to 8%)), but not diarrhoea; while high certainty evidence shows greater increased risk of dizziness (RD 9% (5% to 14%)) for trials with <3 months follow-up versus RD 28% (18% to 43%) for trials with ≥3 months follow-up; interaction test P=0.003; moderate credibility of subgroup effect). CONCLUSIONS: Rapid Recommendation provides contextualised guidance based on this body of evidence. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/3pwn2.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.071
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0270.038
Bibliometrics0.0100.010
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.253
GPT teacher head0.543
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations285
Published2021
Admission routes2
Has abstractyes

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