Long-term and serious harms of medical cannabis and cannabinoids for chronic pain: A systematic review of non-randomized studies
Bibliographic record
Abstract
Abstract Objective To establish the risk and prevalence of long-term and serious harms of medical cannabis and cannabinoids for chronic pain. Design Systematic review and meta-analysis. Data sources MEDLINE, EMBASE, PsycInfo, and the Cochrane Central Register of Controlled Trials (CENTRAL) from inception to April 1, 2020. Study selection Non-randomized studies reporting on harms of medical cannabis or cannabinoids in people living with chronic pain with ≥4 weeks of follow-up. Data extraction and synthesis A parallel guideline panel provided input on the design and interpretation of the systematic review, including selection of adverse events for consideration. Two reviewers, working independently and in duplicate, screened the search results, extracted data, and assessed risk of bias. We used random-effects models for all meta-analyses and the GRADE approach to evaluate the certainty of evidence. Results We identified 39 eligible studies that enrolled 12,143 patients with chronic pain. Very low certainty evidence suggests that adverse events are common (prevalence: 26.0%; 95% CI 13.2 to 41.2) among users of medical cannabis or cannabinoids for chronic pain, particularly any psychiatric adverse events (prevalence: 13.5%; 95% CI 2.6 to 30.6). However, very low certainty evidence indicates serious adverse events, adverse events leading to discontinuation, cognitive adverse events, accidents and injuries, and dependence and withdrawal syndrome are uncommon and typically occur in fewer than one in 20 patients. We compared studies with <24 weeks and ≥ 24 weeks cannabis use and found more adverse events reported among studies with longer follow-up (test of interaction p < 0.01). Palmitoylethanolamide was usually associated with few to no adverse events. We found insufficient evidence addressing the harms of medical cannabis compared to other pain management options, such as opioids. Conclusions There is very low certainty evidence that adverse events are common among people living with chronic pain who use medical cannabis or cannabinoids, but that few patients experience serious adverse events. Future research should compare long-term and serious harms of medical cannabis with other management options for chronic pain, including opioids. Systematic review registration https://osf.io/25bxf What is already known on this topic Medical cannabis and cannabinoids are increasingly used for the management of chronic pain. Clinicians and patients considering medical cannabis or cannabinoids as a treatment option for chronic pain require evidence on benefits and harms, including long-term and serious adverse events to make informed decisions. What this study adds Very low certainty evidence suggests that adverse events are common among people living with chronic pain who use medical cannabis or cannabinoids, including psychiatric adverse events, though serious adverse events, adverse events leading to discontinuation, cognitive adverse events, accidents and injuries, and dependence and withdrawal syndrome are uncommon. There is insufficient evidence comparing the harms of medical cannabis or cannabinoids to other pain management options, such as opioids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".