Medical cannabis is effective for cancer-related pain: Quebec Cannabis Registry results
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To evaluate the safety and effectiveness of medical cannabis (MC) in reducing pain and concurrent medications in patients with cancer. METHODS: This study analysed data collected from patients with cancer who were part of the Quebec Cannabis Registry. Brief Pain Inventory (BPI), revised Edmonton Symptom Assessment System (ESAS-r) questionnaires, total medication burden (TMB) and morphine equivalent daily dose (MEDD) recorded at 3-month, 6-month, 9-month and 12-month follow-ups were compared with baseline values. Adverse events were also documented at each follow-up visit. RESULTS: This study included 358 patients with cancer. Thirteen out of 15 adverse events reported in 11 patients were not serious; 2 serious events (pneumonia and cardiovascular event) were considered unlikely related to MC. Statistically significant decreases were observed at 3-month, 6-month and 9-month follow-up for BPI worst pain (5.5±0.7 baseline, 3.6±0.7, 3.6±0.7, 3.6±0.8; p<0.01), average pain (4.1±0.6 baseline, 2.4±0.6, 2.3±0.6, 2.7±0.7; p<0.01), overall pain severity (3.7±0.5 baseline, 2.3±0.6, 2.3±0.6, 2.4±0.6; p<0.01) and pain interference (4.3±0.6 baseline, 2.4±0.6, 2.2±0.6, 2.4±0.7, p<0.01). ESAS-r pain scores decreased significantly at 3-month, 6-month and 9-month follow-up (3.7±0.6 baseline, 2.5±0.6, 2.2±0.6, 2.0±0.7, p<0.01). THC:CBD balanced strains were associated with better pain relief as compared with THC-dominant and CBD-dominant strains. Decreases in TMB were observed at all follow-ups. Decreases in MEDD were observed at the first three follow-ups. CONCLUSIONS: Real-world data from this large, prospective, multicentre registry indicate that MC is a safe and effective complementary treatment for pain relief in patients with cancer. Our findings should be confirmed through randomised placebo-controlled trials.
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.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it