An Open-Label Pilot Study Testing the Feasibility of Assessing Total Symptom Burden in Trials of Cannabinoid Medications in Palliative Care
Bibliographic record
Abstract
Background: There is considerable interest in the use of cannabinoids for symptom control in palliative care, but there is little high-quality evidence to guide clinical practice. Objectives: Assess the feasibility of using global symptom burden measures to assess response to medicinal cannabis, to determine median tolerated doses of cannabidiol (CBD) and tetrahydrocannabinol (THC), and to document adverse events (AEs). Design: Prospective two-arm open-label pilot trial of escalating doses of CBD and THC oil. Setting/Subjects: Participants had advanced cancer and cancer-related symptoms in a palliative and supportive care service in an Australian cancer center. Measurements: The main outcome measures were the number of participants screened and randomized over the time frame, the number of participants completing days 14 and 28 and providing total symptom distress scores (TSDSs) (measured using the Edmonton Symptom Assessment Scale), and the change from baseline of the TSDS at day 14. Results: Of the 21 participants enrolled (CBD, n = 16; THC, n = 5), 18 (86%) completed the primary outcome measure at day 14 and 8 completed at day 28. The median maximum tolerated doses were CBD, 300 mg/day (range 100–600 mg); THC, 10 mg/day (range 5–30 mg). Nine of 21 patients (43%) met the definition of response (≥6 point reduction in TSDS). Drowsiness was the most common AE. Conclusions: Trials of medicinal cannabis in advanced cancer patients undergoing palliative care are feasible. The doses of THC and CBD used in this study were generally well tolerated and the outcome measure of total symptom distress is promising as a measure of overall symptom benefit. Trial registration: ACTRN12618001205224.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".