Preliminary Results from a Phase IV Surveillance Study of Medical Cannabis Use in Australian Patients With Advanced Cancer Receiving Palliative Care
Bibliographic record
Abstract
Introduction:Our research group is conducting three large randomized placebo-controlled trials of medicinal cannabis for cancer symptoms. All participants are invited to take part in a posttrial surveillance study. Methods:Participants were given the manufacturers dosing instructions and liberty to titrate to effect. Data were collected on symptoms (Edmonton Symptom Assessment Scale [ESAS] score), perceived benefits, adverse effects, satisfaction with the product, and dose/frequency. Results:Twenty-six percent of eligible participants consented to take part in the surveillance study. Most participants changed their self-titrated dose at least once. Pain, sleep, and mood were the most frequently cited symptoms which improved. Fatigue, nausea, and cognitive impairment were the most frequently mentioned adverse effects. Conclusion:Participants felt confident making changes to their medicinal cannabis dose within the limits suggested by the manufacturer of each product. A number of benefits and adverse effects were ascribed to the product. Benefits were similar to those described in previous studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".