Efficacy and mechanisms of cannabis oil for alleviating side effects of breast cancer chemotherapy (CBC2): protocol for randomized controlled trial
Bibliographic record
Abstract
Abstract Background In a pilot study using both cannabidiol (CBD) and tetrahydrocannabinol (THC) as single agents in advanced cancer patients undergoing palliative care in Thailand, the doses were generally well tolerated, and the outcome measure of total symptom distress scores showed overall symptom benefit. The current study aims to determine the intensity of the symptoms experienced by breast cancer patients, to explore the microbiome profile, cytokines, and bacterial metabolites before and after the treatment with cannabis oil or no cannabis oil, and to study the pharmacokinetics parameters and pharmacogenetics profile of the doses. Methods A randomized, double-blinded, placebo-controlled trial will be conducted on the breast cancer cases who were diagnosed with breast cancer and currently receiving chemotherapy at King Chulalongkorn Memorial Hospital (KCMH), Bangkok, Thailand. Block randomization will be used to allocate the patients into three groups: Ganja Oil (THC 2 mg/ml; THC 0.08 mg/drop, and CBD 0.02 mg/drop), Metta Osot (THC 81 mg/ml; THC 3 mg/drop), and placebo oil. The Edmonton Symptom Assessment System (ESAS), Food Frequency Questionnaires (FFQ), microbiome profile, cytokines, and bacterial metabolites will be assessed before and after the interventions, along with pharmacokinetic and pharmacogenetic profile of the treatment during the intervention. Trial registration TCTR20220809001.
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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 | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.078 | 0.011 |
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".