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Record W4402325634 · doi:10.1136/spcare-2024-anzspm.11

OP-11 A double-blind randomised controlled trial of dose-escalated CBD/THC oil for symptom management in advanced cancer

2024· article· en· W4402325634 on OpenAlexaboutno aff
Phillip Good, Ristan M. Greer, Anita Pelecanos, Alison Kearney, Georgie Huggett, Taylan Gurgenci, Janet Hardy

Bibliographic record

VenueOral Presentations · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsnot available
Fundersnot available
KeywordsDouble blindMedicineCancerAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

Background Patients with advanced cancer commonly access cannabis in an attempt to improve their symptoms. It has been difficult to show evidence of benefit for individual symptoms in a randomised controlled trial setting however. Rather than focus on specific symptoms, we have chosen to assess the benefit, if any, of medicinal cannabis (MC) on total symptom burden. Objective To assess the impact of a 1:1 10mg/10mg THC/CBD oil on total symptom burden in patients with advanced cancer receiving palliative care. Methods Eligible patients had a total symptom distress score (TSDS) as measured by an Edmonton Symptom Assessment Scale (ESAS) of ≥10/90 (with a least one symptom score ≥3) and a negative baseline THC urine test. They were excluded if they had severe liver, renal or psychiatric dysfunction or were still driving a motor vehicle. Participants were randomised to MC oil, with a dose escalation from 2.5mg to 30mg/day, or matched placebo over 14 days according to tolerance and efficacy. The patient determined dose was then continued for another 14 days. The primary outcome measure was change in TSDS from baseline at 14 days. Secondary outcomes included participant selected dose, individual symptom scores, change in TSDS over time, opioid use, depression, anxiety and stress (DASS), QoL (EORTC), global impression of change (GIC) and adverse events (AEs). Results One hundred and forty-five patients were randomised over 46 months to reach the planned sample size of 120 at day 14. The median (range) dose for those in the active arm was 15mg (5–30mg) THC/CBD per day. The mean (SD) change in TSDS from baseline was -6.30 (12.30) for MC and -6.98 (12.56) for placebo, with no difference between arms (p=0.76). Response (defined as ≥6 point fall in TSDS from baseline) was 25/56 (44.6%) for MC and 32/65 (49.2%) for placebo, p=0.75. There was a significant difference in reduction in ESAS pain scores at day 14 (mean (SD)-1.41 (2.15) MC, -0.46 (2.82) placebo) in favor of MC, remaining significant when adjusted for baseline values (mean (SE) 0.85 (0.42)) (p=0.04) and supported by a reduction in QoL pain scores (difference in reduction of pain score/day 0.46 (SE 0.2), p=0.02). AEs of special interest revealed an increased incidence of confusion, feeling high, and exaggerated sense of well-being in MC arm. There was no difference between arms for any other secondary outcome. Attrition from toxicity was higher in the MC arm. Discussion The delivery of palliative care led to an improvement in TSDS over time in patients with advanced cancer. The addition of MC did not add to this benefit but did result in a small improvement in pain scores at the expense of increased toxicity.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0190.002

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.

Opus teacher head0.065
GPT teacher head0.441
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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