Edmonton Symptom Assessment Scale and Clinical Characteristics Associated With Cannabinoid Use in Oncology Supportive Care Outpatients
Bibliographic record
Abstract
BACKGROUND: Information about the frequency of cannabinoid use and the clinical characteristics of its users in oncology supportive care is limited. This study explored associations between cannabinoid use and cancer-related clinical characteristics in a cancer population. PATIENTS AND METHODS: This retrospective review included 332 patients who had a urine drug test (UDT) for tetrahydrocannabinol (THC) together with completion of an Edmonton Symptom Assessment Scale (ESAS) and cannabinoid history questionnaire on the same day that urine was obtained during 1 year in the supportive care clinic. RESULTS: The frequency of positive results for THC in a UDT was 22.9% (n=76). Significant statistical differences were seen between THC-positive and THC-negative patients for age (median of 52 [lower quartile, 44; upper quartile, 56] vs 58 [48; 67] years; P<.001), male sex (53.9% vs 39.5%; P=.034), and past or current cannabinoid use (65.8% vs 26.2%; P<.001). Statistical significance was observed in ESAS items between the THC-positive and THC-negative groups for pain (7 [lower quartile, 5; upper quartile; 8] vs 5 [3; 7]; P=.001), nausea (1 [0; 3] vs 0 [0; 3]; P=.049), appetite (4 [2; 7] vs 3 [0; 5.75]; P=.015), overall well-being (5.5 [4; 7] vs 5 [3; 6]; P=.002), spiritual well-being (5 [2; 6] vs 3 [1; 3]; P=.015), insomnia (7 [5; 9] vs 4 [2; 7]; P<.001), and total ESAS (52 [34; 66] vs 44 [29; 54]; P=.001). Among patients who reported current or past cannabinoid use, THC-positive patients had higher total scores and scores for pain, appetite, overall well-being, spiritual well-being, and insomnia than THC-negative patients. CONCLUSIONS: Patients with cancer receiving outpatient supportive care who had positive UDT results for THC had higher symptom severity scores for pain, nausea, appetite, overall and spiritual well-being, and insomnia compared with their THC-negative counterparts. These results highlight potential opportunities to improve palliative care.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".