Improving Quality of Life With Nabilone During Radiotherapy Treatments for Head and Neck Cancers
Bibliographic record
Abstract
OBJECTIVES: Patients treated for head and neck carcinomas experience a significant deterioration of their quality of life during treatments because of severe side effects. Nabilone has many properties that could alleviate symptoms caused by radiotherapy and improve patients' quality of life. The aim of the present study was to compare the effects of nabilone versus placebo on the quality of life and side effects during radiotherapy for head and neck carcinomas. METHODS: Fifty-six patients were randomized to nabilone or placebo. Patients filled the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 and the EORTC QLQ-H&N35; three independent questionnaires assessing appetite, nausea, and toxicity; and a visual analog scale for pain. These data were collected before radiotherapy, each week during radiotherapy, and 4 weeks after radiotherapy. Patients were weighed every week. RESULTS: Nabilone did not lengthen the time necessary for a 15% deterioration of quality of life (P = .4279), and it was not better than placebo for relieving symptoms like pain (P = .6048), nausea (P = .7105), loss of appetite (P = .3295), weight (P = .1454), mood (P = .3214), and sleep (P = .4438). CONCLUSION: At the dosage used, nabilone was not potent enough to improve the patients' quality of life over placebo.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".