An open‐label study of the effects of bupropion SR on fatigue, depression and quality of life of mixed‐site cancer patients and their partners
Bibliographic record
Abstract
This preliminary study investigated whether bupropion sustained release (SR) improved symptomatic fatigue, depression and quality of life in cancer patients and caregiver quality of life. The sample consisted of a prospective open case series of 21 cancer patients, with fatigue and with or without depression at moderate to severe levels, referred for psychiatric assessment from a tertiary care cancer centre. Both patient symptom ratings and caregiver ratings were measured before and after 4 weeks of treatment with the maximally tolerated dose of bupropion in the range of 100-300 mg per day. At trial completion, significant improvement was found for symptoms of fatigue and depression. Subjects were divided into two groups: depressed and non-depressed (based on a cut-off score of 17 on the Hamilton Depression Rating Scale). Both groups reported improvement for fatigue and depressive symptoms. Depressed subjects and their caregivers did not experience any change in quality of life, while the non-depressed subjects and their caregivers reported improvements. Results from this small group of patients suggest that bupropion may have potential as an effective pharmaceutical agent for treating cancer-related fatigue. A randomized, placebo-controlled trial with this medication is indicated.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".