Improved cancer-related fatigue in a randomised clinical trial: methylphenidate no better than placebo
Bibliographic record
Abstract
INTRODUCTION: Methylphenidate is a psychostimulant drug used to treat fatigue in patients with advanced cancer, for which there is no gold standard of treatment. OBJECTIVE: To explore the efficacy of methylphenidate in the relief of fatigue in patients with advanced cancer. MATERIALS AND METHODS: A randomised double-blind placebo-controlled multicentre clinical trial, stratified according to the intensity of fatigue. The treatment was considered effective if the improvement in mean fatigue intensity between baseline values and day 6 was significantly higher in the methylphenidate group than in the placebo group. The responses were measured using the Edmonton Symptoms Assessment System (ESAS) and the Functional Assessment of Cancer Therapy-Fatigue (FACT-F) scales. RESULTS: 35 patients received placebo and 42 patients received methylphenidate. The populations of both groups were homogeneous. Patients receiving methylphenidate did not exhibit statistically significant improvement of fatigue in comparison to patients receiving placebo (p=0.52). The mean improvement of fatigue (ESAS) on day 6 was -1.9 (±2.5) in the placebo group, and -2.3 (±2.6) in the methylphenidate group (p=0.52). The results obtained with the FACT-F were congruent with those obtained by the ESAS. The responses in patients with severe fatigue were -2.4 (±2.9) in the placebo group and -3.4 (±2.5) in the methylphenidate group; the difference was not statistically significant (p=0.3). CONCLUSION: Methylphenidate was not more efficient than placebo to treat cancer-related fatigue. Fatigue improved significantly after 3 days of treatment and was stabilised on day 6, both with placebo and methylphenidate. The side effects of methylphenidate were mild and infrequent. TRIAL REGISTRATION NUMBER: EudraCT Registry (2008-002171-27).
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 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".