Reduction of Cancer-Related Fatigue With Dexamethasone: A Double-Blind, Randomized, Placebo-Controlled Trial in Patients With Advanced Cancer
Bibliographic record
Abstract
PURPOSE: Cancer-related fatigue (CRF) is the most common symptom in patients with advanced cancer. The primary objective of this prospective, randomized, double-blind, placebo-controlled study was to compare the effect of dexamethasone and placebo on CRF. PATIENTS AND METHODS: Patients with advanced cancer with ≥ three CRF-related symptoms (ie, fatigue, pain, nausea, loss of appetite, depression, anxiety, or sleep disturbance) ≥ 4 of 10 on the Edmonton Symptom Assessment Scale (ESAS) were eligible. Patients were randomly assigned to either dexamethasone 4 mg or placebo orally twice per day for 14 days. The primary end point was change in the Functional Assessment of Chronic Illness-Fatigue (FACIT-F) subscale from baseline to day 15. Secondary outcomes included anorexia, anxiety, depression, and symptom distress scores. RESULTS: A total of 84 patients were evaluable (dexamethasone, 43; placebo, 41). Mean (± standard deviation) improvement in the FACIT-F subscale at day 15 was significantly higher in the dexamethasone than in the placebo group (9 [± 10.3] v 3.1 [± 9.59]; P = .008). The improvement in FACIT-F total quality-of-life scores was also significantly better for the dexamethasone group at day 15 (P = .03). The mean differences in the ESAS physical distress scores at day 15 were significantly better for the dexamethasone group (P = .013, respectively). No differences were observed for ESAS overall symptom distress (P = .22) or psychological distress score (P = .76). Frequency of adverse effects was not significantly different between groups (41 of 62 v 44 of 58; P = .14). CONCLUSION: Dexamethasone is more effective than placebo in improving CRF and quality of life in patients with advanced cancer.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".