Combination Therapy of Physical Activity and Dexamethasone for Cancer-Related Fatigue: A Phase II Randomized Double-Blind Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Despite the high frequency of cancer-related fatigue (CRF) and its debilitating effects on the quality of life of patients with advanced cancer, there are limited treatment options available. Treatments including physical activity (PA) or dexamethasone (Dex) improve CRF; however, they have lower adherence rates (PA) or long-term adverse effects (Dex). The aim of this study was to determine the feasibility of and preliminary results for the combination of PA and Dex in improving CRF. METHODS: In this phase II randomized controlled trial, patients with advanced cancer and CRF scores of ≥4/10 on the Edmonton Symptom Assessment Scale were eligible. Patients were randomized to standardized PA for 4 weeks with either 4 mg of Dex (LoDex arm) or 8 mg of Dex (HiDex arm) twice a day for 7 days. Feasibility and change in the Functional Assessment of Cancer Illness Therapy-Fatigue subscale (FACIT-F) from baseline to day 8 and day 29 (primary outcome) were assessed. Secondary outcomes included changes in fatigue dimensions (FACIT-General, Patient-Reported Outcomes Measurement Information System [PROMIS]-Fatigue). RESULTS: A total of 60 of 67 (90%) patients were evaluable. All patients were adherent to study medication. We found that 84% and 65% of patients in the LoDex arm and 96% and 68% of patients in the HiDex arm were adherent to aerobic and resistance exercise, respectively. The FACIT-F effect size in the LoDex arm was 0.90 (P<.001) and 0.92 (P<.001) and the effect size in the HiDex arm was 0.86 and 1.03 (P<.001 for both) at days 8 and 29, respectively. We found significant improvements in the Functional Assessment of Cancer Therapy-Physical (P≤.013) and the PROMIS-Fatigue (P≤.003) at days 8 and 29 in both arms. Mixed-model analysis showed a significant improvement in the FACIT-F scores at day 8 (P<.001), day 15 (P<.001), and day 29 (P=.002). Changes in the FACIT-F scores were not significantly different between patients in the 2 arms (P=.86). CONCLUSIONS: Our study found that the combination therapy of PA with Dex was feasible and resulted in the improvement of CRF. The improvement was seen for up to 3 weeks after the discontinuation of Dex. Further larger studies are justified. CLINICALTRIALS: gov identifier: NCT02491632.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".