Exercise Improves Physical Function and Mental Health of Brain Cancer Survivors
Bibliographic record
Abstract
Background Malignant brain tumors are unpredictable and incurable, with 5-year survival rates less than 30%. The poor prognosis combined with intensive treatment necessitates the inclusion of complementary and supportive therapies that optimize quality of life and reduce treatment-related declines in health. Exercise therapy has been shown to be beneficial in other cancer populations, but no evidence is available for brain cancer survivors. Therefore, we report results from 2 preliminary cases. Methods Two female patients diagnosed with glioblastoma multiforme and oligodendroglioma participated in a structured and supervised 12-week exercise program. The program consisted of two 1-hour resistance and aerobic exercise sessions per week and additional self-managed aerobic sessions. Outcome measures of strength, cardiovascular fitness, and several psychological indicators (depression, anxiety, and quality of life) were recorded at baseline, after 6 weeks and at the conclusion of the intervention. Results Exercise was well tolerated; both participants completed all 24 sessions and the home-based component with no adverse effects. Objective outcome measures displayed positive responses relating to reduced morbidity. Similar positive responses were found for psychological outcomes. Scores on the Hospital Anxiety and Depression Scale showed clinically meaningful improvements in depression and total distress. Conclusion These findings provide initial evidence that, despite the difficulties associated with brain cancer treatment and survivorship, exercise may be safe and beneficial and should be considered in the overall management of patients with brain 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".