Safety, feasibility, and effectiveness of implementing supervised exercise into the clinical care of individuals with advanced cancer
Bibliographic record
Abstract
Objective To evaluate the safety, feasibility, and preliminary effectiveness of implementing supervised exercise programming into the clinical care of individuals with advanced cancer. Design Single group implementation feasibility study using a pre–posttest design. Setting Exercise Oncology Unit of the Spanish Cancer Association (a cancer-specific community facility outside the hospital setting). Participants Adult individuals with advanced cancer profile involving advanced local cancer or distant metastases. Intervention A 12-week, twice-weekly, supervised, clinic-based multi-component exercise program. Main Measure Paired t-tests were used to assess pre–post changes and analyses of covariance were used to compare effects based on selected participant characteristics. Results Eighty-four individuals with advanced cancer completed the baseline assessment, with six participants withdrawing prior to the start of the program. Of the 78 participants, 17 dropped out, thus, a total of 61 completed the final assessment. Mean adherence was 82.5%. No serious adverse events occurred. Exercise significantly improved VO 2max by 5.2 mL·kg·min ( p < 0.001), chest strength ( p < 0.001), leg strength ( p < 0.001), lean body mass ( p = 0.003), skeletal muscle mass ( p < 0.002), % body fat ( p = 0.02), quality of life by 5.3 points ( p = 0.009), fatigue by 3.2 points ( p = 0.012), and physical activity by 1680 METs/week ( p < 0.001). Conclusions Our clinically supervised and tailored exercise program involving moderate to vigorous intensity exercise was found to be feasible, safe, and effective for individuals with advanced cancer. Implications for Cancer Survivors With proper screening and supervision, individuals with advanced cancer can benefit from tailored exercise oncology support as part of an overall therapeutic care plan.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".