Potential Benefits from Physical Exercise in Advanced Cancer Patients Undergoing Systemic Therapy? A Narrative Review of the Randomized Clinical Trials
Bibliographic record
Abstract
DESIGN: The purpose of this review is the analysis of the literature concerning the effects of physical exercise in cancer patients undergoing medical oncologic treatment. Papers were retrieved from the scrutiny of 15 reviews/meta-analyses published in the last 2 years, which, however, pooled different populations of patients (surgical and medical patients, receiving or not an oncologic therapy, harboring a cancer, or being survivors). RESULTS: We reviewed the data of 35 RCTs on the use of physical exercise in cancer patients, distinguishing well-nourished from malnourished patients. The conclusions of our study are the following: No major difference between well-nourished and malnourished patients as regards compliance/adherence with physical exercise and outcomes. Compliance with physical exercise was reported in about 70% of the studies. Compared with a control group receiving the usual care, in patients who practiced physical exercise, a benefit in some parameters of physical function and quality of life and lean body mass (LBM) was reported in 61%, 47%, and 12%, respectively, of the studies in non-malnourished patients, and in 50%, 100%, and 36%, respectively, of the studies in malnourished patients. The benefit in LBM was more frequently reported in weight-losing patients. There was no strict association among the results of different outcomes (muscle function vs. quality of life vs. LBM). There are still some ill-defined issues, including the optimal physical regimen (with some authors favoring high-intensity interval training and resistance) and the place of exercising (patients usually preferring home exercises, which, however, have been proved less efficacious).
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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 | 0.017 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".