Role of physical activity in cancer survival and recurrence: A narrative review from relationship evidence to crucial research perspectives
Bibliographic record
Abstract
Purpose: The benefits of Physical Activity (PA) considered as a major supportive care in cancer patients, on survival, and recurrence risk is largely disseminated in public communication. However, these data must be taken with caution. The main objectives were to review the evidence and limits of studies reported regarding the post-diagnosis PA role on cancer survival and recurrence risk to secondly discuss of research perspectives on PA programs. Method: The narrative review included all published or ongoing studies in English during the last 20 years related to PA, survival and recurrence risk with a systematic search on main databases. Results and discussion: The current evidences regarding the PA role on survival and recurrence risk were only based on cohort studies, mainly in breast cancer. The major methodological limits identified as the lack of PA change assessment, PA level assessed largely by self-reported methods and the significant inter- but also intra- variability make the interpretation of data very. Beyond the use of rigorous RCT, the major issue is to develop adapted and personalized interventions to progressively increase PA level overtime in cancer survivors. Conclusion: Despite the lack of causal relationship between post-diagnosis PA, survival and recurrence risk, the review underlines several interesting research perspectives. The future PA interventions, using innovative tools and integrated to the “real-life” will argued for the potential antitumoral PA role growing in literature.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".