Exercise Recommendation for People With Bone Metastases: Expert Consensus for Health Care Providers and Exercise Professionals
Bibliographic record
Abstract
PURPOSE: Exercise has been underutilized in people with advanced or incurable cancer despite the potential to improve physical function and reduce psychosocial morbidity, especially for people with bone metastases because of concerns over skeletal complications. The International Bone Metastases Exercise Working Group (IBMEWG) was formed to develop best practice recommendations for exercise programming for people with bone metastases on the basis of published research, clinical experience, and expert opinion. METHODS: . RESULTS: Recommendations emerged from the contributing evidence and IBMEWG discussion for pre-exercise screening, exercise testing, exercise prescription, and monitoring of exercise response. Identification of individuals who are potentially at higher risk of exercise-related skeletal complication is a complex interplay of these factors: (1) lesion-related, (2) cancer and cancer treatment-related, and (3) the person-related. Exercise assessment and prescription requires consideration of the location and presentation of bone lesion(s) and should be delivered by qualified exercise professionals with oncology education and exercise prescription experience. Emphasis on postural alignment, controlled movement, and proper technique is essential. CONCLUSION: Ultimately, the perceived risk of skeletal complications should be weighed against potential health benefits on the basis of consultation between the person, health care team, and exercise professionals. These recommendations provide an initial framework to improve the integration of exercise programming into clinical care for people with bone metastases.
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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 | 0.042 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".