The Case for Prehabilitation Prior to Breast Cancer Treatment
Bibliographic record
Abstract
Cancer rehabilitation in breast cancer survivors is well established, and there are many studies that focus on interventions to treat impairments as well as therapeutic exercise. However, very little is known about the role of prehabilitation for people with breast cancer. In this narrative review, we describe contemporary clinical management of breast cancer and associated treatment-related morbidity and mortality considerations. Knowing the common short- and long-term sequelae, as well as less frequent but serious sequelae, informs our rationale for multimodal breast cancer prehabilitation. We suggest 5 core components that may help to mitigate short- and long-term sequelae that align with consensus opinion of prehabilitation experts: total body exercise; locoregional exercise pertinent to treatment-related deficits; nutritional optimization; stress reduction/psychosocial support; and smoking cessation. In each of these categories, we review the literature and discuss how they may affect outcomes for women with breast 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".