Exercise During Breast Cancer Treatment: Results Of The NEXT-BRCA Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE: To determine the feasibility and effectiveness of institution-based exercise and self-management education on improving outcomes for individuals receiving treatment for breast cancer (BC). METHODS: A hybrid implementation-effectiveness study was conducted at a single site in Canada. Eligible participants included adult females with a current diagnosis of stage 1-3 BC undergoing treatment. Participants were randomized to one of three groups: 1) Exercise and self-management (EXSM; 8 in person sessions of moderate intensity aerobic exercise, self-management education, 4 booster sessions), 2) SM only (8 virtual sessions of self-management education, 4 booster sessions), or 3) usual care (no intervention). Feasibility (recruitment, retention, and adherence rates) and effectiveness (physical activity level (primary), exercise knowledge and behaviour, perception of health status, quality of life, and physical functioning) were assessed pre and post intervention, and at 6- and 12-month follow-up. Descriptive statistics described feasibility outcomes and an ANCOVA was used to assess effectiveness over time. RESULTS: Eighty-five participants enrolled in the study. Most were 40-60 years of age (56%), living with stage 2 BC (46%), and receiving chemotherapy (68%). Feasibility outcomes demonstrated a recruitment rate of 72%, retention rates of 75% (EXSM) and 93% (SM), and adherence rates of 76% (EXSM) and 93% (SM). ANCOVA analysis demonstrated a significant effect of group and timepoint interaction on all outcomes. The EXSM group showed a significant improvement in our primary outcome, physical activity level, compared to UC at the post-intervention (t = 6.00, p < 0.001), 6-month follow-up (t = 9.70, p < 0.001), and 12-month follow-up (t = 7.85, p < 0.001). The SM only group also showed a significant improvement compared to UC at all three timepoints (post-intervention: t = 6.87, p < 0.006; 6-month follow-up: t = 8.67, p < 0.001; 12-month follow up: t = 8.90, p < 0.001). No adverse events occurred during the intervention. CONCLUSION: Institution-based exercise and virtual self-management is feasible for individuals with BC during treatment and is effective in improving outcomes. Future research should consider triaging exercise strategies based on an individual’s cancer and personal characteristics. Supported by: Juravinski Hospital and Cancer Centre Foundation (Grant #T210)
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".