Effects of exercise during chemotherapy for breast cancer on patient-reported outcomes: Secondary data analysis of a randomized controlled trial
Bibliographic record
Abstract
Background: Breast cancer is associated with poorer patient-reported outcomes (PROs) during treatment. Interventions to improve PROs are needed to reduce the burden associated with breast cancer. We tested the effects of an aerobic exercise intervention initiated during chemotherapy for breast cancer (EX) compared to usual care (wait-list control condition; UC) on PROs (cancer-related fatigue [CRF], general and disease-specific quality of life [QoL]) post-intervention. Methods: This study involved secondary analysis of data from the ACTIVATE trial – a two-arm, two-centre randomized controlled trial conducted in Ottawa and Vancouver. Women (N=57; Mage=48.8±10 years) diagnosed with stage I-III breast cancer and awaiting chemotherapy were randomized to aerobic exercise initiated with chemotherapy (nEX=28) or usual care during chemotherapy with aerobic exercise after chemotherapy completion (nUC=29). The intervention lasted 12-24 weeks and involved supervised aerobic training and at-home exercise. PROs were considered secondary outcomes and assessed via generic and disease-specific questionnaires. Analysis of covariance adjusting for baseline scores and pre-specified covariates (age, education, self-reported exercise) was used to compare PROs between groups post-intervention (commensurate with chemotherapy completion). Results: Post-intervention, EX reported lower CRF and higher QoL than UC; however, differences were not significant for any of the PROs after adjusting for baseline scores and covariates (p-values >0.05). Conclusions: Although observing that aerobic exercise during chemotherapy for breast cancer did not significantly improve CRF and QoL in the short-term compared to UC is surprising considering findings from previous reviews, we will discuss ideas that may explain these results and that could direct future research and intervention design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".