QOL-29. Evaluating the effectiveness of a tailored exercise intervention on neuro-oncology patient outcomes
Bibliographic record
Abstract
Abstract Despite the known benefits of exercise as a supportive cancer care resource, evidence of its effectiveness in neuro-oncology is scarce and thus access to programming remains limited. This study evaluated the effectiveness of a tailored neuro-oncology exercise intervention on patient outcomes – the Alberta Cancer Exercise-Neuro Oncology (i.e., ACE-Neuro) study. ACE-Neuro was a multi-site type II effectiveness-implementation trial delivered in Alberta, Canada and included a 12-week tailored exercise and health coaching intervention to adult neuro-oncology patients. Measures included baseline and 12-week patient-reported outcomes and functional fitness, acute energy and fatigue assessed pre-/post-exercise sessions, and objective physical activity assessed across the intervention via a Garmin activity tracker. Descriptive statistics and linear mixed models were used to analyze the data. Across a 20-month recruitment period, n=62 participants were scheduled to begin the intervention, and n=51 completed (82.3%). Statistically significant improvements were observed for overall quality of life (p < 0.011) and the sub-domains of functional well-being (p < 0.018) and brain-specific concerns (p < 0.001). Resistance exercise levels (p < 0.005), balance (p < 0.009 right side and p < 0.002 left side), and aerobic fitness (p < 0.001) also significantly improved. General fatigue worsened from pre- to post-intervention (p < 0.048). Acute energy significantly worsened after each exercise session (p = 0.001) but significantly improved from baseline to 12-weeks (p < 0.001), while acute fatigue significantly improved across the intervention (p < 0.001). Objective physical activity during the intervention averaged 86.6 ± 57.51 minutes per day. ACE-Neuro was associated with improved patient-reported, functional fitness, and objective physical activity outcomes, contributing to the limited literature on exercise interventions in neuro-oncology. Ongoing work is needed to continue to tailor and deliver effective exercise interventions that meet the unique needs of this patient population.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".