Novel Methods for Reporting of Exercise Dose and Adherence: An Exploratory Analysis
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to explore whether methods adapted from oncology pharmacological trials have utility in reporting adherence (tolerability) of exercise treatment in cancer. METHODS: Using a retrospective analysis of a randomized trial, 25 prostate cancer patients received an aerobic training regimen of 72 supervised treadmill walking sessions delivered thrice weekly between 55% and 100% of exercise capacity for 24 consecutive weeks. Treatment adherence (tolerability) was assessed using conventional (lost to follow-up and attendance) and exploratory (e.g., permanent discontinuation, dose modification, and relative dose intensity) outcomes. RESULTS: The mean total cumulative "planned" and "completed" dose was 200.7 ± 47.6 and 153.8 ± 68.8 MET·h, respectively, equating to a mean relative dose intensity of 77% ± 24%. Two patients (8%) were lost to follow-up, and mean attendance was 79%. A total of 6 (24%) of 25 patients permanently discontinued aerobic training before week 24. Aerobic training was interrupted (missing ≥3 consecutive sessions) or dose reduced in a total of 11 (44%) and 24 (96%) patients, respectively; a total 185 (10%) of 1800 training sessions required dose reduction owing to both health-related (all nonserious) and non-health-related adverse events. Eighteen (72%) patients required at least one session to be terminated early; a total of 59 (3%) sessions required early termination. CONCLUSIONS: Novel methods for the conduct and reporting of exercise treatment adherence and tolerability may provide important information beyond conventional metrics in patients with 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 | 0.279 | 0.451 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".