Patient‐reported outcomes, body composition, and nutrition status in patients with head and neck cancer: Results from an exploratory randomized controlled exercise trial
Bibliographic record
Abstract
BACKGROUND: Patients with head and neck cancer experience loss of weight and muscle mass, decreased functioning, malnutrition, depression, and declines in quality of life during and after treatment. The purpose of this exploratory randomized study was to determine the optimal timing for the initiation of a lifestyle and progressive resistance exercise training intervention (during or after radiation therapy), as determined by intervention adherence and by comparing between-group outcomes across 24 weeks. METHODS: Sixty patients with head and neck cancer were randomized to engage in a 12-week lifestyle intervention and progressive resistance-training program either during radiation treatment or immediately after completion. The primary outcome of body composition--specifically, lean body mass, body mass index, and body fat--as well as secondary outcomes of fitness, quality of life, depression, and nutrition status were evaluated. RESULTS: The progressive resistance-training intervention carried out during treatment did not significantly influence the primary outcome of body composition, despite a significant increase in weekly physical activity reported by the intervention group. A small-to-medium intervention effect was noted for some secondary outcomes, including fitness, quality of life, and nutrition status. Regardless of whether patients received the immediate or delayed progressive resistance-training intervention, the analysis revealed a main effect of time on body composition, fitness, quality of life, depression, and nutritional scores. CONCLUSIONS: Although the intervention during treatment did not reduce the loss of lean body mass, delaying the exercise program until after treatment completion was associated with improved intervention adherence, a finding with important clinical implications.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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; 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".