Exercise and nutrition for head and neck cancer patients: a patient oriented, clinic-supported randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Research on physical activity and nutrition interventions aimed at positively impacting symptom management, treatment-related recovery and quality of life has largely excluded head and neck (HN) cancer populations. This translates into a lack of clinical programming available for these patient populations. HN cancer patients deal with severe weight loss, with more than 70% attributed to lean muscle wasting, leading to extended recovery times, decreased quality of life (QoL), and impaired physical functioning. To date, interventions to address body composition issues have focused solely on diet, despite findings that nutritional therapy alone is insufficient to mitigate changes. A combined physical activity and nutrition intervention, that also incorporates important educational components known to positively impact behaviour change, is warranted for this population. Our pilot work suggests that there is large patient demand and clinic support from the health care professionals for a comprehensive program. METHODS/DESIGN: Therefore, the purpose of the present study is to examine the impact and timing of a 12-week PA and nutrition intervention (either during or following treatment) for HN cancer patients on body composition, recovery, serum inflammatory markers and quality of life. In addition, we will examine the impact of a 12-week maintenance program, delivered immediately following the intervention, on adherence, patient-reported outcomes (i.e., management of both physical and psychosocial treatment-related symptoms and side-effects), as well as return to work. DISCUSSION: This research will facilitate advancements in patient wellness, survivorship, and autonomy, and carve the path for a physical-activity and wellness-education model that can be implemented in other cancer centers. TRIAL REGISTRATION: Current Controlled Trials NCT01681654.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".