Effects of Semisupervised Exercise Training on Health Outcomes in People With Lung or Head and Neck Cancer: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Lung or head and neck cancers are known for their high prevalence and mortality rates. Chemotherapy and radiotherapy are usually recommended as cancer treatment for these malignancies; however, they can negatively impact both the physical and mental status of patients. Hence, it is reasonable to consider resistance and aerobic exercise training to prevent these negative health outcomes. Further, several factors prevent patients from attending outpatient exercise training programs, and, therefore, a semisupervised home-based exercise training program may be seen as a well-accepted alternative. OBJECTIVE: The aim of this study will be to investigate the effects of a semisupervised home-based exercise training program on physical performance, body composition, and self-reported outcomes; changes in the initial cancer treatment dose prescribed; number of hospitalizations at 3, 6, and 9 months; and 12-month survival in people with primary lung or head and neck cancer. METHODS: Participants will be randomly allocated to the training group (TG) or control group (CG). The TG will undergo semisupervised home-based resistance and aerobic exercise training throughout their cancer treatment. The resistance training will be performed using elastic bands (TheraBand) twice a week. The aerobic training (ie, brisk walk) will be performed for at least 20 minutes per day outdoors. The equipment and tools used during the training sessions will be provided. This intervention will start the week before treatment commencement, will be performed throughout the duration of the treatment, and will continue for 2 weeks after treatment completion. The CG will undergo usual care (ie, cancer treatment with no formal exercise prescription). Assessments will take place 2 weeks before the beginning of the usual cancer treatment and 2 weeks after treatment completion. The measures of physical function (peripheral muscle strength, functional exercise capacity, and physical activity), body composition, and self-reported outcomes (symptoms of anxiety and depression, health-related quality of life, and symptoms related to the disease and treatment) will be collected. We will report on any change in the initial cancer treatment dose prescribed; number of hospitalizations at 3, 6, and 9 months; and 12-month survival. RESULTS: In February 2021, the clinical trial registration was approved. Recruitment and data collection for the trial are ongoing (as of April 2023, 20 participants had already been randomized), and findings of this study are likely to be published late in 2024. CONCLUSIONS: This exercise training as a complementary treatment for patients with cancer is likely to promote positive effects on the health outcomes assessed, over and above any change in the CG, and prevent the reduction of initial cancer treatment dose prescribed. If these positive effects are shown, they will likely impact long-term outcomes such as hospitalizations and 12-month survival. TRIAL REGISTRATION: Brazilian Clinical Trials Registry (ReBEC) RBR-5cyvzh9; https://ensaiosclinicos.gov.br/rg/RBR-5cyvzh9. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/43547.
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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 | 0.032 | 0.030 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.009 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.070 | 0.011 |
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".