The impact of physical activity on health-related fitness and quality of life for patients with head and neck cancer: a systematic review
Bibliographic record
Abstract
BACKGROUND: Patients with head and neck cancer often face a plethora of cancer and treatment-related side effects, negatively impacting their lean body mass, physical functioning, quality of life and fatigue management. Physical activity is a potential mediator of many of these side effects. This is the first systematic review reporting on head and neck cancer and physical activity literature. METHODS: A literature search was conducted up to January 2015. Two reviewers independently identified articles using the outlined inclusion criteria, assessing the study methodology, risk of bias and extracting the necessary data from studies evaluating the impact of full-body physical activity on patients with head and neck cancer. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement was used to guide this review. RESULTS: We identified 16 articles published from 2003 to 2014, the majority of which were published within the past 5 years. Physical activity interventions were feasible, safe and beneficial in mediating cancer and treatment-related side effects. Specifically, patients experienced improvements in lean body mass, muscular strength, physical functioning, quality of life and fatigue management. Owing to significant study heterogeneity, data were not pooled. Reflecting the early state of the literature, included studies were found to vary greatly in design, quality and reporting characteristics. CONCLUSIONS: There is early evidence that supports the benefit of physical activity interventions for patients with head and neck cancer, both during and following treatment. Future research is necessary to determine the benefits of different physical activity interventions, and their impact on patients with different head and neck cancers.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".