Factors associated with quality of life in outpatients with head and neck cancer 6 months after diagnosis
Bibliographic record
Abstract
BACKGROUND: Identifying patients with head and neck cancer at greatest risk of poor health-related quality of life (HRQOL) will facilitate screening for such patients and targeted interventions. METHODS: This was a cross-sectional, self-administered survey with medical record review among 65 out-patients with head and neck cancer >6 months from diagnosis and off treatment. RESULTS: Most were men (80%) and white (95%), with a mean age of 60 +/- 13 years. The most prevalent cancer type was squamous cell (88%), site was pharyngeal (40%), and stage was III or IV (80%). Lower total HRQOL was independently associated with gastrostomy (p < .001) and history of radiation therapy (p < .05)(R(2) = 0.27). Certain HRQOL subscales were also independently associated with depression, body mass index, age, and education. CONCLUSIONS: Several factors can be used to identify patients with head and neck cancer at risk for persistent reductions in HRQOL requiring intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".