Head and neck cancer patients declining curative treatment: a case series and literature review
Bibliographic record
Abstract
There is a scarcity of data assessing outcomes of head and neck cancer patients who refuse treatment for potentially curable disease. We report the data of patients who refused curative treatment at a tertiary referral centre and perform a review of the literature. Patients with a potentially curable mucosal head and neck cancers that were discussed at the multidisciplinary tumour board of a referral centre in a two-year period were included. Two cohorts were obtained: patients who accepted the proposed treatment and those who declined it. Statistical analysis was performed using a univariate analysis with parametric and non-parametric tests. Of a total of 803 patients, 14 (1.74%) refused treatment despite being potentially curable. Their median survival was 6.92 months (range 3-12). Patients who refused treatment were older (73.07 years [95% CI, 66.86-79.28] vs 65.56 years [95% CI, 64.70-66.43], p = 0.030) and more likely to have T4 disease (50% vs 26.04%, p = 0.044). Most patients with curable disease accept conventional treatment and those who refuse it experience dismal outcomes. This report provides objective evidence and can be employed to better counsel patients who refuse curative treatment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".