Patient Choice of Nonsurgical Treatment Contributes to Disparities in Head and Neck Squamous Cell Carcinoma
Bibliographic record
Abstract
Objectives There are well-established outcome disparities among different demographic groups with head and neck squamous cell carcinoma (HNSCC). We aimed to investigate the potential contribution of patient choice of nonsurgical treatment to these disparities by estimating the rate of this phenomenon, identifying its predictors, and estimating the effect on cancer-specific survival. Study Design Retrospective nationwide analysis. Settings Surveillance, Epidemiology, and End Results Database (2004-2014). Subjects and Methods Patients with HNSCC, who were recommended for primary surgery, were included. Multivariable logistic regression was used to identify demographic and clinical factors associated with patient choice of nonsurgical treatment, and Kaplan Meier/Cox regression was used to analyze survival. Results Of 114,506 patients with HNSCC, 58,816 (51.4%) were recommended for primary surgery, and of those, 1550 (2.7%) chose nonsurgical treatment. Those who chose nonsurgical treatment were more likely to be older (67.1 ± 12.6 vs 63.6 ± 13.1, P < .01), were of Black (odds ratio [OR], 1.49; 95% confidence interval [CI], 1.28-1.74) or Asian (OR = 1.79; 95% CI, 1.46-2.20) ethnicity, were unmarried (OR married, 0.50; 95% CI, 0.44-0.58), had an advanced tumor, and had a hypopharyngeal or laryngeal primary. Choice of nonsurgical treatment imparted a 2.16-fold (95% CI, 2.02-2.30) increased risk of cancer-specific death. Conclusion Of the patients, 2.7% chose nonsurgical treatment despite a provider recommendation that impairs survival. Choice of nonsurgical treatment is associated with older age, having Black or Asian ethnicity, being unmarried, having an advanced stage tumor, and having a primary site in the hypopharynx or larynx. Knowledge of these disparities may help providers counsel patients and help patients make informed decisions.
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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".