Alcohol and Tobacco Use Prediagnosis and Postdiagnosis, and Survival in a Cohort of Patients with Early Stage Cancers of the Oral Cavity, Pharynx, and Larynx
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As more people begin to survive first cancers, there is an increased need for science-based recommendations to improve survivorship. For survivors of head and neck cancer, use of tobacco and alcohol before diagnosis predicts poorer survival; however, the role of continuing these behaviors after diagnosis on mortality is less clear, especially for more moderate alcohol consumption. Patients (n = 264) who were recent survivors of early stage head and neck cancer were asked to retrospectively report their tobacco and alcohol histories (before diagnosis), with information prospectively updated annually thereafter. Patients were followed for an average of 4.2 years, with 62 deaths observed. Smoking history before diagnosis dose-dependently increased the risk of dying; risks reached 5.4 [95% confidence interval (95% CI), 0.7-40.1] among those with >60 pack-years of smoking. Likewise, alcohol history before diagnosis dose-dependently increased mortality risk; risks reached 4.9 (95% CI, 1.5-16.3) for persons who drank >5 drinks/d, an effect explained by beer and liquor consumption. After adjusting for prediagnosis exposures, continued drinking (average of 2.3 drinks/d) postdiagnosis significantly increased risk (relative risk for continued drinking versus no drinking, 2.7; 95% CI, 1.2-6.1), whereas continued smoking was associated with nonsignificantly higher risk (relative risk for continued smoking versus no smoking, 1.8; 95% CI, 0.9-3.9). Continued drinking of alcoholic beverages after an initial diagnosis of head and neck cancer adversely affects survival; cessation efforts should be incorporated into survivorship care of these patients.
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.
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 | 0.001 | 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 | 0.001 |
| 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 it