Association between smoking during radiotherapy and prognosis in head and neck cancer: A follow‐up study
Bibliographic record
Abstract
BACKGROUND: The study objective was to confirm a previous finding that patients with stage III/IV squamous head and neck cancer (SHNC) who smoke during radiotherapy (RT) experience reduced survival. METHODS: An observational cohort study. Patients' smoking status was assessed weekly by questionnaire plus blood cotinine. Patients were assessed every 3 to 4 months for survival. Logistic regression and Cox proportional hazards analyses were used to detect the independent contribution of smoking on survival. RESULTS: Of 148 patients, 113 smoked during RT. Blood cotinine and smoking questionnaire responses were highly correlated (Spearman R = .69; p < .0005). Abstainers and very light smokers experienced better survival than light, moderate, and heavy smokers (median, 42 vs 29 months; p = .07). Tumor and nodal status and years smoked were the most important prognostic factors. Smoking during RT was not an independent predictor of survival, but baseline smoking status was (p = .016). CONCLUSION: Smoking status should be documented in all future trials of RT in SHNC to allow for pooled analyses with sufficient power to address this question.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".