Aetiological heterogeneity of head and neck squamous cell carcinomas: the role of human papillomavirus infections, smoking and alcohol
Bibliographic record
Abstract
Tobacco and alcohol consumption are the main risk factors for head and neck squamous cell carcinoma (HNSCC). In addition, human papillomavirus (HPV) infection plays a causal role in oropharyngeal cancer (OPC), a subset of HNSCC. We assessed the independent effects of tobacco, alcohol and HPV infection on OPC risk in the head and neck cancer (HeNCe) Life study, a hospital-based case-control study of HNSCC with frequency-matched controls by age and sex from four Montreal hospitals. Interviewers collected information on socio-demographic and behavioural factors. We tested exfoliated oral cells for HPV DNA by polymerase chain reaction (PCR). We included only OPC cases (n = 188) and controls (n = 427) without missing values for HPV, smoking or alcohol. We examined associations by estimating odds ratios (ORs) and corresponding 95% confidence intervals (CI) using unconditional logistic regression. Smoking (OR = 1.90, 95% CI: 1.04-3.45) and alcohol (OR = 2.74, 95% CI: 1.45-5.15) were associated with an increased risk of OPC independent of HPV status. Positivity for HPV 16 among heavy smokers and heavy alcohol users was associated with a 30.4-fold (95% CI: 8.94-103.26) and 18.6-fold (95% CI: 5.75-60.13) elevation in risk of OPC relative to participants who were HPV negative, respectively. Moreover, the combined effect of heavy smoking and alcohol comsumption with HPV 16 infection substantially increased OPC risk (OR = 48.76, 95% CI: 15.83-150.17) and (OR = 50.60, 95% CI: 15.96-160.40), respectively. Our results support the independent roles of smoking, alcohol and HPV infection in OPC risk and a possible combined effect. Efforts should be made to tackle these major risk factors simultaneously.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".