Nicotine dependence as a risk factor for upper aerodigestive tract (UADT) cancers: A mediation analysis
Bibliographic record
Abstract
PURPOSE: This study investigated nicotine dependence as an independent risk factor for upper aerodigestive tract (UADT) cancers, including lung and head and neck cancers (HNC). The study aimed to isolate the direct effect of nicotine dependence, independent of tobacco smoking. METHODS: A case-control study with a total of 4957 participants was conducted in Ontario, Canada, of which 2964 categorized as either current or former smokers were used in the analysis. Nicotine dependence of ever-smokers (2360 UADT cases and 604 controls) was measured using the Fagerström Test for Nicotine Dependence. Using mediation analyses and adjusted logistic regression models, we decomposed the direct effect of nicotine dependence and the mediated effect of smoking duration to quantify the risks of lung and HNC. The role of human papillomavirus (HPV) and cancer subtypes were assessed. RESULTS: Most individual nicotine dependence behaviours showed positive associations with lung cancer with approximately 1.8 to 3.5-fold risk increase, and to lesser extent with 1.4 to 2.3-fold risk for HNC. Nicotine dependence is partially accountable for increased risks of lung cancer (OR = 1.20, 95%CI = 1.13-1.28) and HNC (1.12, 95%CI = 1.04-1.19). Nicotine dependence had a greater effect on the risk of HPV-negative oropharyngeal cancer (OR = 3.06, 95%CI = 1.65-5.66) in comparison to HPV-positive oropharyngeal cancer (OR = 1.05, 95%CI = 0.67-1.65). The direct effects of nicotine dependence remained significant after accounting for cumulative tobacco exposures. CONCLUSION: Nicotine dependence increases the risks of lung and HNC cancers after accounting for tobacco smoking, suggesting potential toxic effects of nicotine. These results are informative for the safety consideration of nicotine exposures.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".