Diet and body mass, and oral and oropharyngeal squamous cell carcinomas: Analysis from the IARC multinational case–control study
Bibliographic record
Abstract
Tobacco and alcohol use are the main risk factors for oral and oropharyngeal cancers, yet, dietary habits may also be of importance. Data from a series of case-control studies conducted in 9 countries worldwide (1,670 cases and 1,732 controls) were used to investigate the role of several food groups and body mass index (BMI). Low BMI significantly increased the odds ratio (OR) of cancer more than 2-fold among ever- and never-tobacco users and ever- and never-alcohol drinkers. After adjustment for potential confounders, high intake of fruits and vegetables significantly reduced the OR of cancer compared to low intake among ever-tobacco users (OR 0.4, 95% confidence interval [CI] 0.3-0.6), although not among never-tobacco users (OR 1.1, 95% CI 0.6-2.0). Similarly, the protective effect of high fruit and vegetable consumption was present among ever-drinkers (OR 0.4, 95% CI 0.3-0.6), but not among never-drinkers (OR 1.0, 95% CI 0.6-1.6). In conclusion, low BMI increases the risk of oral cancer, and vegetables and fruits may modulate the carcinogenic effects of tobacco and alcohol.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".