Anthropometry and head and neck cancer:a pooled analysis of cohort data
Bibliographic record
Abstract
BACKGROUND: Associations between anthropometry and head and neck cancer (HNC) risk are inconsistent. We aimed to evaluate these associations while minimizing biases found in previous studies. METHODS: We pooled data from 1,941,300 participants, including 3760 cases, in 20 cohort studies and used multivariable-adjusted Cox proportional hazard regression models to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association of anthropometric measures with HNC risk overall and stratified by smoking status. RESULTS: Greater waist circumference (per 5 cm: HR = 1.04, 95% CI 1.03-1.05, P-value for trend = <0.0001) and waist-to-hip ratio (per 0.1 unit: HR = 1.07, 95% CI 1.05-1.09, P-value for trend = <0.0001), adjusted for body mass index (BMI), were associated with higher risk and did not vary by smoking status (P-value for heterogeneity = 0.85 and 0.44, respectively). Associations with BMI (P-value for interaction = <0.0001) varied by smoking status. Larger BMI was associated with higher HNC risk in never smokers (per 5 kg/m(2): HR = 1.15, 95% CI 1.06-1.24, P-value for trend = 0.0006), but not in former smokers (per 5 kg/m(2): HR = 0.99, 95% CI 0.93-1.06, P-value for trend = 0.79) or current smokers (per 5 kg/m(2): HR = 0.76, 95% CI 0.71-0.82, P-value for trend = <0.0001). Larger hip circumference was not associated with a higher HNC risk. Greater height (per 5 cm) was associated with higher risk of HNC in never and former smokers, but not in current smokers. CONCLUSIONS: Waist circumference and waist-to-hip ratio were associated positively with HNC risk regardless of smoking status, whereas a positive association with BMI was only found in never smokers.
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How this classification was reachedexpand
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".