Baseline and lifetime alcohol consumption and risk of skin cancer in the European Prospective Investigation into Cancer and Nutrition cohort (<scp>EPIC</scp>)
Bibliographic record
Abstract
Abstract Experimental evidence suggests that alcohol induces cutaneous carcinogenesis, yet epidemiological studies on the link between alcohol intake and skin cancer have been inconsistent. The European Prospective Investigation into Cancer and Nutrition (EPIC) is a prospective cohort initiated in 1992 in 10 European countries. Alcohol intake at baseline and average lifetime alcohol intake were assessed using validated country‐specific dietary and lifestyle questionnaires. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated in Cox models. A total of 14 037 skin cancer cases (melanoma: n = 2457; basal‐cell carcinoma (BCC): n = 8711; squamous‐cell carcinoma (SCC): n = 1928; unknown: n = 941) were identified among 450 112 participants (average follow‐up: 15 years). Baseline alcohol intake was positively associated with SCC (>15 vs 0.1‐4.9 g/day: HR = 1.44, 95% CI = 1.17‐1.77; P trend = .001), BCC (HR = 1.12, 95% CI = 1.01‐1.23; P trend = .04), and melanoma risks in men (HR = 1.17, 95% CI = 0.95‐1.44; P trend = .17), while associations were more modest in women (SCC: HR = 1.09, 95% CI = 0.90‐1.30; P trend = .13; BCC: HR = 1.08, 95% CI = 1.00‐1.17, P trend = .03; melanoma: HR = 0.93, 95% CI = 0.80‐1.08, P trend = .13). Associations were similar for lifetime alcohol intake, with an attenuated linear trend. Lifetime liquor/spirit intake was positively associated with melanoma (fourth vs first quartile: HR = 1.47, 95% CI = 1.08‐1.99; P trend = .0009) and BCC risks in men (HR = 1.17, 95% CI = 1.04‐1.31; P trend = .14). Baseline and lifetime intakes of wine were associated with BCC risk (HR = 1.25 in men; HR = 1.11‐1.12; in women). No statistically significant associations were found between beverage types and SCC risk. Intake of beer was not associated with skin cancer risk. Our study suggests positive relationships between alcohol intake and skin cancer risk, which may have important implications for the primary prevention of skin cancer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".