Risk Factors for Early-Onset and Very-Early-Onset Pancreatic Adenocarcinoma
Bibliographic record
Abstract
OBJECTIVES: While pancreatic cancer (PC) most often affects older adults, to date, there has been no comprehensive assessment of risk factors among PC patients younger than 60 years. METHODS: We defined early-onset PC (EOPC) and very-early-onset PC (VEOPC) as diagnosis of PC in patients younger than 60 and 45 years, respectively. We pooled data from 8 case-control studies, including 1954 patients with EOPC and 3278 age- and sex-matched control subjects. Logistic regression analysis was performed to identify associations with EOPC and VEOPC. RESULTS: Family history of PC, diabetes mellitus, smoking, obesity, and pancreatitis were associated with EOPC. Alcohol use equal to or greater than 26 g daily also was associated with increased risk of EOPC (odds ratio, 1.49; 95% confidence interval, 1.21-1.84), and there appeared to be a dose- and age-dependent effect of alcohol on risk. The point estimate for risk of VEOPC was an odds ratio of 2.18 (95% confidence interval, 1.17-4.09). CONCLUSIONS: The established risk factors for PC, including smoking, diabetes, family history of PC, and obesity, also apply to EOPC. Alcohol intake appeared to have an age-dependent effect; the strongest association was with VEOPC.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".