Prediagnostic Plasma C-Peptide and Pancreatic Cancer Risk in Men and Women
Bibliographic record
Abstract
BACKGROUND: Hyperinsulinemia and insulin resistance have been proposed as underlying mechanisms for the increase in pancreatic cancer among long-standing diabetics and obese individuals. An association between serum insulin levels and pancreatic cancer risk was reported in a recent study, but the population was composed of heavy smokers and their findings may not be generalizable to nonsmokers. METHODS: Pancreatic cancer cases and matched controls were obtained from four large-scale prospective cohorts to examine the association between prediagnostic plasma levels of C-peptide and insulin and pancreatic cancer. One hundred ninety-seven pancreatic cancer cases were diagnosed during a maximum of 20 years of follow-up, after excluding cases diagnosed within 2 years of blood collection or with baseline diabetes. We estimated OR and confidence intervals (CI) using conditional logistic regression with adjustment for pancreatic cancer risk factors. RESULTS: Prediagnostic plasma C-peptide was positively associated with pancreatic cancer risk (OR, 1.52; 95% CI, 0.87-2.64, highest compared with the lowest quartile, P(trend) = 0.005). The association was not modified by body mass index or physical activity but seemed to be slightly stronger among never smokers than ever smokers. Fasting C-peptide and insulin were not related to pancreatic cancer; however, we observed a strong linear association for nonfasting C-peptide and pancreatic cancer (OR, 4.24; 95% CI, 1.30-13.8, highest versus lowest quartile, P(trend) < 0.001). CONCLUSIONS: Based on our finding of a strong positive association with nonfasting C-peptide levels, we propose that insulin levels in the postprandial state may be the relevant exposure for pancreatic carcinogenesis; however, other studies will need to examine this possibility.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".