Long-Term Risk of Pancreatic Cancer After Acute Acetylcholinesterase Inhibitor Insecticide Exposure: A Nationwide Cohort Study
Bibliographic record
Abstract
This nationwide cohort study investigated whether a single episode of acute exposure to high-dose acetylcholinesterase (AChE) inhibitor insecticide is associated with an increased risk of pancreatic cancer. Data from the Korean National Health Insurance Service were analyzed. The case group (n = 938) included adults exposed to organophosphate or carbamate insecticide and the control group (n = 3752) was matched by age, sex, and socioeconomic status. Cox proportional hazards regression was used to calculate hazard ratios (HRs) and 95% confidence intervals. Kaplan–Meier curves with log-rank tests evaluated differences in pancreatic cancer incidence. Over 33,219.8 person-years of follow-up, pancreatic cancer developed in 9 patients in the case group and 19 patients in the control group. The cumulative incidence of pancreatic cancer was significantly higher in the case group (log-rank p < 0.01). Acute high-dose exposure to AChE inhibitor insecticide was associated with an increased risk of pancreatic cancer (adjusted HR: 2.57). The risk was particularly elevated among women (HR: 5.85) and individuals with diabetes (HR: 2.75). Acute high-dose exposure to AChE inhibitor insecticide may increase the risk of pancreatic cancer. Women and those with diabetes may represent high-risk subgroups. These findings highlight the need for targeted cancer surveillance and further confirmatory studies.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".