Association between Allergies and Risk of Pancreatic Cancer
Bibliographic record
Abstract
BACKGROUND: Less than 10% of pancreatic cancer cases survive 5 years, yet its etiology is not well understood. Studies suggest allergies are associated with reduced pancreatic cancer risk. Our study collected additional information on allergies (including skin prick test results and differentiation of allergic/nonallergic asthma), and is the first to assess possible confounding by allergy medications. METHODS: A population-based case-control study was designed to comprehensively assess the association between allergy and pancreatic cancer risk. Pancreas cancer cases were diagnosed during 2011 to 2012, and identified through the Ontario Cancer Registry (345 cases). Population-based controls were identified using random digit dialing and age/sex frequency matched to cases (1,285 controls). Questionnaires collected lifetime allergy history (type of allergy, age at onset, skin prick testing results), allergy medications, and established pancreas cancer risk factors. Logistic regression was used to estimate odd ratios and test potential confounders, including allergy medications. RESULTS: Hay fever was associated with a significant reduction in pancreatic cancer risk [AOR = 0.68; 95% confidence intervals (CI), 0.52-0.89], and reduction was greatest for those whose skin prick test was positive for hay fever allergens. No particular patterns were observed as regards age at onset and duration of allergy. Positive dust/mold allergy skin prick test and animal allergies were associated with a statistically significant reduced pancreatic cancer risk; AOR = 0.49; 95% CI, 0.31-0.78 and AOR = 0.68; 95% CI, 0.46-0.99, respectively. Asthma was not associated with pancreatic cancer risk. CONCLUSIONS/IMPACT: These findings support the growing body of evidence that suggests certain allergies are associated with reduced pancreatic cancer risk.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".