S79 Systematic Review on the Prevalence of Pancreatitis as a Risk Factor to Pancreatic Cancer
Bibliographic record
Abstract
Introduction: Pancreatic cancer (PC) is the third leading cause of cancer-related death in Canada. Limited information exists on the role of pancreatitis as a risk factor for PC. This systematic review aims to evaluate the relationship between a history of pancreatitis and the risk of developing PC. Methods: We searched MEDLINE, EMBASE, CENTRAL, and Web of Science databases from inception to January 2024 for case-control studies reporting the prevalence of acute or chronic pancreatitis in adult patients with pancreatic cancers, including pancreatic ductal adenocarcinomas (PDACs), intraductal papillary mucinous neoplasms (IPMNs), and other subtypes. Screening, data extraction, and risk of bias assessments were performed independently by 2 authors. Results: A total of 22 studies, encompassing 412,082 patients (48,603 PC cases and 363,479 controls), were included. The hazard ratio (HR) for developing PC in patients with a history of acute or chronic pancreatitis was 3.62 (95% CI:3.50-3.74), indicating a moderately increased risk. Studies focusing on PDAC patients (n=6) showed similar findings [HR 3.95 (95% CI:3.78-4.13)], whereas those examining IPMN patients (n=2) did not find a significant difference [HR 0.98 (95% CI:0.84-1.16)]. Twelve studies did not specify the PC type but also demonstrated a moderate association [HR 3.18(95% CI:3.00-3.37)]. These findings were consistent when stratified by age and gender. The overall risk of bias in the studies ranged from low to moderate, with most concerns related to the lack of confounder analysis and incomplete protocols. Conclusion: Current literature indicates a moderate association between pancreatitis and pancreatic cancer, consistent across gender and age subgroups. Further detailed reporting on the characteristics of acute pancreatitis, hospitalization rates, and comprehensive confounder analyses are necessary to strengthen the evidence base regarding this relationship.
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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 | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".