The Population-Level Prevalence of Exocrine Pancreas Insufficiency and the Subsequent Risk of Pancreatic Cancer
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to study the prevalence of exocrine pancreas insufficiency (EPI) at a population level and the subsequent risk of pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS: Using TriNetX (a database of over 79 million US residents), we included patients ≥18 years with EPI (identified via ICD-10 codes) and continuous follow-up from 2016-2022. Patients with prior pancreas resection and PDAC before an EPI diagnosis were excluded. The primary outcome was EPI prevalence. Secondary outcomes included imaging utilization, PDAC risk, and pancreatic enzyme replacement therapy (PERT) utilization. We performed 1:1 propensity score matching (PSM) of patients with EPI versus patients without an EPI diagnosis. RESULTS: The population prevalence of EPI was 0.8% (n = 24,080) with a mean age of 55.6 years. After PSM, PDAC risk among patients with EPI was twice as high compared with patients without EPI (aHR, 1.97; 95% CI, 1.66-2.36). This risk persisted even after excluding patients with a history of acute or chronic pancreatitis (adjusted odds ratio, 4.25; 95% CI, 2.99-6.04). Only 58% (n = 13, 390) of patients with EPI received PERT. No difference was observed in PDAC risk between patients with EPI on PERT and those not on PERT (aHR, 1.10; 95% CI, 0.95-1.26; P = 0.17). CONCLUSIONS: Despite a low prevalence, patients with EPI may have a higher risk of PDAC, and majority with EPI were not on PERT. PERT did not impact incident PDAC risk after an EPI diagnosis.
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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 | 0.001 | 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 | 0.001 |
| 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".