Clinical and radiological predictive features for high‐grade and invasive carcinoma in intraductal papillary mucinous neoplasms: A systematic review
Bibliographic record
Abstract
BACKGROUND/PURPOSE: Intraductal papillary mucinous neoplasms (IPMNs) progress from low-grade dysplasia to high-grade dysplasia (HGD) or invasive carcinoma (IC). High diagnostic accuracy is critical for surgical decision-making. METHODS: We searched Medline, Embase, and Cochrane Library from January 1, 2015, to January 27, 2025. Eligible studies reported on resected IPMNs, assessing diagnostic features for HGD/IC. Two reviewers screened articles, extracted data, and assessed bias using the Newcastle-Ottawa scale. Descriptive statistics summarized outcomes. The performance of worrisome features (WFs) and high-risk stigmata (HRS) based on International Association of Pancreatology guidelines were evaluated. RESULTS: In the 53 studies, 12 953 patients were included. HRS including obstructive jaundice and enhancing mural nodules ≥5mm showed robust specificity for HGD/IC, while main pancreatic duct size ≥10mm showed variable diagnostic accuracy. WFs such as cyst size ≥3 cm performed poorly, while cyst growth rate >3.5 mm/year demonstrated higher sensitivity (88%) and specificity (91%). Although rare, abrupt caliber change with distal atrophy was a robust predictor of malignancy (median odds ratio: 3.01). Acute pancreatitis and lymphadenopathy displayed variable value. Incremental improvement in diagnostic accuracy was observed with additional HRS or WFs. CONCLUSIONS: Current diagnostic markers are valuable but provide limited guidance for surgical decision-making in IPMNs, highlighting the need for further refinement of diagnostic tools.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".