Extranodal extension in N1-adenocarcinoma of the pancreas and papilla of Vater
Bibliographic record
Abstract
The aim of the study was to investigate the prognostic role of extranodal extension (ENE) of lymph node metastasis in adenocarcinoma of the pancreas (PDAC) and papilla [cancer of the papilla of Vater (CPV)]. A PubMed and SCOPUS search from database inception until 5 January 2015 without language restrictions was conducted. Eligible were prospective studies reporting data on prognostic parameters in individuals with PDAC and/or CPV, comparing participants with the presence of ENE (ENE+) with those with intranodal extension (ENE-). Data were summarized using risk ratios for number of deaths/recurrences and hazard ratios for time-dependent risk related to ENE+, adjusted for potential confounders. ENE was found to be very common in these tumors (up to about 60% in both N1-PDAC and CPV), leading to a significant increased risk for all-cause mortality [risk ratio=1.20; 95% confidence interval (CI): 1.06-1.35, P=0.003, I(2)=44%; hazard ratio=1.415, 95% CI: 1.215-1.650, P<0.0001, I(2)=0%] and recurrence of disease (risk ratio=1.20, 95% CI: 1.03-1.40, P=0.02, I(2)=0%). On the basis of our results, in PDAC and CPV, ENE should be considered mandatorily from the gross sampling and pathology report to the oncologic staging and therapeutic approach.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".