Neoadjuvant therapy in borderline resectable pancreatic ductal adenocarcinoma: A single institution review
Bibliographic record
Abstract
Objectives: Margin negative (R0) resection is the only known curative therapy for Pancreatic Ductal Adenocarcinoma (PDA), but only 20% of cases are resectable. Neoadjuvant therapy (NATx) in borderline resectable PDA may increase chance for R0 resection and improve overall survival (OS). Methods: We retrospectively identified 52 patients with borderline resectable PDA based on radiologic findings of clear celiac axis margins and no distant disease with local involvement of the superior mesenteric vein, portal vein, hepatic artery, gastroduodenal artery , or superior mesenteric artery ≤180 degrees. Results: Patients were grouped based on NATx and resection history: 17 (33%) NATx and resection (NATxR), 22 (42%) NATx without resection (NATxO), and 13 (25%) upfront resection (UR). Comparison of pathologic vs. clinical stage demonstrated a 41% rate of pathologic downstaging in the NATxR group vs. 77% rate of clinical under staging in the UR group. Median lymph node ratio (number of positive nodes vs. total number of nodes harvested), was lower in the NATxR vs. UR group (0% vs. 12.5%). R0 resection correlated with NATx (NATxR 71% vs. UR 31%; p = .003). Radiation therapy during NATx was associated with an even higher R0 resection rate (82% vs. 25%; p = .05). Median OS in months was highest in the NATxR group (40.7) vs. UR (22.8), and lowest in unresected patients (13.4) ( p = .0002). Conclusions: NATx in borderline resectable PDA can abate disease progression and increase chance of R0 resection. NATxR and surgical resection leads to the best OS in this analysis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".