Intraoperative Positive Pancreatic Parenchymal Resection Margin: Is It a True Indication of Completion Total Pancreatectomy after Partial Pancreatectomy for Pancreatic Ductal Adenocarcinoma?
Bibliographic record
Abstract
Background: Total pancreatectomy (TP) can be performed in cases with positive resection margin after partial pancreatectomy for pancreatic cancer. However, despite complete removal of the residual pancreatic parenchyme, it is questionable whether an actual R0 resection and favorable survival can be achieved. This study aimed to identify the R0 resection rate and postoperative outcomes, including survival, following completion TP (cTP) performed due to intraoperative positive margin. Methods: From 1995 to 2015, 1096 patients with pancreatic ductal adenocarcinoma underwent elective pancreatectomy at the Samsung Medical Center. Among these, 25 patients underwent cTP, which was converted during partial pancreatectomy because of a positive resection margin. To compare survival after R0 resection between the cTP R0 and pancreaticoduodenectomy (PD) R0 cases, propensity score matching was conducted to balance the baseline characteristics. Results: The R0 rate of cTP performed due to intraoperative positive margin was 84% (21/25). The overall 5-year survival rate (5YSR) in the 25 cTP cases was 8%. There was no difference in the 5YSR between the cTP R0 and cTP R1 groups (9.5% versus 0.0%, p = 0.963). However, the 5YSR of the cTP R0 group was significantly lower than that of the PD R0 group (9.5% versus 20.0%, p = 0.022). There was no distinct difference in postoperative complications between the cTP R0 versus cTP R1 and cTP R0 versus PD R0 groups. Conclusions: In cases with intraoperative positive pancreatic parenchymal resection margin, survival after cTP was not favorable. Careful patient selection is needed to perform cTP in such cases.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".