The Impact of Positive Resection Margins on Survival and Recurrence Following Resection and Adjuvant Chemotherapy for Pancreatic Ductal Adenocarcinoma
Bibliographic record
Abstract
OBJECTIVE AND BACKGROUND: Local and distant disease recurrence are frequently observed following pancreatic cancer resection, but an improved understanding of resection margin assessment is required to aid tailored therapies. METHODS: Analyses were carried out to assess the association between clinical characteristics and margin involvement as well as the effects of individual margin involvement on site of recurrence and overall and recurrence-free survival using individual patient data from the European Study Group for Pancreatic Cancer (ESPAC)-3 randomized controlled trial. RESULTS: There were 1151 patients, of whom 505 (43.9%) had an R1 resection. The median and 95% confidence interval (CI) overall survival was 24.9 (22.9-27.2) months for 646 (56.1%) patients with resection margin negative (R0 >1 mm) tumors, 25.4 (21.6-30.4) months for 146 (12.7%) patients with R1<1 mm positive resection margins, and 18.7 (17.2-21.1) months for 359 (31.2%) patients with R1-direct positive margins (P < 0.001). In multivariable analysis, overall R1-direct tumor margins, poor tumor differentiation, positive lymph node status, WHO performance status ≥1, maximum tumor size, and R1-direct posterior resection margin were all independently significantly associated with reduced overall and recurrence-free survival. Competing risks analysis showed that overall R1-direct positive resection margin status, positive lymph node status, WHO performance status 1, and R1-direct positive superior mesenteric/medial margin resection status were all significantly associated with local recurrence. CONCLUSIONS: R1-direct resections were associated with significantly reduced overall and recurrence-free survival following pancreatic cancer resection. Resection margin involvement was also associated with an increased risk for local recurrence.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".