Impact of Neoadjuvant Therapy for Pancreatic Cancer: Transatlantic Trend and Postoperative Outcomes Analysis.
Bibliographic record
Abstract
BACKGROUND: The introduction of modern chemotherapy a decade ago has led to increased use of neoadjuvant therapy (NAT) in patients with pancreatic ductal adenocarcinoma (PDAC). A recent North American study demonstrated increased use of NAT and improved operative outcomes in patients with PDAC. The aims of this study were to compare the use of NAT and short-term outcomes in patients with PDAC undergoing pancreatoduodenectomy (PD) among registries from the US and Canada, Germany, the Netherlands, and Sweden. STUDY DESIGN: Databases from 2 multicenter (voluntary) and 2 nationwide (mandatory) registries were queried from 2018 to 2020. Patients undergoing PD for PDAC were compared based on the use of upfront surgery vs NAT. Adoption of NAT was measured in each country over time. Thirty-day outcomes, including the composite measure (ideal outcomes), were compared by multivariable analyses. Sensitivity analyses of patients undergoing vascular resection were performed. RESULTS: Overall, 11,402 patients underwent PD for PDAC with 33.7% of patients receiving NAT. The use of NAT increased steadily from 28.3% in 2018 to 38.5% in 2020 (p < 0.0001). However, use of NAT varied widely by country: the US (46.8%), the Netherlands (44.9%), Sweden (11.0%), and Germany (7.8%). On multivariable analysis, NAT was significantly (p < 0.01) associated with reduced rates of serious morbidity, clinically relevant pancreatic fistulae, reoperations, and increased ideal outcomes. These associations remained on sensitivity analysis of patients undergoing vascular resection. CONCLUSIONS: NAT before PD for pancreatic cancer varied widely among 4 Western audits yet increased by 26% during 3 years. NAT was associated with improved short-term outcomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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".