The role of systemic therapy in borderline resectable and locally advanced pancreatic ductal adenocarcinoma
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDAC) remains a deadly disease, even in patients whose cancer is localized and non-metastatic. Surgical resection provides the only option for cure, but long-term survival rates remain dismal. For patients with borderline resectable (BR) disease who undergo upfront resection, many patients are either too unwell for subsequent adjuvant systemic therapy, develop recurrence soon after, or are found to have unresectable disease intra-operatively. There is increasing evidence for a neoadjuvant approach, using more conventional multi-agent chemotherapy regimens, which have demonstrated higher activity in the metastatic setting compared to single agents. For patients with locally advanced (LA) disease, which is unresectable by current definitions, there is mounting evidence that effective neoadjuvant systemic therapy is able to convert some patients’ disease to a resectable state, offering the potential for long-term survival and cure. Herein we present a review of key trials focusing on prospective, randomized studies to provide high-level evidence supporting a neoadjuvant approach to both BR and LA PDAC. However, many knowledge gaps exist, such as the optimal neoadjuvant multi-agent chemotherapy regimen, the role of radiotherapy, and the safety and efficacy of adding immunotherapy to chemo/radiation therapy. Future challenges in determining the optimal approach to patients with BR or LA PDAC include not only overcoming the inherent difficulties in conducting complex, multidisciplinary, multicentre randomized trials in patients with a high-morbidity and mortality disease, but also trying to standardize disease definitions, treatment regimens, and outcome measures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".