An Evolving Paradigm in Borderline Resectable and Locally Advanced Pancreatic Cancer: Current Strategies and Opportunities for the Future
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDAC), a cancer of the gastrointestinal tract, has been increasing in incidence, with an estimated doubling worldwide over the past two decades. Despite increases in awareness and innovations in genomics and drug discovery, 5-year survival remains low, at only 10%. This is in part owing to the majority of patients being diagnosed at the advanced stage of the disease, in addition to chemotherapy recalcitrant disease. Surgical resection is necessary for a potential cure, however, this is only possible for the 10% of patients who present with resectable disease and potentially for those with borderline resectable disease. Locally advanced pancreatic cancer accounts for approximately 30% of those with PDAC and most of those patients are often precluded from curative intent surgery due to major vascular invasion and local infiltration into peri-pancreatic soft tissue. In cases of locally advanced disease, induction chemotherapy is often used, identifying the subgroup of patients more suited for local treatments and those who may later develop metastases. The treatment regimens used for patients with locally advanced PDAC are often extrapolated from trials involving patients with metastatic disease. In some cases, responses to neoadjuvant therapy have allowed for surgical resection, albeit these aggressive resections were associated with significant morbidity. There is growing interest in identifying the optimal neoadjuvant treatment for patients with borderline resectable pancreatic cancer (BRPC) and locally advanced PDAC (LAPC) in an effort to improve outcomes. Here we review therapeutic strategies for borderline resectable and locally advanced PDAC, with a focus on novel systemic therapy regimens, chemoradiation, and different radiation modalities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".