Review of Current Systemic Therapy and Novel Systemic Therapy for Pancreatic Ductal Adenocarcinoma
Bibliographic record
Abstract
BACKGROUND: This review aims to describe the systemic treatment options for pancreatic ductal adenocarcinoma and includes a summary of the current treatments as well as the ongoing clinical trials which may be efficacious in the treatment of this aggressive malignancy. METHODS: A literature review was performed using MEDLINE/PubMed between August 1996 and February 2023. The reviewed studies are categorized into these categories: current standard of care treatments, targeted therapies, immunotherapy and clinical trials. The current treatment modality for the treatment of advanced pancreatic cancer is mainly systemic chemotherapy. RESULTS: The introduction of polychemotherapy regimens including gemcitabine/nab-paclitaxel and FOLFIRINOX (oxaliplatin, irinotecan, folinic acid and fluorouracil) has improved the clinical outcome of advanced pancreatic cancer. For further improvement in clinical outcomes, several novel approaches have been extensively studied in pancreatic cancer. The review discusses the current standard chemotherapy regimen and the novel treatment options in the field. CONCLUSIONS: While there are novel treatments being explored for metastatic pancreatic, it remains a debilitating and aggressive disease with high mortality that warrants continued efforts to advance therapeutic options.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| 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) | 0.004 | 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".