Survival Benefit of Pembrolizumab for Patients With Pancreatic Adenocarcinoma: A Case Series
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with 5-year survival rate of 10%. Evidence about pembrolizumab usage for PDAC is limited even though it is Food and Drug Administration (FDA)-approved for treatment of advanced pancreatic cancer with deficient mismatch repair expression (dMMR) or high tumor mutational burden (TMB) where as there is limited evidence for programmed death-ligand 1 (PD-L1)-positive PDACs. We present three patients with different stages of advanced PDAC treated with pembrolizumab as single maintenance therapy or combination with other therapy. Case 1 is a patient with borderline resectable PDAC, treated with neoadjuvant chemotherapy and surgical resection, followed with pembrolizumab as maintenance therapy with no progression for 4 years after test showed patient was dMMR positive. Case 2 is a patient who was found to have locally advanced PDAC, treated with neoadjuvant chemotherapy and surgical resection followed by multiple line of treatment with programmed cell death-1 ( PD-1 ) and breast cancer gene 2 ( BRCA2 )-positive status treated with pembrolizumab and olaparib maintenance without any evidence of progression for more than 3 years. Case 3 is a patient with metastatic PDAC with PD-1 and BRCA2 -positive status initially treated with FOLFIRINOX (5-fluorouracil, leucovorin, irinotecan and oxaliplatin) and gemcitabine plus nab-paclitaxel switched to irinotecan liposomal, at the same time was started on maintenance pembrolizumab and olaparib with no progression on computed tomography (CT) surveillance for 8 months. For patient with different stages of PDAC with dMMR mutation or PD-1 expression, pembrolizumab should be explored more as maintenance therapy for patients with surgical operable PDAC to decrease recurrence, or as a combination with targeted therapy or chemotherapy to prolong survival in patients with advanced PDAC. J Med Cases. 2022;13(5):240-243 doi: https://doi.org/10.14740/jmc3918
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".