5-Fluorouracil/L-Leucovorin Plus Oxaliplatin (FOLFOX) Regimen as Salvage Chemotherapy for Patients with Unresectable Pancreatic Cancer Receiving Gemcitabine and Nab-Paclitaxel and 5-Fluorouracil/L-Leucovorin Plus Nanoliposomal Irinotecan: Preliminary Results from Clinical Practice
Bibliographic record
Abstract
Salvage chemotherapy for patients with unresectable pancreatic cancer (UR-PC) who have been treated with gemcitabine and nab-paclitaxel (GnP), and 5-fluorouracil (5-FU)/l-leucovorin (LV) plus nanoliposomal irinotecan (nal-IRI), has not been fully established. We retrospectively reviewed data from 17 patients with UR-PC who initiated 5-FU/l-LV plus oxaliplatin (FOLFOX) as salvage chemotherapy at our hospital between June 2020 and August 2021, after treatment with GnP and 5-FU/LV plus nal-IRI. The primary endpoint was tumor response. The secondary endpoints were progression-free survival (PFS) and adverse events (AEs). The response and disease control rates were 5.9% (1/17) and 17.6% (3/17), respectively. The median PFS was 1.8 months (range: 0.4-5.2 months). Eight patients (47.1%) experienced grade 3 nonhematologic AEs, while none experienced grade 3 hematologic AEs. Two patients with controlled disease had homologous recombination deficiency (HRD)-associated gene mutations in cancer panel testing. The FOLFOX regimen benefit for UR-PC patients treated with GnP and 5-FU/LV plus nal-IRI may be limited to patients with HRD-associated gene mutations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".