Real World First-Line Treatments and Outcomes of Nab-Paclitaxel Plus Gemcitabine, mFOLFIRINOX and GEMOX in Unresectable Pancreatic Cancer from a Chinese Single Institution
Bibliographic record
Abstract
Background: There have not been any head-to-head prospective studies to compare the effects of different chemotherapy regimens as first-line treatments for unresectable pancreatic cancer (UPC). We aimed to compare the effectiveness of nab-paclitaxel plus gemcitabine, mFOLFIRINOX and gemcitabine plus oxaliplatin (GEMOX) as first-line treatments by using real-world data from Chinese patients. Methods: We retrospectively included patients with UPC treated with nab-paclitaxel plus gemcitabine, mFOLFIRINOX or GEMOX as a first-line treatment at Sun Yat-sen University Cancer Center. Overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and disease control rate (DCR) were assessed. Results: A total of 117 patients were administered nab-paclitaxel plus gemcitabine (n = 62), mFOLFIRINOX (n = 30) or GEMOX (n = 25) as first-line chemotherapy. The median OS was 11.1, 10.1 and 10.2 months (p = 0.75) in the nab-paclitaxel plus gemcitabine, mFOLFIRINOX and GEMOX, respectively. The ORR was similar among the three groups (24%, 23% and 32%, p = 0.76) and the DCR was higher in the nab-paclitaxel-gemcitabine group (82%) than the other two groups (60% and 64%, p = 0.04). The most common adverse events of grade 3 or 4 were neutropenia (32%, 28% and 5%), peripheral neuropathy (13%, 16% and 0) and fatigue (9%, 16% and 5%). Febrile neutropenia occurred in 2%, 4% and 5% of the patients in the three groups. Conclusion: In the first line treatment of UPC, our results suggest that nab-paclitaxel plus gemcitabine was associated with a higher DCR than mFOLFIRINOX or GEMOX, while all groups demonstrated similar OS, PFS and ORR.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".