Comparisons of Outcomes of Real-World Patients With Advanced Pancreatic Cancer Treated With FOLFIRINOX Versus Gemcitabine and Nab-Paclitaxel
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to compare the efficacy and safety of FOLFIRINOX (5-FU/leucovorin, irinotecan, and oxaliplatin) and gemcitabine/nab-paclitaxel (GnP) in patients with advanced pancreatic cancer. METHODS: Patients with newly diagnosed advanced pancreatic cancer in Saskatchewan, Canada, from 2011 to 2016, who received FOLFIRINOX or GnP were assessed. A Cox proportional multivariate analysis was performed to evaluate prognostic variables. RESULTS: One hundred nineteen eligible patients with median age of 61 years and male/female ratio of 70:49 were identified. Seventy-seven percent had metastatic disease. Of 119 patients, 86 (72%) received FOLFIRINOX and 33 (28%) were treated with GnP. Median progression-free survival of the FOLFIRINOX group was 6.0 months [95% confidence interval (CI), 4.5-7.5] versus 4.0 months (95% CI, 2.9-5.1) with GnP (P = 0.39). The median overall survival of the FOLFIRINOX group was 9.0 months (95% CI, 7-11) compared with 9.0 months (95% CI, 4.2-13.8) with GnP (P = 0.88). On multivariate analysis, albumin [hazard ratio (HR), 0.63; 95% CI, 0.41-0.97], male sex (HR, 0.65; 95% CI, 0.43-0.97), and second-line therapy (HR, 0.50; 95% CI, 0.28-0.86) were correlated with survival. CONCLUSIONS: Our results showed that real-world patients with advanced pancreatic cancer treated with FOLFIIRNOX or GnP had comparable survival with different safety profile.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".