Administration of FOLFIRINOX for Advanced Pancreatic Cancer: Physician Practice Patterns During Early Use
Bibliographic record
Abstract
Advanced pancreatic cancer results in high morbidity and mortality. The standard of care treatment in the advanced setting changed in 2011 with the introduction of FOLFIRINOX (FFX) chemotherapy. However, it was highly toxic with significant risk of complications. We assessed the practice patterns of medical oncologists across Canada. METHODS: We performed a retrospective study of consecutive patients with advanced pancreatic cancer treated with FFX at eight Canadian cancer centers. Demographic, treatment, and outcome data were collected and analyzed. RESULTS: The median age of the patients was 61 (range 24-80), 43% were female, 96% had an ECOG PS of 0 or 1, and 50% had three or more metastatic sites. The median follow-up time was 20.8 months (95%CI 18.6-24.9). Physicians started FFX at the standard dose 31% of the time. Physicians prescribed GCSF for primary prophylaxis most when giving standard-dose FFX (30% of the time) in comparison to reduced dose with or without the 5-FU bolus. Dose reductions occurred in 78.1% of patients, while dose delay occurred in 65.2% of patients. CONCLUSIONS: Medical oncologists in Canada historically prescribed FFX to patients with advanced pancreatic cancer in a fashion that was not uniform, prior to the emergence of evidence for upfront dose reductions.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".