Impact of first-line fluorouracil, leucovorin, oxaliplatin, and docetaxel (FLOT) for patients with advanced gastroesophageal adenocarcinoma: A retrospective analysis.
Bibliographic record
Abstract
216 Background: Despite a large number of randomized trials, there is no consensus as to the best regimen for advanced gastroesophageal cancer. Combination therapy with docetaxel, cisplatin, and 5-FU has shown increased response rates, progression-free survival (PFS) and overall survival (OS), but at the cost of significant toxicity. Based on a small phase II study, FLOT has been adopted by some groups given its better toxicity profile. We aim at reporting our experience with this regimen Methods: Patients with unresectable advanced gastroesophageal adenocarcinoma who received FLOT (oxaliplatin 85 mg/m2, leucovorin 200 mg/m2, and fluorouracil 2600 mg/m2 as a 24h infusion in combination with docetaxel 50 mg/m2 on day 1 every 2 weeks) as first-line therapy at our institution were retrospectively evaluated. PFS and OS were estimated by the Kaplan-Meier method. Results: A total of 23 patients were reviewed, most of them with metastatic disease (60%). Median age was 56 years (range 26–76) and 74% were male. Median PFS and OS were 5,2 (95% CI 4,0-6,3) and 8,5 months (95% CI 4,4-12,6), respectively. Only 13%of the patients experienced prolonged PFS (>12 months). There were no deaths due to the treatment. Conclusions: Before FLOT could be adopted as a first-line regimen for metastatic gastroesophageal cancer, phase III trials are urgently needed comparing FLOT with more traditional regimens.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".