Phase IV Study of Bevacizumab in Combination with Infusional Fluorouracil, Leucovorin and Irinotecan (FOLFIRI) in First-Line Metastatic Colorectal Cancer
Bibliographic record
Abstract
BACKGROUND: Bevacizumab (Avastin) significantly improves overall survival (OS) and progression-free survival (PFS) when combined with first-line irinotecan (IFL) plus bolus 5-fluorouracil (5-FU) and leucovorin (LV) in patients with metastatic colorectal cancer (CRC). This open-label, phase IV trial evaluated the efficacy and safety of first-line bevacizumab in combination with IFL and infusional 5-FU/LV (FOLFIRI). METHODS: Two-hundred and nine treatment-naïve metastatic CRC patients were enrolled and received bevacizumab and FOLFIRI every 2 weeks. Treatment was continued until disease progression. The primary objective was PFS, with additional determinations of OS, response and toxicity. RESULTS: Median PFS was 11.1 months and is comparable to that observed in published phase III and community-based trials using first-line bevacizumab plus FOLFIRI, and to phase III trials using bevacizumab in combination with bolus 5-FU/LV plus IFL. Median OS was 22.2 months. Overall response rate was 53.1% and the disease control rate 85.6%. Most adverse events were grade 1/2 and were manageable. The most common grade 3/4 adverse events (> or =10%) were neutropenia, venous thromboembolic events, diarrhea, and fatigue. CONCLUSION: Bevacizumab combined with first-line FOLFIRI is an effective and well-tolerated therapy option for patients with metastatic CRC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".