An Open-Label Phase II Study Evaluating the Safety and Efficacy of Ramucirumab Combined With mFOLFOX-6 as First-Line Therapy for Metastatic Colorectal Cancer
Bibliographic record
Abstract
BACKGROUND: Vascular endothelial growth factor (VEGF) and VEGF receptor 2 (VEGFR-2) are believed to mediate angiogenesis in colorectal cancer (CRC). Ramucirumab (RAM; IMC-1121B) is a human IgG1 monoclonal antibody that inhibits VEGF ligand binding to VEGFR-2, inhibiting VEGFR-2 activation and signaling. METHODS: Patients with metastatic CRC, Eastern Cooperative Oncology Group performance status 0-1, and adequate organ function who had not received chemotherapy for metastatic disease received RAM and the modified FOLFOX-6 regimen every 2 weeks. Endpoints included progression-free survival (PFS), objective response rate, overall survival, and safety. The sample size was based on a potentially improved median PFS from 8 months to 11 months. RESULTS: Forty-eight patients received therapy. Median PFS was 11.5 months (95% confidence interval [CI]: 8.6-13.1 months). The objective response rate was 58.3% (95% CI: 43.21-72.39). The disease control rate (complete or partial response plus stable disease) was 93.8% (95% CI: 82.8-98.7). Median overall survival was 20.4 months (95% CI: 18.5-25.1 months). The most frequent grade 3-4 adverse events included neutropenia (grade 3: 33.3%; grade 4: 8.3%), hypertension (grade 3: 16.7%), and neuropathy (grade 3: 12.5%). Two patients died during the study due to myocardial infarction and cardiopulmonary arrest. CONCLUSION: RAM may enhance the efficacy of modified FOLFOX-6 chemotherapy with an acceptable safety profile in metastatic CRC.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".