Phase III Randomized, Placebo-Controlled Study of Cetuximab Plus Brivanib Alaninate Versus Cetuximab Plus Placebo in Patients With Metastatic, Chemotherapy-Refractory, Wild-Type <i>K-RAS</i> Colorectal Carcinoma: The NCIC Clinical Trials Group and AGITG CO.20 Trial
Bibliographic record
Abstract
PURPOSE: The antiepidermal growth factor receptor monoclonal antibody cetuximab has improved survival in patients with metastatic, chemotherapy-refractory, wild-type K-RAS colorectal cancer. The addition of brivanib, a tyrosine kinase inhibitor targeting vascular endothelial growth factor receptor and fibroblast growth factor receptor, to cetuximab has shown encouraging early clinical activity. PATIENTS AND METHODS: Patients with metastatic colorectal cancer previously treated with combination chemotherapy were randomly assigned 1:1 to receive cetuximab 400 mg/m(2) intravenous loading dose followed by weekly maintenance of 250 mg/m(2) plus either brivanib 800 mg orally daily (arm A) or placebo (arm B). The primary end point was overall survival (OS). RESULTS: A total of 750 patients were randomly assigned (376 in arm A and 374 in arm B). Median OS in the intent-to-treat population was 8.8 months in arm A and 8.1 months in arm B (hazard ratio [HR], 0.88; 95% CI, 0.74 to 1.03; P = .12). Median progression-free survival (PFS) was 5.0 months in arm A and 3.4 months in arm B (HR, 0.72; 95% CI, 0.62 to 0.84; P < .001). Partial responses observed (13.6% v 7.2%; P = .004) were higher in arm A. Incidence of any grade ≥ 3 adverse events was 78% in arm A and 53% in arm B. Fewer patients received ≥ 90% dose-intensity of both cetuximab (57% v 83%) and brivanib/placebo (48% v 87%) in arm A versus arm B, respectively. CONCLUSION: Despite positive effects on PFS and objective response, cetuximab plus brivanib increased toxicity and did not significantly improve OS in patients with metastatic, chemotherapy-refractory, wild-type K-RAS colorectal cancer.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".