Final analysis of the phase III randomized trial of cetuximab (CET) plus either brivanib alaninate (BRIV) or placebo in patients (pts) with chemotherapy refractory, <i>K-RAS </i>wild-type (WT), metastatic colorectal carcinoma (mCRC): The NCIC Clinical Trials Group and AGITG CO.20 trial.
Bibliographic record
Abstract
3504 Background: The anti-EGFR monoclonal antibody CET has improved survival in pts with chemotherapy refractory, K-RAS WT mCRC. BRIV is a potent inhibitor of multiple receptor tyrosine kinases including both VEGFR and FGFR. The combination of CET and BRIV targets tumor growth and angiogenesis and demonstrated encouraging activity in an early phase clinical trial. Methods: Pts with mCRC previously treated with combination chemotherapy were randomized 1:1 to receive CET 400 mg/m2 IV loading dose followed by weekly maintenance of 250 mg/m2 plus either BRIV 800 mg PO daily (Arm A) or placebo (Arm B). Pts may have had 1 prior anti-VEGF, but no prior anti-EGFR therapy. Primary endpoint was overall survival (OS). Results: From 02/2008 to 02/2011, 750 pts were randomized (376 in Arm A and 374 in Arm B). Demographics: median age=64 (range 27-88); male=64%; ECOG 0:1:2 (%)=32:58:10; >3 prior chemotherapy regimens=92%; prior anti-VEGF therapy=41%; K-RAS WT=97%. Primary analysis was conducted per protocol after 536 deaths were observed, with median OS of 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=0.12. 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<0.0001. Incidence of any ≥grade 3 adverse event (AE) was 78% in Arm A and 53% in Arm B. Time to deterioration of physical function was shorter and global quality of life scores were lower in Arm A vs Arm B. Planned subgroup analyses revealed no statistically difference in treatment effects on OS based on pre-specified factors of age, gender, ECOG and race. Likewise, no difference was detected based on exploratory subgroup analyses of LDH and prior anti-VEGF therapy. Conclusions: Despite positive effects on PFS, the combination of CET+BRIV did not significantly improve OS in pts with chemotherapy refractory, K-RAS WT mCRC. Final updated results based on 20-25% additional events for a total of nearly 700 deaths, as well as further exploratory subgroup analyses, will be presented.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".