Comparison of Gemcitabine Versus the Matrix Metalloproteinase Inhibitor BAY 12-9566 in Patients With Advanced or Metastatic Adenocarcinoma of the Pancreas: A Phase III Trial of the National Cancer Institute of Canada Clinical Trials Group
Bibliographic record
Abstract
PURPOSE: To compare the selective matrix metalloproteinase inhibitor BAY 12-9566 with the nucleoside analog gemcitabine in the treatment of advanced pancreatic cancer. METHODS: Patients with advanced pancreatic adenocarcinoma who had not previously received chemotherapy were randomly assigned to receive BAY 12-9566 800 mg orally bid continuously or gemcitabine 1,000 mg/m2 administered intravenously on days 1, 8, 15, 22, 29, 36, and 43 for the first 8 weeks, and then days 1, 8, and 15 of each subsequent 28-day cycle. The primary end point was overall survival; secondary end points were progression-free survival, tumor response, quality of life, and clinical benefit. The planned sample size of the study was 350 patients. Two formal interim analyses were planned. RESULTS: The study was closed to accrual after the second interim analysis on the basis of the recommendation of the National Cancer Institute of Canada Clinical Trials Group Data Safety Monitoring Committee. There were 277 patients enrolled onto the study, 138 in the BAY 12-9566 arm and 139 in the gemcitabine arm. The rates of serious toxicity were low in both arms. The median survival for the BAY 12-9566 arm and the gemcitabine arm was 3.74 months and 6.59 months, respectively (P <.001; stratified log-rank test). The median progression-free survival for the BAY 12-9566 and gemcitabine arms was 1.68 and 3.5 months, respectively (P <.001). Quality-of-life analysis also favored gemcitabine. CONCLUSION: Gemcitabine is significantly superior to BAY 12-9566 in advanced pancreatic 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".