Phase I and Pharmacokinetic Study of Daily Oral AZD2171, an Inhibitor of Vascular Endothelial Growth Factor Tyrosine Kinases, in Combination With Carboplatin and Paclitaxel in Patients With Advanced Non–Small-Cell Lung Cancer: The National Cancer Institute of Canada Clinical Trials Group
Bibliographic record
Abstract
PURPOSE: AZD2171 is a potent inhibitor of vascular endothelial growth factor receptors that showed broad antitumor activity in preclinical models. Doses of up to 45 mg/d of AZD2171 are tolerable when administered alone. This study evaluated escalating doses of AZD2171 in combination with standard chemotherapy in patients with advanced non-small-cell lung cancer. PATIENTS AND METHODS: Eligible patients received carboplatin targeted to an area under the concentration time curve of 6 mg . min/mL and paclitaxel 200 mg/m(2), both on day 1 of a 3-week cycle; daily oral AZD2171 at either 30 mg or 45 mg commenced day 2 of cycle 1. Pharmacokinetics of all drugs were performed, and tumor response was assessed by Response Evaluation Criteria in Solid Tumors (RECIST). RESULTS: Twenty patients were enrolled. No dose-limiting toxicities were observed during cycle 1 at either dose. Fatigue, diarrhea, anorexia, and granulocytopenia were common; hypertension was manageable with a treatment algorithm designed for this protocol. No clinically significant drug-related bleeding was observed. At 45 mg/d, fatigue and diarrhea were increased, and headache and hoarseness were observed. Paclitaxel clearance decreased during cycle 2, but no other significant pharmacokinetic interactions were observed. After radiology review, confirmed responses were observed in nine patients (response rate, 45%; 95% CI, 23% to 68%); all but one enrolled patient showed evidence of tumor shrinkage, some with cavitation. CONCLUSION: AZD2171 can be combined with standard doses of carboplatin/paclitaxel with encouraging antitumor activity. Toxicity is increased, but predictable and manageable.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".