Phase I/II Trial of Metronomic Chemotherapy With Daily Dalteparin and Cyclophosphamide, Twice-Weekly Methotrexate, and Daily Prednisone As Therapy for Metastatic Breast Cancer Using Vascular Endothelial Growth Factor and Soluble Vascular Endothelial Growth Factor Receptor Levels As Markers of Response
Bibliographic record
Abstract
PURPOSE Preclinical studies indicate that metronomic chemotherapy is antiangiogenic and synergistic with other antiangiogenic agents. We designed a phase I/II study to evaluate the safety and activity of adding dalteparin and prednisone to metronomic cyclophosphamide and methotrexate in women with measurable metastatic breast cancer (MBC). PATIENTS AND METHODS Patients received daily dalteparin and oral cyclophosphamide, twice-weekly methotrexate, and daily prednisone (dalCMP). The primary study end point was clinical benefit rate (CBR), a combination of complete response (CR), partial response (PR), and prolonged stable disease for > or = 24 weeks (pSD). Secondary end points included time to progression (TTP), duration of response, and overall survival (OS). Biomarker response to treatment was assessed by using plasma vascular endothelial growth factor (VEGF) and soluble VEGF receptors (sVEGFRs) -1 and -2. Results Forty-one eligible patients were accrued. Sixteen (39%) had no prior chemotherapy for MBC; 15 (37%) had two or more chemotherapy regimens for MBC. Toxicities were minimal except for transient grade 3 elevation of liver transaminases in 11 patients (27%) and grade 3 vomiting in one patient (2%). One patient (2%) had CR, six (15%) had PR, and three (7%) had pSD, for a CBR of 10 (24%) of 41 patients. Median TTP was 10 weeks (95% CI, 8 to 17 weeks), and median OS was 48 weeks (95% CI, 32 to 79 weeks). VEGF levels decreased but not significantly, whereas sVEGFR-1 and -2 levels increased significantly after 2 weeks of therapy. There was no correlation between response and VEGF, sVEGFR-1, or sVEGFR-2 levels. CONCLUSION Metronomic dalCMP is safe, well tolerated, and clinically active in MBC.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".