Inflammatory Breast Cancer as a Model Disease to Study Tumor Angiogenesis: Results of a Phase IB Trial of Combination SU5416 and Doxorubicin
Bibliographic record
Abstract
PURPOSE: We used inflammatory breast cancer (IBC) as a model disease to investigate biological changes associated with an antiangiogenesis agent, SU5416, combined with doxorubicin. EXPERIMENTAL DESIGN: Patients with stage IIIB or IV IBC were treated neoadjuvantly with the combination of SU5416 and doxorubicin for induction therapy. The dose of SU5416 (administered on days 1 and 4, every 3 weeks) and doxorubicin (administered on day 1 every 3 weeks) were escalated in cohorts of three patients starting at 110 and 60 mg/m2, respectively, for a total of five cycles leading up to mastectomy. Patients underwent serial assessment (pharmacokinetic sampling, biopsy of breast, tumor blood flow dynamic contrast-enhanced magnetic resonance imaging, plasma angiogenesis, and endothelial cell damage markers) prior to treatment, at the end of cycles no. 2 and no. 5, and after mastectomy. RESULTS: Eighteen patients were enrolled; neutropenia was dose-limiting, and overall median survival was not reached (50 months of study follow-up). Four patients (22%) experienced congestive heart failure, which resolved and were likely attributable to a smaller volume of distribution and higher Cmax of doxorubicin in combination with SU5416. We did observe a significant decline in tumor blood flow using Kep calculated by Brix (pretreatment versus post-cycle no. 5; P = 0.033), trend for a decline in tumor microvessel density after treatment, and low baseline levels of soluble intracellular adhesion molecule were associated with improved event-free survival. CONCLUSIONS: This study showed evidence of an unfavorable cardiac interaction between SU5416 and doxorubicin, which prohibits further investigation of this combination. However, this study supports the importance of using IBC as a model for investigating angiogenesis inhibitors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".