Abstract P6-12-01: A Meta Analysis of Risk of Cardiovascular Events in Patients with Metastatic Breast Cancer (MBC) Treated with Anti Vascular Endothelial Growth Factor (VEGF) Therapy — Bevacizumab
Bibliographic record
Abstract
Abstract Background and objectives: Bevacizumab, used in combination with chemotherapy has demonstrated efficacy in randomized trials in MBC. Hypertension, congestive heart failure and cardiomyopathy have been reported in trials of bevacizumab in breast cancer. The aim of this systematic review and meta analysis is to determine the overall risk of grade 3-4 hypertension (HTN), left ventricular dysfunction (LVD) and venous (VT) and arterial thromboembolic events (ATE) related to Bevacizumab in patients with MBC. Methods: We selected randomized phase III trials which compared chemotherapy with or without bevacizumab in MBC as first or second line therapy. Data extraction was carried out from results published in the literature or from conference proceedings of the selected studies. For the analysis, we used a fixed-effects and random effects models to calculate the pooled event-based relative risk ratios (RR) with 95% confidence interval (CI). The Cochran's Q statistic and I2 statistics were first calculated to assess the heterogeneity among the proportions of the included trials. We collected all grade 3-4 events reported in these trials in relation to cardiovascular events: HTN, LVD, congestive heart failure, cardiomyopathy, VT and ATE. Results: Five trials were included in the meta-analysis: E2100, AVADO, RIBBON-1, RIBBON-2 and Miller et al study (capecitabine alone or plus bevacizumab in previously treated MBC). In total 2126 patients received chemotherapy in combination with bevacizumab and 1444 chemotherapy alone. When there was tendency for heterogeneity, random-effects models were used. Thromboembolic events were pooled together as VT and ATE as information was not clear in some of the reported studies. CHF and cardiomyopathy were considered for LVD events in the Miller study as LVD was not reported. Patients treated with bevacizumab-containing regimens had a RR for HTN of 10.32 (95% CI, 4.23- 24.79; p<.0001), RR for LVD 2.58 (95% CI, 1.06 - 6.32; p=0.04) and RR for VT and ATE of 1.71 (95% CI, 0.81- 3.60; p=0.16) as shown in figure 1. Conclusion: HTN is a recognized side effect of bevacizumab therapy. The risk of LVD is also significantly higher with bevacizumab therapy (RR 2.58) as shown in this pooled analysis, but the risk of thrombotic events is not increased. Figure available in online version. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P6-12-01.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.055 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".