Cardiovascular Toxicity of Bevacizumab in Long-term Survival of Recurrent Ovarian Cancer: A Case Report
Bibliographic record
Abstract
Introduction: Bevacizumab has been shown to improve progression-free survival in women with ovarian cancer in multiple clinical trials. Cardiovascular toxicity is reported in the case of a long term survivor of recurrent ovarian cancer. Case Report: A 47-year-old woman was diagnosed as stage IIIC, Grade 3 endomitriod adenocarcinoma of the ovary. She had been treated with 4 debulking surgeries and 6 different chemotherapy regimens for 9 years. However, remission diminished over this time period to only one month. Bevacizumab was administrated with additional chemotherapies, and prolonged survival was demonstrated over the next 5 years, including ongoing remission of 18 months to date. New onset hypertension was developed at the 10th month of bevacizumab treatment, and proteinuria was found at the 12th month. Patient presented symptoms of coronary artery disease during the 31th month of bevacizumab treatment, and was soon treated with 4 stents, whereby symptoms resolved. After the 36th month of bevacizumab, the patient had non ST elevated myocardial infarction and peripheral vascular disease. Bevacizumab was terminated thereafter. In the following 18 months, the patient was treated with angioplasty 2 times for coronary artery occlusion, and with an additional stent. This was followed with coronary artery bypass graft. She also had an angioplasty for right femoral artery stenosis. Throughout most of the 14 year disease course, the patient maintained a good quality of life. As patients achieve long term survival from bevacizumab treatment, cardiovascular complications should be recognized and treated aggressively to minimize the adverse effects of cancer therapy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 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".