Breaking down the evidence for bevacizumab in advanced cervical cancer: past, present and future
Bibliographic record
Abstract
Despite the introduction of screening and, latterly, vaccination programs in the developed world, globally cervical cancer remains a significant health problem. For those diagnosed with advanced or recurrent disease even within resource rich communities, prognosis remains poor with an overall survival (OS) of just over 12 months. New therapeutic interventions are urgently required. Advances in our understanding of the mechanisms underlying tumor growth and the downstream effects of human papilloma virus (HPV) infection identified angiogenesis as a rational target for therapeutic intervention in cervical cancer. Anti-angiogenic agents showed promising activity in early phase clinical trials culminating in a randomized phase III study of the humanized monoclonal antibody to vascular endothelial growth factor (VEGF), bevacizumab, in combination with chemotherapy. This pivotal study, the Gynecologic Oncology Group protocol 240, met its primary endpoint demonstrating a significant improvement in OS. Bevacizumab became the first targeted agent to be granted regulatory approval by the United States Food and Drug Administration for use alongside chemotherapy in adults with persistent, recurrent or metastatic carcinoma of the cervix. This review outlines the rationale for targeting angiogenesis in cervical cancer focusing on the current indications for the use of bevacizumab in this disease and future directions.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".