First-line Systemic Therapy with Bevacizumab in Advanced Epithelial Ovarian Cancer
Bibliographic record
Abstract
First-line treatment of advanced epithelial ovarian cancer (EOC) involves a combination of cytoreductive surgery, chemotherapy, and targeted therapy. Bevacizumab is a monoclonal antibody targeting the angiogenesis pathway and has become a standard treatment option in EOC. The first part of this thesis synthesizes the current literature on first line systemic treatment in EOC, focusing on clinical trials involving bevacizumab. This includes an in-depth systematic review and meta-analysis of bevacizumab in the first-line treatment of advanced EOC in modern oncology, and a critical analysis of the current economic considerations of bevacizumab in this setting. The latter part of this thesis reflects real-world evidence on patterns of first-line systemic therapy delivery and adoption of bevacizumab for advanced EOC in Ontario using province-wide administrative data. We found overall low uptake of bevacizumab which may be influenced by provider specialty. Further studies are required to explore in more depth factors associated with these findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".