Clinical outcomes of patients with gliomas treated with bevacizumab in British Columbia (BC).
Bibliographic record
Abstract
e13021 Background: Health Canada approved the use of Bevacizumab (Bev) in recurrent gliomas in Mar 2010. However, there is limited evidence for its use for this indication. In Canada, several provincial health jurisdictions do not fund this drug in this setting. BC Cancer Agency started covering Bev for recurrent brain tumors in Apr 2011 and this study was conducted to assess the clinical outcomes of patients (pts) outside clinical trials to help support the continuing funding of this therapy. Methods: This was a retrospective, multi-centre, review conducted at the BC Cancer Agency, a government funded, integrated care organization which delivers cancer care to the residents of BC, Canada. Cases were identified from the agency’s provincial registry and systemic therapy drug database. Pts were eligible if they were treated with one dose of Bev min with or without lomustine or etoposide for recurrent brain tumor between Apr 2011 and Mar 2014. Response was assessed using the Neuro-Oncology Working Group Response Assessment for High-Grade Gliomas. The primary end points were progression free survival (PFS). Secondary endpoints were overall survival (OS) and objective response rate (ORR). Results: A total of 160 pts were included: median age was 55 (range 26-84) and majority was males (64.4%). Most common diagnoses were glioblastoma multiforme (70.6%) and oligodendroglioma (10.6%). Half of pts had received prior metronomic temozolomide. Median therapy duration was 3 months (mo) (0.5-31 mo). Median PFS was 5 mo and 6-mo PFS was 37.2%. Median OS was 7 mo and 9-mo OS was 27.7%. ORR was 20%. Most common reasons for Bev discontinuation were disease progression (57.5%), death (13.8%) and toxicity (5%). Conclusions: Our data suggest Bev induced clinical responses in pts with recurrent brain tumors with similar PFS compared to clinical trials (median 4-4.2 mo, 6-mo 41-42.6%). However, our data showed a lower ORR and less survival benefits than on clinical trials (ORR 28-38%, median OS 9-11 mo, 9-mo OS 38-59%). Bev remains an appropriate therapy option for pts with advanced brain tumors who have failed or cannot tolerate metronomic dose temozolomide or experience symptoms associated with cerebral edema requiring high doses of corticosteroids.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".