Dose-dependent efficacy of bevacizumab in recurrent glioblastoma
Bibliographic record
Abstract
Abstract Background Bevacizumab (BEV), at a standard dose of 10 mg/kg every 2 weeks is associated with prolonged progression-free survival (PFS) but no improvement in overall survival (OS) in recurrent glioblastoma (rGBM). Few studies have examined the potential dose-dependent efficacy of BEV. In Ontario, reimbursement for the costs of BEV varies, and as a result, our practice began to routinely use lower dose regimens. The main aim of this study was to ensure that there was no harm to patients who received the low dose protocol. Methods A single-center retrospective study of patients given BEV for rGBM between 2015–2020 was performed. Clinical and treatment data including BEV dose regimen (SD [10 mg/kg every 2 weeks] vs LD [5 mg/kg every 2–3 weeks or 10 mg/kg every 3 weeks]) received at the time of rGBM diagnosis were captured. Overall survival (OS) and progression-free survival (PFS) on BEV were compared using the Kaplan-Meier product-limit method. Log-rank test was used to compare potential predictive factors. Cox regression model was performed for multivariable analysis of OS and PFS. Results A total of 96 patients were included with a median follow-up duration of 6.84 months (range 1.12–50.63 months) from the date of the first infusion. The LD group consisted of 55 of the 96 patients. By virtue of funding mechanisms for BEV, the median age in the LD group was significantly higher (62 vs 54 years p = 0.009). There was no difference in MGMT status between the 2 groups (p = 0.60). Eight patients received lomustine with BEV (3 from the SD and 5 from the LD. The LD group had prolonged median PFS (5.89 months versus 3.22 months; p = 0.0112) and OS (10.23 months versus 6.28 months; p = 0.0010). Multivariable analysis including the dose of BEV, the extent of resection, gender, and age revealed that standard dose of BEV, subtotal resection, and female sex were associated with worse overall survival. Nine patients in the SD group vs 18 patients in the LD group reported an adverse event related to BEV. Conclusions For patients with recurrent GBM, we found that a low dose regimen of BEV was associated with prolonged OS and PFS compared to the standard dose regimen. Lower dose schedules may be a better and more cost-effective option for patients with rGBM. Lower costs might provide more equitable access to this very important palliative drug.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".