Dose-dependent efficacy of bevacizumab in recurrent glioblastoma.
Bibliographic record
Abstract
e14042 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). While there are reports of lower dose regimens of bev being better tolerated and effective in rGBM, this has not been studied in comparison to a standard dose of bev. The main aim of this study is to report on the dose-dependent efficacy of bev by comparing PFS and OS in rGBM patients receiving standard dose (SD) vs lower dose (LD) of bev. Methods: A single-center retrospective study of patients with rGBM started on bev 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 between the two groups 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 date of the first infusion. The LD group consisted of 55/96 patients (57 %) and the age in the LD group was significantly older than the SD group (62 vs 54 years p = 0.009). There was no significant difference in MGMT status between the 2 groups (p = 0.73). Eight patients received lomustine with bev (3 from the standard and 5 from the low dose group). The LD group had prolonged OS (10.23 months versus 6.28 months; p-value = 0.0010) and PFS (5.89 months versus 3.22 months; p-value = 0.0112). Multivariable analysis including dose of bev, extent of resection, gender and age revealed that standard dose of bev, subtotal resection and female sex were associated with worse OS. Eleven patients in the SD group vs 15 patients in the LD group reported an adverse event related to bev. Conclusions: In this study we demonstrate that a reduced dose of bev (5 mg every 2-3 weeks) prolonged both the OS and PFS compared to a standard dose of 10 mg/kg every 2 weeks. This may represent a better and more cost-effective option for patients with rGBM in need of salvage 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".