ACTR-78. TAMIGA: A PHASE II STUDY EVALUATING THE EFFICACY AND SAFETY OF CONTINUOUS BEVACIZUMAB THROUGH MULTIPLE LINES OF TREATMENT FOR GLIOBLASTOMA
Bibliographic record
Abstract
Bevacizumab (anti-vascular endothelial growth factor) prolongs progression-free survival (PFS) in newly diagnosed and recurrent glioblastoma. We hypothesized overall-survival (OS) benefit from continuing bevacizumab (BEV) through multiple lines of treatment (TML). Patients with newly diagnosed glioblastoma were enrolled in a multicenter, double-blind, placebo-controlled, randomized study (TAMIGA/NCT01860638). First-line (1L) treatment was radiotherapy plus temozolomide and BEV with maintenance treatment consisting of temozolomide plus BEV (six cycles) and BEV monotherapy until first disease progression (PD1). After PD1, patients were randomized to receive lomustine (CCNU) plus BEV or CCNU + placebo (P) until PD2. After PD2, patients received BEV plus chemotherapy (investigator choice; CIC) or P+CIC. Primary endpoint: OS. Secondary endpoints: PFS, OS rates, and safety. Overall, 296 patients were enrolled and 123 patients (due to withdrawal) were randomized at PD1 (BEV+CCNU, n=61; P+CCNU, n=62). After PD2, 25 patients in each arm received third-line treatment. Baseline characteristics were generally balanced. At randomization, 32.8% and 30.6% of the patients were receiving corticosteroids for BEV and placebo, respectively. The study terminated prematurely, due to the high withdrawal rate, implying underpowered (i.e. power=60%) inferential testing. For BEV versus placebo, respectively: median OS from randomization was 6.4 vs 5.5 months (HR=1.04, 95% CI 0.69–1.59); 6-month OS rate was 49.2% vs 38.7%; median time to corticosteroid initiation during second-line treatment was 5.8 vs 5.4 months; 86% and 83% had an adverse event (AE); 19% and 15% had ≥1 treatment-related grade ≥3 AEs; 21% and 15% had AEs leading to discontinuation. The study was underpowered for analysis of the primary endpoint. Descriptive analyses suggest neither an improvement nor detriment with the addition of BEV TML, in recurrent glioblastoma. No new safety signals were observed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".