ACTR-19. BASELINE PLASMA MATRIX METALLOPROTEINASE 9 (MMP9) PREDICTS OVERALL SURVIVAL (OS) BENEFIT FROM BEVACIZUMAB INDEPENDENTLY OF MOLECULAR SUBTYPES IN NEWLY DIAGNOSED GLIOBLASTOMA: RETROSPECTIVE ANALYSIS OF AVAglio
Bibliographic record
Abstract
Addition of bevacizumab to radiotherapy/temozolomide (RT/TMZ) improved progression-free survival (PFS) (vs placebo+RT/TMZ) but not OS in newly diagnosed glioblastoma (AVAglio/NCT00943826). However, a retrospective analysis of AVAglio suggested that patients with proneural glioblastoma derived an OS benefit from first-line bevacizumab. In recurrent glioblastoma, MMP9 and MMP2 plasma levels may predict bevacizumab activity. We retrospectively analyzed AVAglio data to examine whether MMP9/MMP2 baseline plasma levels predicted OS benefit from bevacizumab in newly diagnosed glioblastoma and potential relationships between MMP and glioblastoma molecular subtypes. MMP9 and MMP2 levels were assessed (ELISA; R&D Systems) in baseline plasma samples from 577/921 patients (AVAglio: placebo n=294/bevacizumab n=283). Molecular subtypes were analyzed by gene expression profiling (placebo n=167/bevacizumab n=164). Post-hoc analysis and PFS/OS multivariate models, including MMP9/2-treatment interactions, were performed. MMP9 distribution at baseline was comparable between arms (median: placebo 82.4ng/mL [range 5–3454]; bevacizumab 83.6ng/mL [range 10–3070]). Patient characteristics were generally balanced between subgroups (per quartile [Q]), including for known prognostic factors. Patients with low MMP9 (<Q1) derived a significant 5.2-month OS benefit with bevacizumab (HR 0.51, 95% CI 0.34−0.76, p=0.0009; median 13.6 [placebo] vs 18.8 [bevacizumab] months). A consistent 5.8-month PFS benefit was seen (HR 0.36, 95% CI 0.24−0.54, pQ3), OS favored the placebo arm (HR 1.21, 95% CI 0.80−1.81) although no statistically significant difference could be shown. Molecular subtype distribution (proneural/mesenchymal/proliferative) was similar in low (Q3) MMP9 subgroups (both arms). In the multivariate analysis, an interaction was seen between treatment and MMP9 (p=0.03) for OS. Predictive value of MMP2 levels could not be shown in this study. This post-hoc analysis suggests that baseline MMP9 levels were predictive of OS benefit from bevacizumab in newly diagnosed glioblastoma; no relationship between this predictive value and molecular subtype could be shown.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 teacher head, 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".