Multicenter trial of microbubble-enhanced transcranial focused ultrasound (MB-FUS) with monthly adjuvant temozolomide for patients with high-grade gliomas.
Bibliographic record
Abstract
2009 Background: High-grade gliomas (HGGs) have few effective therapies targeting tumor cell recurrence, which remain shielded by blood-brain barrier (BBB). MB-FUS allows for controlled BBB opening (BBBO) enabling localized drug delivery and increased tumor biomarker release into systemic circulation. Methods: MR-guided MB-FUS with real-time feedback was evaluated for HGG patients in multicenter phase 1/2 trial (BT008: NCT03551249, NCT03616860) for adverse events (AEs) and feasibility [primary endpoints], efficacy [secondary endpoint], and plasma cell-free DNA (cfDNA) post-procedure [exploratory]. After resection and 6 weeks of chemoradiation, peri-resectional infiltrative regions were targeted with MB-FUS during monthly adjuvant temozolomide cycles (MB-FUS+TMZ). For efficacy, overall survival (OS) and progression-free survival (PFS) were compared with an external cohort, created using restriction and coarsened exact matching (CEM). Results: Trial cohort had 34 patients enrolled and evaluated from 5 sites in North America. No serious procedure-related AEs were seen, with the most common AEs being mild, self-resolving. BBBO was seen in 100% of treatments, covering 82% targeted volumes with ≤3mm accuracy. Trial cohort had longer mPFS (univariate 13.5 vs. 9.6 months, multivariate HR 0.62, 95%CI: 0.39-0.99, p=0.048) and mOS (36.4 vs. 19.1 months, multivariate HR 0.50, 95%CI: 0.26-0.95, p=0.036), with treatment effect robust in sensitivity analyses. Disease state correlated closely with longitudinal plasma cfDNA changes. Conclusions: MB-FUS+TMZ is a safe and feasible therapeutic approach for HGG, potentially improving survival and enabling longitudinal non-invasive monitoring. Clinical trial information: NCT03551249 , NCT03616860 . Variables Trial cohort Matched Cohort † Patients (N) 34 158 Baseline characteristics used in CEM SMD† Age, years, mean±SD 51.5 ±13.0 51.6 ±13.0 0.0 MGMT, Unmethylated, N (%) 16 (47.1%) 74 (47.1%) 0.0 IDH, Wild type, N (%) 29 (85.3%) 135 (85.3%) 0.0 Characteristics tackled through restriction SMD† Received resection & 6 weeks of chemoradiotherapy 34 (100%) 158 (100%) 0.0 Non-Hispanic, N (%) 34 (100%) 158 (100%) 0.0 Complete resection, N (%) 34 (100%) 158 (100%) 0.0 KPS ≥70 – N (%) 34 (100%) 158 (100%) 0.0 Other characteristics not used in CEM wSMD† Sex, male – N (%) 16 (47.1%) 101 (63.9%) 0.34 Race, White – N (%) 28 (82.4%) 137 (86.7%) 0.13 Preoperative tumor size, median cm 3 (IQR) 19.8 (6.9, 42.9) 47.0 [30.0, 53.0) 0.61 Clinical Outcomes P Unadjusted mOS, months (95%CI) 36.4 (21.1, NR) 19.1 (16.2, 22.8) <0.001 OS HR for treatment adjusted for tumor size, IDH, & M
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".