CTNI-39. UPDATE ON GBM AGILE: A GLOBAL, PHASE 2/3 ADAPTIVE PLATFORM TRIAL TO EVALUATE MULTIPLE REGIMENS IN NEWLY DIAGNOSED AND RECURRENT GLIOBLASTOMA
Bibliographic record
Abstract
Abstract BACKGROUND GBM AGILE (Glioblastoma Adaptive, Global, Innovative Learning Environment) is a biomarker based, multi-arm, international, seamless Phase 2/3 platform trial designed to rapidly identify and confirm experimental therapies that improve overall survival for approval along with their associated biomarker signatures. GBM AGILE is a collaboration between academic investigators, patient organizations, and industry to support new drug applications for newly diagnosed (ND) and recurrent glioblastoma. METHODS The primary objective of GBM AGILE is to identify therapies that improve the overall survival in patients with ND or recurrent glioblastoma. Bayesian response adaptive randomization is used within subtypes of the disease to assign participants to investigational arms based on their performance. GBM AGILE operates under a Master Protocol allowing multiple drugs to be evaluated simultaneously and over time against a common control. New experimental therapies are added as information about promising new drugs is identified, while therapies are removed as they complete evaluation. Six investigational arms have been included to date. Along with an adaptive trial design, shared control arm and operational processes, GBM AGILE continues to incorporate new design and operational elements. One recent design element added to the Master Protocol for consideration for future arms is an extended evaluation period, of up to 11 months, for arms that reach maximum sample size in Stage 1 (Stage 1: learn most responsive signature) without having reached a decision for futility or graduation. Allowing data to mature and additional events to accumulate may increase the ability of the trial to detect efficacy, and if appropriate, for an arm to graduate to Stage 2 (Stage 2: confirm activity in graduating signature). Using improved and flexible processes, GBM AGILE continues to serve as a global trial that supports the efficient and rapid incorporation and evaluation of new experimental therapies for patients with glioblastoma. NCT number: NCT03970447.
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 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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".