PC3 - 155 Phase II Study of Dianhydrogalactitol in Patients with MGMT-Unmethylated, Bevacizumab-Naïve Recurrent Glioblastoma
Bibliographic record
Abstract
Glioblastoma (GBM) is the most common brain cancer. Most GBM tumors have unmethylated promoter status for O6-methylguanine-DNA-methyltransferase (MGMT); a validated biomarker for MGMT protein-expression and ensuing temozolomide-resistance. Second-line treatment with bevacizumab has not improved overall survival (OS). Dianhydrogalactitol (VAL-083) is a bi-functional alkylating agent targeting N7-Guanine, thus MGMT-independently inducing interstrand cross-links, DNA double-strand breaks and cell-death in GBM cell-lines and cancer stem cells. VAL-083 is currently in Phase I/II clinical trial for recurrent GBM, post-TMZ and post-bevacizumab. In this Phase II clinical trial, the main goal is to assess the 9-month OS in MGMT-unmethylated, recurrent, bevacizumab-naive GBM. RATIONALE: The vast majority of GBM patients experience recurrent/progressive disease within a year from initial diagnosis and median survival after recurrence is 3-9 months. Chemotherapy regimens for these patients are lacking and there is a significant unmet medical need. Given VAL-083’s novel alkylating mechanism, promising clinical benefit, and favorable safety profile, a trial studying VAL-083 in MGMT-unmethylated recurrent GBM is warranted. METHOD: Randomized, non-comparative biomarker-driven Phase II clinical trial in MGMT-unmethylated GBM patients at first recurrence/progression, prior to bevacizumab. 48 patients will be randomized to receive VAL-083 or “standard-of-care” salvage drug lomustine. 32 patients will receive VAL-083 40mg/m2/day on days 1,2,3 of a 21-day cycle. 16 patients will receive lomustine 90 mg/m2/day on day 1 of a 42-day cycle. Patients will be followed until death or for at least 9 months from enrollment, whichever occurs earlier. Survival will be compared to the BELOB trial for recurrent MGMT-unmethylated GBM patients treated with lomustine.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".