LGG-46. TRAMETINIB THERAPY IN PEDIATRIC PATIENTS WITH LOW-GRADE GLIOMAS (LGG) WITH BRAF GENE FUSION; A DISEASE-SPECIFIC COHORT IN THE FIRST PEDIATRIC TESTING OF TRAMETINIB
Bibliographic record
Abstract
LGG is the most prevalent childhood brain tumor. BRAF fusions drive constitutive activation of BRAF and tumorigenesis. We report results of trametinib, a MEK1/2 inhibitor, in pediatric patients with LGG with BRAF fusion. This phase 1/2 trial (NCT02124772) enrolled pediatric patients (≤18 y) with refractory/recurrent tumors. We report results from interim analysis of pediatric patients with LGG harboring BRAF fusion. Trametinib was dosed at 4 dose levels in part A (0.0125, 0.025, 0.04, and 0.032 mg/kg/d) and at 0.025 mg/kg/day in the expansion cohort. Tumor assessments were performed every 8 weeks by MRI, including T2-FLAIR sequences, using RANO criteria. Twenty-three patients were enrolled across cohorts. Median age of patients was 8 y (range, 2-18) and 13 of 23 were male. At data cutoff, 15 patients were ongoing. One patient discontinued with progressive disease (PD) at 35 weeks, 4 due to adverse events (AEs), 2 per investigator discretion, and 1 per consent withdrawal. The most common treatment-related AEs were diarrhea (14), rash (13), paronychia (9), and maculopapular rash (8). There were no deaths on study. Confirmed partial responses were observed in 3 patients by investigator and 1 patient by independent review. No patients had best response of PD. All responses were ongoing at the data cutoff (all >1 y), and 12 patients had ongoing stable disease (49-121 weeks). In pediatric patients with pretreated LGG and BRAF fusion, trametinib was well tolerated, with 1 independently confirmed RANO response, and most patients were without PD >1 y.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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".