LGG-49. SAFETY AND EFFICACY OF TRAMETINIB (T) MONOTHERAPY AND DABRAFENIB + TRAMETINIB (D+T) COMBINATION THERAPY IN PEDIATRIC PATIENTS WITH <i>BRAF</i> V600-MUTANT LOW-GRADE GLIOMA (LGG)
Bibliographic record
Abstract
Abstract BACKGROUND Children with BRAF V600-mutant LGG have suboptimal response to standard chemotherapy. Previously, D (BRAF V600 inhibitor) monotherapy has demonstrated clinical benefit in this population. We report interim analysis results of pediatric patients with recurrent/refractory BRAF V600-mutant LGG treated with either T (MEK1/2 inhibitor) monotherapy or D+T combination therapy. METHODS This is a 4-part, open-label, multicenter, phase I/II study (NCT02124772) in pediatric patients (<18 y) with refractory/recurrent tumors. The dose-finding phase, including dose confirmation stratified by age, was followed by disease-specific cohorts at recommended dose levels. Efficacy was determined by both investigator and independent review using RANO criteria. Adverse events (AEs) were assessed per NCI-CTCAE v4.03. RESULTS Of 49 pediatric patients with BRAF V600-mutant LGG (T, n=13; D+T, n=36) enrolled, pooled efficacy data was available for both treatments while safety data was available for 30 patients (T, n=10; D+T, n=20). Most patients (n=8/10) receiving T monotherapy withdrew/discontinued the treatment in contrast to 3/20 in the D+T group. Pyrexia occurred in 50% of patients (n=5/10) in the monotherapy group and was a frequent AE in the combination group (75%; n=15/20). Objective response rate per independent review was 15% (95% CI, 2%–45%) with T monotherapy and 25% (95% CI, 12%–42%) with D+T combination therapy. Seven patients (54%) on monotherapy and 33 patients (92%) on combination therapy had stable disease or better. CONCLUSION In pediatric patients with previously treated BRAF V600-mutant LGG, T monotherapy and D+T combination therapy demonstrated clinical activity, with pyrexia being a common AE.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".