CTP-17. Clinical stability following tovorafenib treatment in relapsed/refractory pediatric low-grade glioma: updated results from the phase 2 FIREFLY-1 trial
Bibliographic record
Abstract
Abstract BACKGROUND Tovorafenib is a selective, CNS-penetrant, type II RAF inhibitor that is FDA approved for recurrent BRAF-altered pLGG based on results of the ongoing FIREFLY-1 (NCT04775485) phase 2 study. METHODS 77 patients enrolled in the registrational arm (Arm 1) of FIREFLY-1. After 26 or more cycles (28 days each), patients could stop tovorafenib (drug holiday) and reinitiate upon radiographic or clinical evidence of progressive disease (PD). RESULTS As of May 10, 2024 data cutoff, objective response rate (ORR; RAPNO) for arm 1 (n=77) was 53%; median duration of response (DOR) was 18 months (range 12.0-22.8). 44 patients completed a 26-cycle course; 33/44 (75%) patients opted to enter drug holiday per protocol, with median follow-up since last dose of 4.4 months (range 0.2-11.6). 15/33 (45%) did not have radiographic PD prior to treatment cessation; PD events occurred in 5/15 patients by 6 months post treatment cessation. A more recent data extract (May 21, 2025) showed 5 additional patients entered drug holiday (n=38); median follow-up since last dose was 15.6 months (range 1.4-24.0). 30/38 (79%) remained clinically stable irrespective of radiographic response, with 28 (74%) remaining without retreatment ≥12 months from last dose. 2 patients exited study early, 7.7 months and 3 months from last dose. 8/38 (21%) were retreated with tovorafenib and remained on retreatment at time of extract. No new toxicities were reported with retreatment. Updated data from a prespecified data cut with approximately 36-month follow-up will be presented, including DOR, time to next treatment with ≥12 months off tovorafenib, and activity of tovorafenib at retreatment. CONCLUSIONS Tovorafenib induces durable responses with evidence of clinical stability off treatment in patients with recurrent BRAF-altered pLGG. Progression can occur after cessation, but retreatment is feasible.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".