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Clinical activity of pan-RAF inhibitor tovorafenib in the registrational pediatric low-grade glioma arm of the phase 2 FIREFLY-1 (PNOC026) study.

2023· article· en· W4379282610 on OpenAlexaff
Lindsay Kilburn, Dong‐Anh Khuong‐Quang, Karsten Nysom, Daniel Landi, David S. Ziegler, Pablo Hernáiz Driever, Sarah Leary, Simon Bailey, Jasper van der Lugt, Sébastien Perreault, Angela J. Waanders, Patricia Baxter, Olaf Witt, Darren Hargrave, Geoffrey McCowage, Xin Zhao, Daniel Da Costa, Michael C. Cox, Peter Manley, Jordan R. Hansford

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineClinical endpointInternal medicineGliomaPhases of clinical researchOncologyAdverse effectClinical trialSurgeryCancer research

Abstract

fetched live from OpenAlex

10004 Background: Pediatric low-grade gliomas (LGGs) are the most common brain tumors of childhood. Genomic alterations of BRAF ( KIAA1549-BRAF fusions, 50–60% and BRAF V600E mutations, 5–15%) are the most frequent oncogenic drivers in pLGGs. Tovorafenib is an investigational, oral, selective, brain-penetrant, small molecule, type II pan-RAF inhibitor. Tovorafenib has demonstrated clinically meaningful responses in 24/35 patients (2 CR, 7 PR and 15 SD) in the pediatric phase 1B PNOC014 (NCT03429803) trial in patients with RAF-altered cancers (Wright, SNO 2022). Methods: FIREFLY-1 (NCT04775485) is a multicenter phase 2 study evaluating the efficacy and safety of tovorafenib monotherapy in patients with BRAF-altered cancers. Registrational arm 1 of FIREFLY-1 includes patients 6 months–25 years of age with recurrent or progressive LGG previously treated with ≥1 prior line of systemic therapy. Tovorafenib 420 mg/m2 (not to exceed 600 mg) is administered weekly, in 28-day cycles, (tablet or liquid suspension formulation) until progression. The primary endpoint of arm 1 is ORR, as defined by Response Assessment in Neuro-Oncology (RANO) criteria and determined by blinded independent review. Results: As of September 28, 2022, arm 1 had enrolled 77 patients and is fully accrued. All patients had ≥6 months of follow-up. Median age at enrollment was 8 years (range 2–21). Patients were pretreated with a median of 3 prior lines of systemic therapy (range: 1–9); 60% had received prior MAPK pathway-targeted agents. The most common tumor site was optic pathway (51%). Sixty-four patients harbored a BRAF fusion/rearrangement (83%) in their tumors, and 13 (17%) had a BRAF V600E mutation. Median duration of tovorafenib treatment is 8.4 months (range 0.7–16.8), with 59 patients (77%) remaining on treatment at the time of data cutoff. Per independent assessment in 69 RANO-evaluable patients, ORR was 64%, [3 CR, 41 PR (10 unconfirmed) and 19 SD] with a clinical benefit rate of 91%. Responses were achieved in tumors with BRAF fusions and V600E mutations, including those previously treated with MAPK inhibitors. The most common treatment-related adverse events (TRAEs) of any grade were hair color changes (75%), increased creatine phosphokinase (64%), anemia (46%), fatigue (42%) and maculopapular rash (42%). Tovorafenib dose modifications occurred in 16 (21%) and discontinuations in 2 (3%) patients due to TRAEs. Updates from a longer follow-up on the 77 patients in arm 1 will be presented at the meeting. Conclusions: Tovorafenib was generally well tolerated and showed encouraging evidence of antitumor activity in children and young adults with recurrent/progressive BRAF-altered pLGG. LOGGIC/FIREFLY-2 (NCT05566795), a global, phase 3 trial is evaluating once-weekly tovorafenib monotherapy in newly-diagnosed patients with pLGG harboring a known activating RAF alteration. Clinical trial information: NCT04775485 .

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.190
GPT teacher head0.518
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2023
Admission routes1
Has abstractyes

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