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Record W2987946496 · doi:10.1093/neuonc/noz175.073

ACTR-30. UPDATED EFFICACY AND SAFETY OF DABRAFENIB PLUS TRAMETINIB IN PATIENTS WITH RECURRENT/REFRACTORY BRAF V600E–MUTATED HIGH-GRADE GLIOMA (HGG) AND LOW-GRADE GLIOMA (LGG)

2019· article· en· W2987946496 on OpenAlexaff
Patrick Y. Wen, Alexander Stein, Martin J. van den Bent, Jacques De Grève, Sascha Dietrich, Filip De Vos, Nikolas von Bubnoff, Myra van Linde, Albert Lai, Gerald W. Prager, Mario Campone, Angelica Fasolo, José A. López-Martín, Tae Min Kim, Warren Mason, Ralf‐Dieter Hofheinz, Jean‐Yves Blay, Daniel Cho, Anas Gazzah, Carlos Gomez‐Roca, Jeffrey Yachnin, Aislyn Boran, Paul Burgess, Ilan Palanichamy, Eduard Gasal, Vivek Subbiah

Bibliographic record

VenueNeuro-Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsTrametinibMedicineDabrafenibInternal medicineOncologyGliomaProgression-free survivalDiscontinuationInterim analysisClinical endpointMEK inhibitorClinical trialChemotherapyCancerCancer researchMAPK/ERK pathwayVemurafenibMetastatic melanoma

Abstract

fetched live from OpenAlex

Abstract BACKGROUND There is a lack of treatment options for HGG and LGG patients. BRAFV600E mutations are uncommon in glioma, with a poor long-term prognosis. Combined BRAF/MEK inhibition extends progression-free survival (PFS) and overall survival (OS) in BRAF V600E–mutated melanoma, non small-cell lung cancer, and anaplastic thyroid cancer. METHODS This phase 2, open-label trial (NCT02034110) evaluated dabrafenib (BRAF inhibitor, 150mg BID) plus trametinib (MEK inhibitor, 2mg QD) in patients with BRAF V600E mutations in 9 rare tumor types, including HGG and LGG. Eligible patients had histologically-confirmed recurrent or progressive glioma (LGG:WHO grade 1 or 2; HGG:WHO grade 3 or 4), with HGG patients required to have received radiotherapy and first-line chemotherapy, or concurrent chemoradiation. Treatment continued until unacceptable toxicity, disease progression, or death. Primary endpoint was investigator-assessed objective response rate (ORR) using RANO criteria. Secondary endpoints included duration of response (DOR), PFS, OS, and safety. RESULTS Interim analysis (IA) #14 (data cutoff: April 2, 2018) reported additional 3 months follow-up, with 49 patients enrolled (HGG, n=39; LGG, n=10) and 3 patients not evaluable for response. In HGG patients, ORR was 27% (10/37; 95%CI: 13.8%-44.1%), including CR (n=1), PR (n=9), and SD (n=11), with 16 patients currently ongoing treatment. In LGG patients, ORR was 56% (5/9; 95%CI: 26.8%-79.3%), including PR (n=5) and SD (n=4), with 6 patients currently ongoing treatment. OS, PFS, and DOR will be presented (IA#15). In HGG patients, adverse events (AEs) included fatigue (33%), headache (31%), rash (28%), and pyrexia (23%); grade 3/4 AEs included neutropenia (8%) and fatigue (5%). In LGG patients, AEs included headache (70%), fatigue, pyrexia (60% each), nausea, and arthralgia (50% each); grade 3/4 AEs included fatigue (20%). CONCLUSIONS Dabrafenib plus trametinib demonstrated promising efficacy in patients with recurrent or refractory BRAF V600E‒mutated HGG or LGG, with manageable AEs and no new safety signals.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.269
Teacher spread0.258 · 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 teacher head, not a consensus.

Study designObservational
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

Citations22
Published2019
Admission routes1
Has abstractyes

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