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Record W4388794664 · doi:10.1093/neuonc/noad179.1202

LTBK-06. IMPACT OF VORASIDENIB TREATMENT ON MUTANT <i>IDH1</i> OR <i>IDH2</i> DIFFUSE GLIOMA TUMOR GROWTH RATE: RESULTS FROM THE RANDOMIZED, DOUBLE-BLIND, PHASE 3 INDIGO STUDY

2023· article· en· W4388794664 on OpenAlexaff
Patrick Y. Wen, Ingo K. Mellinghoff, Martin J. van den Bent, Deborah T. Blumenthal, Mehdi Touat, Katherine B. Peters, Jennifer Clarke, Joe Mendez, Shlomit Yust‐Katz, Warren Mason, François Ducray, Yoshie Umemura, Burt Nabors, Matthias Holdhoff, Andreas F. Hottinger, Yoshiki Arakawa, Juan Manuel Sepúlveda-Sánchez, Wolfgang Wick, Riccardo Soffietti, James Perry, Pierre Giglio, Macarena de la Fuente, Elizabeth A. Maher, Dan Zhao, Shuchi S. Pandya, Lori Steelman, Islam Hassan, Timothy F. Cloughesy, Benjamin M. Ellingson

Bibliographic record

VenueNeuro-Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science CentreToronto General Hospital
Fundersnot available
KeywordsPlaceboMedicineMagnetic resonance imagingGliomaIsocitrate dehydrogenaseNuclear medicineIDH1IDH2Randomized controlled trialInternal medicineUrologyRadiologyPathologyNuclear magnetic resonanceMutant

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION The INDIGO study (NCT04164901) showed that vorasidenib, an oral, brain-penetrant, dual inhibitor of mutant isocitrate dehydrogenase (mIDH) 1/2, significantly improved imaging-based progression-free survival and time-to-next-intervention compared with placebo in patients with grade 2 mIDH1/2 glioma previously treated with surgery only. Given the limitations of traditional bi-dimensional measurements, evaluating volumetry and tumor growth rate (TGR) is an additional method of measuring treatment effect in these diffuse growing tumors. METHODS Magnetic resonance imaging (MRI) scans were performed at baseline and every 12 weeks on-treatment; up to three pre-treatment MRI scans were requested when available. Tumor volumes were derived per blinded independent review committee using a semi-automated approach. TGR was defined as percentage change in tumor volume every 6 months. Patients with evaluable baseline and ≥ 1 MRI during the corresponding period were included in the analysis. The difference in TGR in each arm was assessed by slope of tumor growth over time using a linear mixed model. RESULTS 331 patients were randomized to vorasidenib (n=168) or placebo (n=163). Median follow-up was 14.2 months. On-treatment TGR was −2.5% (95% CI, −4.7, −0.2) with vorasidenib (n=167) and 13.9% (95% CI, 11.1, 16.8) with placebo (n=161). In patients with available imaging data, TGR pre- and post-treatment with vorasidenib (n=56) was 13.2% (95% CI, 10.3, 16.3) and −3.3% (95% CI, −5.2, −1.2), respectively, while placebo (n=67) was 18.3% (95% CI, 15.0, 21.7) and 12.2% (95% CI, 9.5, 14.9), respectively. In patients who crossed over from placebo with available imaging data (n=38), TGR pre- and post-crossover was 22.4% (95% CI, 15.7, 29.4) and 5.2% (95% CI, −3.8, 15.0), respectively. CONCLUSIONS Tumor growth was observed in patients with mIDH1/2 gliomas before receiving vorasidenib or placebo. Treatment with vorasidenib reduced the TGR and shrunk tumor volume, whereas continued growth in tumor volume was observed in patients receiving placebo.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.058
GPT teacher head0.369
Teacher spread0.311 · 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 designRandomized 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

Citations18
Published2023
Admission routes1
Has abstractyes

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