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Record W4416140125 · doi:10.1093/neuonc/noaf201.0942

INNV-53. Precision Medicine in Pediatric Neuro-Oncology-Experience from a tertiary care center in Canada

2025· article· en· W4416140125 on OpenAlexaffabout
Meziane Brizini, Tina Drimes, Jessica Streilein, Annie Ong, Cathy Bourne, Annie Drapeau, Colin Kazina, Patrick J. McDonald, Marc Geirnaert, Allison Feely, Oliver Bucher, Magimairajan Vanan

Bibliographic record

VenueNeuro-Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsDabrafenibAdverse effectCohortPrecision medicineCancerRadiation therapyRetrospective cohort studyTertiary care

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION The increased use of multi-omics testing in Neuro-Oncology has provided newer therapeutic options directed against molecular alterations for the treatment of Pediatric brain tumors, referred to as Precision medicine with targeted therapy (TT). We describe here the real-world use of innovative /targeted therapies for pediatric brain tumors from Cancer Care Manitoba in Canada. METHODS This is a retrospective study of all pediatric brain tumors diagnosed between 2010-2023 treated with at least one dose of TT. RESULTS Forty patients were treated with 50 lines of TT; Seven patients (N=7/40, 17.5%) received multiple lines of TT. Low grade gliomas (LGG) formed the largest cohort (N=26/40, 59.1%). Initial treatment included surgery (N=12/40, 30%), chemotherapy (N=15/40, 37.5%), radiotherapy (N=10/40, 25%) or any combination of the three modalities (N=9/40, 22.5%). Twenty-seven (N=27/50, 54%) patients were initiated with TT before first relapse. TT was initiated in 55% of the patients (N=22/40) based on molecular findings. Targetable genomic alterations were found mostly in RAS/MAPK and PI3K/AKT/mTOR pathway. Monotherapy with MEK inhibitors (Trametinib, Selumetinib, N=30/50, 60%) was the most common regime; 12 different combinations of TT were used; most common being Dabrafenib and Trametinib. Drugs were accessed through compassionate access programs in 94% of cases (N=47/50). Among all patients treated with TT, ten (N=10/50, 20%) had partial response and 28 (N=29/50, 63.6%) had stable disease; 11 patients (11/50, 22%) had progression while on TT; leading to a disease control rate (DCR) of 78% and a clinical benefit rate (CBR) of 63.3%. Adverse events involved most commonly the skin, hair and /nails (N=24, 66.7%). TT was stopped due to toxicities in 6 patients (N=6/50, 12%) with no deaths reported. CONCLUSION Our study confirms existing data in the literature regarding precision medicine in pediatric cancer with high CBR along with good quality of life and minimal toxicities.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.293
Teacher spread0.281 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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