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Record W4281632793 · doi:10.1093/neuonc/noac079.226

HGG-11. Clinical characteristics and clinical evolution of a large cohort of pediatric patients with primary central nervous system (CNS) tumors and tropomyosin receptor kinase (TRK) fusion.

2022· article· en· W4281632793 on OpenAlexaff
Audrey‐Anne Lamoureux, Michael Fisher, Lauriane Lemelle, Elke Pfaff, Christof M. Kramm, Bram De Wilde, Bernarda Kazanowska, Caroline Hutter, Stefan M. Pfister, Dominik Sturm, David Jones, Daniel Orbach, Gaëlle Pierron, Scott Raskin, Alexander Drilon, Eli L. Diamond, Guilherme Harada, Michal Zápotocký, Benjamin Ellezam, Alexander G. Weil, Dominic Venne, Marc Barritault, Pierre Leblond, Hallie Coltin, Rawan Hammad, Uri Tabori, Cynthia Hawkins, Jordan R. Hansford, Déborah Meyran, Craig Erker, Kathryn McFadden, Mariko Sato, Nicholas G. Gottardo, Hetal Dholaria, Dorte Schou Nørøxe, Hiroaki Goto, David S. Ziegler, Frank Y. Lin, D. Williams Parsons, Holly Lindsay, Tai‐Tong Wong, Yen‐Lin Liu, Kuo-Sheng Wu, Andrea Flynn Franson, Eugene I. Hwang, Ana Aguilar-Bonilla, Sylvia Cheng, Chantel Cacciotti, Maura Massimino, Elisabetta Schiavello, Paul Wood, Lindsey M. Hoffman, Andréa Maria Cappellano, Álvaro Lassaletta, An Van Damme, Anna Llort, Nicolas U. Gerber, Mariella Spalato Ceruso, Anne Bendel, Maggie Skrypek, Dima Hamideh, Naureen Mushtaq, Andrew W. Walter, Nada Jabado, Aysha Alsahlawi, Jean‐Pierre Farmer, Christina Coleman Abadi, Sabine Mueller, Claire Mazewski, Dolly Aguilera, Nathan Robison, Katrina O’Halloran, Samuel Abbou, Pablo Berlanga, Birgit Geoerger, Ingrid Øra, Christopher L. Moertel, Evangelia Razis, Anastasia Vernadou, François Doz, Theodore W. Laetsch, Sébastien Perreault

Bibliographic record

VenueNeuro-Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineLondon Health Sciences CentreBC Children's HospitalMontreal Children's HospitalIzaak Walton Killam Health CentreHospital for Sick Children
Fundersnot available
KeywordsTrk receptorMedicineInternal medicineOncologyRadiation therapyPathologyGastroenterologyNeurotrophinReceptor

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: TRK fusions are detected in less than 3% of CNS tumors. Given their rarity, there are limited data on the clinical course of these patients. METHODS: We contacted 166 oncology centers worldwide to retrieve data on patients with TRK fusion-driven CNS tumors. Data extracted included demographics, histopathology, NTRK gene fusion, treatment modalities and outcomes. Patients less than 18 years of age at diagnosis were included in this analysis. RESULTS: Seventy-three pediatric patients with TRK fusion-driven primary CNS tumors were identified. Median age at diagnosis was 2.4 years (range 0.0–17.8) and 60.2 % were male. NTRK2 gene fusions were found in 37 patients (50.7%), NTRK1 and NTRK3 aberrations were detected in 19 (26.0%) and 17 (23.3%), respectively. Tumor types included 38 high-grade gliomas (HGG; 52.1%), 20 low-grade gliomas (LGG; 27.4%), 4 embryonal tumors (5.5%) and 11 others (15.1%). Median follow-up was 46.5 months (range 3-226). During the course of their disease, a total of 62 (84.9%) patients underwent surgery with a treatment intent, 50 (68.5%) patients received chemotherapy, 35 (47.9%) patients received radiation therapy, while 34 (46.6%) patients received NTRK inhibitors (3 as first line treatment). Twenty-four (32.9%) had no progression including 9 LGG (45%) and 9 HGG (23.6%). At last follow-up, only one (5.6%-18 evaluable) patient with LGG died compared to 11 with HGG (35.5%-31 evaluable). For LGG the median progression-free survival (PFS) after the first line of treatment was 17 months (95% CI: 0.0-35.5) and median overall survival (OS) was not reached. For patients with HGG the median PFS was 30 months (95% CI: 11.9-48.1) and median OS was 182 months (95% CI 20.2-343.8). CONCLUSIONS: We report the largest cohort of pediatric patients with TRK fusion-driven primary CNS tumors. These results will help us to better understand clinical evolution and compare outcomes with ongoing clinical trials.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.283
Teacher spread0.270 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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