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Record W4390237156 · doi:10.1093/neuonc/noad227

Consensus framework for conducting phase I/II clinical trials for children, adolescents, and young adults with pediatric low-grade glioma: Guidelines established by the International Pediatric Low-Grade Glioma Coalition Clinical Trial Working Group

2023· article· en· W4390237156 on OpenAlexaff
Sabine Mueller, Jason Fangusaro, Arzu Onar Thomas, Thomas S. Jacques, Pratiti Bandopadhayay, Peter de Blank, Roger J. Packer, Maryam Fouladi, Antoinette Schouten‐van Meeteren, David Jones, Arie Perry, Yoshiko Nakano, Darren Hargrave, David Riedl, Nathan Robison, Marita Partanen, Michael J. Fisher, Olaf Witt

Bibliographic record

VenueNeuro-Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick Children
FundersBrain Tumour CharityPediatric Brain Tumor Foundation
KeywordsClinical trialMedicineClinical endpointPaceQuality of life (healthcare)GliomaDosingClinical study designIntensive care medicinePediatricsInternal medicineNursing

Abstract

fetched live from OpenAlex

Within the last few decades, we have witnessed tremendous advancements in the study of pediatric low-grade gliomas (pLGG), leading to a much-improved understanding of their molecular underpinnings. Consequently, we have achieved successful milestones in developing and implementing targeted therapeutic agents for treating these tumors. However, the community continues to face many unknowns when it comes to the most effective clinical implementation of these novel targeted inhibitors or combinations thereof. Questions encompassing optimal dosing strategies, treatment duration, methods for assessing clinical efficacy, and the identification of predictive biomarkers remain unresolved. Here, we offer the consensus of the international pLGG coalition (iPLGGc) clinical trial working group on these important topics and comment on clinical trial design and endpoint rationale. Throughout, we seek to standardize the global approach to early clinical trials (phase I and II) for pLGG, leading to more consistently interpretable results as well as enhancing the pace of novel therapy development and encouraging an increased focus on functional endpoints as well and quality of life for children faced with this disease.

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)0.007
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.201
GPT teacher head0.462
Teacher spread0.261 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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