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Record W4399787756 · doi:10.1093/neuonc/noae064.579

NFS-21. DEMOGRAPHIC, CLINICAL AND IMAGING CHARACTERISTICS OF NEWLY DIAGNOSED OPTIC PATHWAY GLIOMAS ASSOCIATED WITH NF1: RESULTS FROM THE INTERNATIONAL MULTICENTER NF1-OPG NATURAL HISTORY STUDY

2024· article· en· W4399787756 on OpenAlexaff
Michael J. Fisher, Peter de Blank, Robert Listernick, Grant Liu, Rosalie E. Ferner, David H. Gutmann, Janice Lasky-Zeid, Nicole J. Ullrich, Gena Heidary, Miriam Bornhorst, Steven F. Stasheff, T.H.L. Rosser, March Borcher, Simone Arden-Holmes, Maree Flaherty, Trent R. Hummel, Walker Motley, Kevin Bielamowicz, Paul H. Phillips, Éric Bouffet, Arun Reginald, David S. Wolf, Jason H. Peragallo, Mays El-Dairi, David Van Mater, Aimee Sato, Kristina Tarczy‐Hornoch, Laura J. Klesse, Nick Hogan, Nicholas K. Foreman, Emily A. McCourt, Jeffrey C. Allen, Milan P. Ranka, Cynthia Campen, Shannon Beres, Christopher L. Moertel, Raymond G. Areaux, Duncan Stearns, Faruk Örge, John R. Crawford, Henry S. O’Halloran, Julius Oattes, Alyssa Reddy, Michael A. Brodsky, Adam J. Esbenshade, Sean P. Donahue, Gary Cutter, Robert A. Avery

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsNatural historyMedicineNatural history studyNeuroimagingMulticenter studyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Treatment and clinical management decisions for children with NF1-OPGs remain challenging as most existing data are retrospective and have not included standardized visual outcomes. In this study, we prospectively enrolled newly diagnosed NF1-OPGs and performed standardized neuro-oncology and ophthalmology assessments in order to develop evidence-based guidelines for monitoring and treatment. METHODS Children with NF1-OPG on MRI who were evaluated by both a study ophthalmologist and neuro-oncologist/NF1 expert within 1 month of radiologic diagnosis were eligible for enrollment. All subjects attempted quantitative visual acuity using Teller acuity cards (TAC) as well as ATS-HOTV testing. The neuro-oncologist/NF1 expert provided reasons for obtaining the MRI as well as initiating treatment, if applicable. Descriptive statistics calculated the success rate of acquiring TAC and reasons to obtain the MRI. RESULTS Two-hundred fifty subjects from 22 institutions were enrolled and had at least one visit beyond baseline (Median age 3.1 years, range 0.1–16.8; 53% female). TAC was successfully acquired in both eyes (N=195, 78%) and at least one eye in (N=206, 82%). ATS-HOTV was successfully acquired in both eyes (N=97, 39%) and at least one eye in (N=98, 39%). The two most common reasons to obtain an MRI were screening due to a diagnosis of NF1 (N=99, 39%) and ophthalmologic concern (N=81, 32%). At enrollment, continued observation occurred in a majority of subjects (N=221, 88%) while treatment with chemotherapy was initiated in only 11% (N=29). Twenty-nine (11%) subjects initially observed transitioned to treatment after enrollment (range: 2.5–25 months) thus far. DISCUSSION We present a prospective multicenter study of children with newly diagnosed NF1-OPGs. The ability to acquire quantitative visual acuity was higher than anticipated. The frequency of NF1-OPGs requiring treatment is lower than previously reported. Regression models of clinical and MRI features that prompted immediate treatment with chemotherapy versus observation will be discussed.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.077
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.028
GPT teacher head0.299
Teacher spread0.271 · 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.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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