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Record W4399787533 · doi:10.1093/neuonc/noae064.582

NFS-24. TUMOR VOLUME IN NEWLY DIAGNOSED OPTIC PATHWAY GLIOMAS ASSOCIATED WITH NF1 (NF1-OPG): PRELIMINARY RESULTS FROM THE INTERNATIONAL MULTICENTER NF1-OPG NATURAL HISTORY STUDY

2024· article· en· W4399787533 on OpenAlexaff
Robert A. Avery, Zhifan Jiang, Abhijeet Parida, Robert Listernick, Grant Liu, Rosalie E. Ferner, David H. Gutmann, Peter de Blank, Janice Lasky-Zeid, Nicole J. Ullrich, Gena Heidary, Miriam Bornhorst, Steven F. Stasheff, T.H.L. Rosser, Mark Borchert, 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, David Van Mater, Mays El-Diari, 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, Michael A. Brodsky, Adam J. Esbenshade, Sean P. Donahue, Julius Oattes, Alyssa Reddy, Gary Cutter, Marius George Linguraru, Michael J. Fisher

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsNatural historyMedicineVolume (thermodynamics)Multicenter studyOncologyInternal medicinePhysics

Abstract

fetched live from OpenAlex

Abstract BACKGROUND NF1-OPGs are amorphous tumors involving either single or multiple locations (optic nerve, chiasm, tract) along the anterior visual pathway (AVP). In this prospective study, we investigated how volumetric MRI measures of the AVP as well as other clinical variables are associated with treatment decisions in children with newly diagnosed NF1-OPGs. METHODS Children with newly diagnosed NF1-OPG whose MRI included a T1-weighted volumetric sequence without significant artifact at their enrollment visit were eligible for inclusion. All subjects underwent a quantitative ophthalmic exam to determine if visual acuity (VA) was normal. The neuro-oncologist/NF1 expert determined whether the subject would be observed or undergo treatment at that baseline visit. Volumetric MRI analysis was automatically performed using a deep learning network that measured AVP volume (mm3). Non-parametric group comparisons and multivariable logistic regression models evaluated the impact of age at enrollment, sex, NF1 inheritance type, AVP volume, and VA on the decision for immediate treatment with chemotherapy versus observation. RESULTS One-hundred twenty-three subjects met inclusion criteria. Subjects assigned to observation (N=112, 44% female) and subjects immediately treated with chemotherapy (N=11, 80% female) at enrollment were of similar age (2.7 and 2.8 years, respectively) and inheritance (p > 0.05). Abnormal VA was present more often in the treatment group (46%) compared to the observation group (17%, p <0.001). AVP volume was significantly greater in the treatment group (4,181.1mm3) compared to the observation group (1,819.8mm3, p <0.001). AVP volume, sex, and VA reached significance in univariable regression, however, in the multivariable regression model only the AVP volume (p < 0.001) was significantly associated with treatment initiation. DISCUSSION Children with greater NF1-OPG AVP volumes are treated more often compared with those with lower volumes. Volumetric measures of NF1-OPGs are a valuable metric in understanding treatment patterns and are positioned to help inform clinical decision making.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.023
GPT teacher head0.266
Teacher spread0.243 · 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
Published2024
Admission routes1
Has abstractyes

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