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Record W4409148665 · doi:10.1001/jamaoncol.2025.0329

Chromosome 1p Loss and 1q Gain for Grading of Meningioma

2025· article· en· W4409148665 on OpenAlexaffabout
Alexander Landry, Justin Z. Wang, Vikas Patil, Jeff Liu, Chloe Gui, Yosef Ellenbogen, Andrew Ajisebutu, Leeor Yefet, Qingxia Wei, Olivia Singh, Julio Sosa, Sheila Mansouri, Aaron Cohen‐Gadol, Ghazaleh Tabatabai, Marcos Tatagiba, Felix Behling, Jill S. Barnholtz‐Sloan, Andrew E. Sloan, Silky Chotai, Lola B. Chambless, Alireza Mansouri, Serge Makarenko, Stephen Yip, Felix Ehret, David Capper, Derek S. Tsang, Jennifer Moliterno, Murat Günel, Felix Sahm, Kenneth Aldape, Andrew Gao, Gelareh Zadeh, Farshad Nassiri

Bibliographic record

VenueJAMA Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity of British ColumbiaUniversity Health Network
Fundersnot available
KeywordsMedicineMeningiomaCDKN2AGrading (engineering)Internal medicineCDKN2BProportional hazards modelOncologyConcordanceCohortPathologyCancerBiology

Abstract

fetched live from OpenAlex

Importance: The World Health Organization (WHO) classification of central nervous system tumors (CNS) grading for meningioma was updated in 2021 to include rare molecular features, namely homozygous deletions of CDKN2A or CDKN2B and TERT promotor alterations. Previous work, including the cIMPACT-NOW statement, has discussed the potential value of including chromosomal copy number alterations to help refine the current grading system. Objective: To identify chromosomal copy number alterations that could be used to improve the current CNS WHO grading of meningioma. Design, Setting, and Participants: In this cohort study, patients with surgically treated meningioma were followed-up until recurrence or progression of disease or death. Chromosomal copy number alterations were then correlated with progression-free survival (PFS) to identify new outcome biomarkers. This study included patients with a histopathological diagnosis of meningioma from multiple institutions in Canada, the US, and Germany, with molecular data collection starting in 2016. Data were analyzed from January to September 2024. Exposures: All patients underwent surgery for meningioma and a subset underwent radiation therapy. Main Outcomes and Measures: The main outcome was PFS. Cox regression analysis was used to identify copy number alterations associated with outcomes in the context of WHO grading. Results: Among 1964 patients with meningioma (1256 female; median [IQR] age, 58 [48-69] years) assessed, loss of chromosome 1p in WHO grade 1 meningiomas was associated with significantly worse outcomes compared with tumors without loss of 1p (median PFS, 5.83 [95% CI, 4.36-∞] years vs 34.54 [95% CI, 16.01-∞] years; log-rank P < .001). Outcomes of patients with WHO grade 1 tumors with loss of chromosome 1p were comparable to those of patients with WHO grade 2 tumors (median PFS, 4.48 [95% CI, 4.09-5.18] years). Combined loss of chromosome 1p and gain of chromosome 1q were associated with outcomes that were highly concordant with WHO grade 3 tumors, regardless of initial grade (median PFS: grade 1, 2.23 [95% CI, 1.28-∞] years; grade 2, 1.90 [95% CI, 1.23-2.25] years; grade 3, 2.27 [95% CI, 1.68-3.05] years). Conclusions and Relevance: These findings highlight a role for cytogenetic profiling in the next iteration of CNS WHO grading, with a specific focus on chromosome 1p loss and 1q gain, suggesting that chromosome 1p loss, in addition to 22q loss, should be added as a criterion for a CNS WHO grade of 2 and addition of 1q gain as a criterion for a CNS WHO grade of 3.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.339
Teacher spread0.317 · 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

Citations18
Published2025
Admission routes2
Has abstractyes

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