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A 16 year-retrospective study of refractory meningiomas: Prognostic factors and systemic treatments.

2024· article· en· W4399319907 on OpenAlexaff
Dan-Thanh Christine Nguyen, Cyril Nader, Karl Bélanger, Sarah Lapointe, Bernard Lemieux, Émilie Lemieux‐Blanchard, Jean-Paul Bahary, Laura Masucci, Carole Lambert, David Roberge, Robert Moumdjian, Moujaheb Labidi, Romain Cayrol, Marie Florescu

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineRefractory (planetary science)Retrospective cohort studySystemic therapyInternal medicineOncologySurgeryCancer

Abstract

fetched live from OpenAlex

2085 Background: Meningiomas are the most common brain tumors, with no established standard systemic treatment for refractory cases after surgical and radiotherapeutic interventions. This study aims to identify prognostic factors for overall survival in refractory meningioma and document patient evolution with systemic treatments. Methods: In a retrospective study, we identified patients with meningioma initially followed at CHUM university hospital between 2006 and 2022. Patients with progression after first-line treatment and over 6 months of follow-up were included. The population was divided into two: group 1 received surgery and/or radiotherapy for progression, and group 2 received additional systemic treatments. Survival analysis with Kaplan-Meier curves and group comparisons (Log-Rank, Fisher's Exact Tests) were conducted. Results: A total of750 patients with meningioma were identified. 99 (13%) progressed after first-line treatment. Among them, 70 (9%) were categorized in group 1 and 29 (4%), in group 2. The median follow-up time from diagnosis was 7.5 years. The overall 10-year survival rate was higher in group 1 compared to group 2 (88% vs 62%). Prognostic factors affecting survival were identified as the following: disease progression after second-line treatment, age ≥ 65 years, and grade 2 or 3. When comparing PFS-1 after first-line treatment, they were similar between group 1 and group 2 (mPFS-1: 2.63 vs 3.49 years; p = 0.421). However, PFS-2 after second-line treatment was significantly shorter in group 2 (mPFS-2 : 12.6 vs 2.3 years ; p < 0.001). Age of ≥ 65 years (10-year survival: 57% vs 89%; p < 0.001) and higher grades (10 year survival: 90% grade 1 vs 58% - grade 2 vs 75% - grade 3; p = 0.027) were associated with lower survival rates. The number of lesions (unique or multiple) and localization (supra or infratentorial) of tumors had no significant impact on survival (p=0.257; p = 0.482). Regarding systemic treatments, 7 patients (25%) received Bevacizumab. It was the treatment associated with the longest PFS (mPFS = 22.5 months) when compared to Hydroxyurea (n=18 [62%], mPFS = 4 months), Somatostatin (n = 5 [17%], mPFS = 8 months), a combination of Hydroxyurea and Somatostatin (n=7 [24%], mPFS = 8 months) and Sunitinib (n=3 [10%], mPFS = 14 months). For patients discontinuing systemic treatment, median survival was 5 months. Systemic treatments were well-tolerated. Among moderate to severe side effects (grade ≥ 2), we documented bradycardia (Somatostatin, n=1), elevated liver enzymes (Sunitinib, n=1), anemia and neutropenia (Hydroxyurea, n=3) and proteinuria (Bevacizumab, n=1). Conclusions: Prognostic factors for survival in meningioma include age ≥ 65 years, grades 2 and 3, and the occurrence of a second progression. Our study highlights Bevacizumab in systemic treatment strategies which was well tolerated in our patients.

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 score0.007
Threshold uncertainty score0.014

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.112
GPT teacher head0.445
Teacher spread0.333 · 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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