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Record W3111693169 · doi:10.1093/neuonc/noaa215.859

SURG-12. PREDICTORS OF SURVIVAL AND UTILITY OF INTRAOPERATIVE MRI FOR RESECTION OF GRADE II ASTROCYTOMAS AND OLIGODENDROGLIOMAS: A MULTICENTER ANALYSIS

2020· article· en· W3111693169 on OpenAlexaff
Alexander T. Yahanda, Bhuvic Patel, Amar Shah, Daniel P. Cahill, Garnette R. Sutherland, John Honeycutt, Randy L. Jensen, Keith M. Rich, Joshua L. Dowling, David D. Limbrick, Ralph G. Dacey, Albert Kim, Eric C. Leuthardt, Gavin P. Dunn, Gregory J. Zipfel, Jeffrey R. Leonard, Matthew D. Smyth, Mitesh V. Shah, Steven R. Abram, John A. Evans, Michael R. Chicoine

Bibliographic record

VenueNeuro-Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineAstrocytomaProgression-free survivalGliomaInternal medicineRetrospective cohort studyOverall survivalResectionMagnetic resonance imagingGastroenterologySurgeryOncologyRadiology

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Few studies use large, multi-institutional patient cohorts to examine the role of intraoperative MRI (iMRI) in the resection of grade II gliomas. We assessed the impact of iMRI and other factors on overall survival (OS) and progression-free survival (PFS) for newly-diagnosed grade II astrocytomas and oligodendrogliomas. METHODS Retrospective analyses of a multicenter database assessed the impact of patient-, treatment-, and tumor-related factors on OS/PFS. RESULTS 232 resections (112 astrocytomas, 120 oligodendrogliomas; 135 males; mean age 36.2 ± 0.9 years) were analyzed. Oligodendrogliomas had longer OS (p< 0.001) and PFS (p=0.009) than astrocytomas. Multivariate regression showed that extent of resection (EOR), including gross-total (GTR) versus near-total (NTR) resection (p=0.02, HR: 0.64, 95% CI: 0.25-.79) and GTR versus subtotal resection (STR) (p=0.006, HR: 0.23, 95% CI: 0.08-0.66), was associated with longer OS. GTR versus NTR (p=0.04, HR: 0.49, 95% CI: 0.29-.85), GTR versus STR (p=0.02, HR: .54, 95% CI: .32-.91) and iMRI use (p=0.02, HR: 0.54, 95% CI: 0.32-0.92) were associated with longer PFS. Frontal (p=0.048, HR: 2.11, 95% CI: 1.01-4.43) and occipital/parietal (p=0.003, HR: 3.59, 95% CI: 1.52-8.49) locations were associated with shorter PFS (versus temporal). Kaplan-Meier analyses showed longer OS with increasing EOR (p=0.03) and 1p/19q gene deletions (p=0.02). PFS improved with increasing EOR (p=0.01), GTR versus NTR (p=0.02), and resections above STR (p=0.04). Factors influencing adjuvant treatment (35.3% of patients) included age (p=0.002, OR: 1.04) and EOR (p=0.037, OR: 0.41 for NTR versus STR; p=0.003, OR: 0.39 for GTR versus STR), but not glioma subtype or location, as determined by logistic regression. Additional tumor resection after iMRI was performed in 105/159 (66%) iMRI cases, yielding GTR in 54.5% of these cases. CONCLUSIONS EOR significantly improves OS and PFS for patients with grade II astrocytomas and oligodendrogliomas. Intraoperative MRI may improve EOR and was associated with increased PFS.

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)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.034
GPT teacher head0.310
Teacher spread0.276 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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