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Record W2767664052 · doi:10.1093/neuonc/nox168.028

ACTR-37. PREDICTIVE SIGNIFICANCE OF IDH1/2 MUTATION AND 1p/19q CO-DELETION STATUS IN A POST-HOC ANALYSIS OF NRG ONCOLOGY/RTOG 9802: A PHASE III TRIAL OF RT VS RT + PCV IN HIGH RISK LOW-GRADE GLIOMAS

2017· article· en· W2767664052 on OpenAlexaff
Erica H. Bell, Jianwen Zhang, Edward G. Shaw, Jan C. Buckner, Geoffrey Barger, Stephen W. Coons, Dennis E. Bullard, Minesh P. Mehta, Mark R. Gilbert, Paul D. Brown, K. Stelzer, Jessica L. Fleming, Joseph P. McElroy, Cynthia Timmers, Aline Paixão Becker, Andrea L. Salavaggione, Ziyan Liu, Ken Aldape, David Brachman, Stanley Z. Gertler, Albert Murtha, Christopher J. Schultz, David H. Johnson, Hui‐Kuo G. Shu, Arnab Chakravarti

Bibliographic record

VenueNeuro-Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsOttawa Regional Cancer FoundationPrincess Margaret Cancer CentreOttawa HospitalUniversity Health Network
Fundersnot available
KeywordsInternal medicineOncologyMedicineHazard ratioIDH1Univariate analysisBiopsyProportional hazards modelPost-hoc analysisMultivariate analysisConfidence intervalBiologyGeneMutation

Abstract

fetched live from OpenAlex

This study investigated the predictive significance of IDH1/2 mutations and 1p/19q co-deletion in patients with high risk (age≥40 or subtotal resection/biopsy) low-grade gliomas (LGGs), randomized to receive RT with or without PCV after biopsy/surgical resection in NRG Oncology/RTOG 9802. Importantly, this is the very first phase III study to analyze the predictive value of these sub-groups in LGGs using prospectively-collected, well-annotated clinical data. Immunohistochemistry and/or IonTorrent sequencing were used to determine IDH1/2 status. Oncoscan and/or 450K methylation data were used to determine 1p/19q status. To estimate by marker status the treatment effect on overall survival (OS) and progression-free survival (PFS), hazard ratios (HRs) were calculated using the Cox proportional hazard model and tested using the log-rank test in a post-hoc and exploratory analysis. Interaction effects between marker status and treatment were tested. Of all the randomized eligible patients in NRG Oncology/RTOG 9802, 97(39%) had sufficient DNA for profiling. Of these, 36(37%) were IDHmut/non-co-deleted, 33(34%) were IDHmut/co-deleted, and 28(29%) were IDHnon-mut. Upon univariate analyses, the IDHmut/non-co-deleted sub-group was significantly correlated with better PFS with the addition of PCV (HR=0.31; p=0.005) and OS (HR=0.36; p=0.02). The IDHmut/co-deleted sub-group was significantly correlated with better PFS with the addition of PCV (HR=0.16; p=0.002), but not OS (HR=0.31; p=0.13). There was no significant difference observed with the addition of PCV in the IDHnon-mut sub-group for either OS or PFS. Tests on interaction effects revealed no statistical significance. Our analyses suggest a putative predictive value of 1p/19q co-deletion and IDH1/2 mutations for high-risk LGGs, based on the observed differences in the treatment effect by marker status. Our results also support the hypothesis that IDHnon-mut high-risk LGG patients do not benefit from the addition of PCV to RT. FUNDING: U10CA21661, U10CA180868, U10CA180822, and U10CA37422. Also, R01CA108633, R01CA169368, RC2CA148190, U10CA180850-01, BTFC, OSU-CCC (all to AC).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.020
GPT teacher head0.346
Teacher spread0.326 · 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 designNon-randomized trial
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

Citations5
Published2017
Admission routes1
Has abstractyes

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