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Randomized phase 2 study of nivolumab (nivo) plus either standard or reduced dose bevacizumab (bev) in recurrent glioblastoma (rGBM).

2021· article· en· W3166474048 on OpenAlexfundno aff
Manmeet S. Ahluwalia, Yasmeen Rauf, Hong Li, Patrick Y. Wen, David M. Peereboom, David A. Reardon

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsnot available
FundersBristol-Myers Squibb Canada
KeywordsMedicineBevacizumabNivolumabInternal medicineOncologyProgression-free survivalOverall survivalGastroenterologySurgeryChemotherapyImmunotherapyCancer

Abstract

fetched live from OpenAlex

2015 Background: Trials with anti-PD1 in rGBM have shown limited efficacy. VEGF is highly up regulated proangiogenic growth factor in GBM contributing to tumor-associated immunosuppression. Preclinical data suggests a potential dose effect of anti-VEGF therapy on immunomodulation. Hence, a combination of anti-PD1 and anti-VEGF may be a promising approach in rGBM. Methods: 90 patients with first-recurrent GBM were randomized (1:1) to nivolumab (240 mg IV Q2 weeks) with bevacizumab at standard (10 mg/kg; Arm A) or at low dose (3 mg/kg; Arm B) IV Q2 weeks. Stratification included extent of resection, age, performance status and MGMT methylation status. Single cell RNA sequencing with CITE-seq was used to analyze blood samples from pre- and 8 weeks post-treatment among 8 responders and 8 non-responders. Progression-free survival (PFS) and overall survival (OS) were compared between two arms. Results: 90 patients (Median age 60.6 years ranged 27.4-86.4, 67.8% male, median KPS 80) were enrolled between May 2018 and Jan 2020. Patients were followed in median 7.7 months (Range 0.7, 28.2). 35 of 88 patients were MGMT methylated (2 indeterminate). Overall OS was not significantly different between arm A and arm B (1 year: 41.1 vs 37.7%, p = 0.14), while OS was better for arm A in age > 60 (At 1-year: 46.2% vs 23.8%; Median: 10.6 vs 5.9 months; P = 0.046). OS was no different in the two arms for age ≤ 60 years (At 1-year: 35.6% vs 56.4; Median 8.0 vs 12.4 months; P = 0.90). Single cell RNA sequencing with CITE-seq was used to analyze blood samples from 16 patients, baseline and 8 weeks post treatment. Standard dose bevacizumab treated patients had decreased myeloid derived suppressor cells and an inflammatory response gene signature at 8 weeks. Most frequent toxicities ( > 20%) included fatigue (45.6%), proteinuria (34.4 %), diarrhea (28.9%), hypertension (23.3%) and lipase increase (21.1%). Toxicities in grade 3-4 were hypertension (7.8%), fatigue (5.6) and other non-neurological toxicities including DVT, PE, infection, and abnormal liver function. Conclusions: Overall PFS and OS rates appear similar for nivolumab with either standard or low-dose bevacizumab compared to historical benchmarks of bevacizumab monotherapy. Nivolumab with standard bevacizumab may benefit older but not younger patients. Ongoing response evaluation and immunocorrelative data will be presented. Clinical trial information: NCT03452579.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.118
GPT teacher head0.495
Teacher spread0.377 · 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 designRandomized 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

Citations14
Published2021
Admission routes1
Has abstractyes

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