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A phase II trial of olaparib and durvalumab in patients with recurrent IDH-mutated gliomas.

2024· article· en· W4399324904 on OpenAlexafffund
Xin Wang, Yosef Ellenbogen, Christianne Mojica, Gustavo Duarte Ramos Matos, Roa Alsajjan, Ronald Ramos, Seth Climans, Mathew Voisin, Vikas Patil, Stephanie Baker, Yin-Ling Chan, Thiago Pimentel Muniz, Andrew Gao, Ben X. Wang, Gelareh Zadeh, Warren Mason, Eric Xueyu Chen

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsJuravinski Cancer CentreUniversity Health NetworkPrincess Margaret Cancer Centre
FundersFondation Brain Canada
KeywordsMedicineDurvalumabOlaparibOncologyInternal medicineCancer researchCancerGeneticsGeneImmunotherapyPoly ADP ribose polymeraseNivolumab

Abstract

fetched live from OpenAlex

2013 Background: Isocitrate dehydrogenase mutations (IDHmt) define astrocytomas and oligodendrogliomas. IDHmt results in accumulation of R-2-hydroxyglutarate (2HG), leading to epigenetic dysregulation and defective homologous recombination repair, providing a rationale for poly (adenosine 5’-diphophate-ribose) polymerase (PARP) inhibitors. PARP inhibition upregulates PD-L1 so the combination with immune checkpoint inhibition is potentially synergistic. Methods: Patients (pts) with recurrent high-grade IDHmt gliomas were enrolled in this phase II open-label study (NCT03991832). Eligibility included progressive disease with up to 2 prior lines of systemic therapies and ECOG 0–1. Pts received olaparib 300 mg twice daily continuously and durvalumab 1500 mg IV every 4 weeks. Simon’s optimal two-stage design was used. The primary objective was overall response rate (ORR) and disease control rate (DCR) by RANO criteria. Secondary objectives included overall survival (OS), progression free survival (PFS) and safety.Exploratory biomarkers of response and resistance were assessed with serial blood samples using cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) as well as multiplex-immunohistochemistry. Results: In the 29 pts enrolled between January 2020–February 2023, median age was 40.5 (range 23–66) and 41% were female. Initial tumor grade was 2 in 9, 3 in 8 and 4 in 12 pts, respectively. Median time to enrollment from tumour diagnosis was 5.9 years. All had prior resection and median number of prior systemic therapies was 2. One patient clinically deteriorated before starting treatment. ORR was 10%, 95% CI 2.2–27%, with responses in 3 pts. One pt with grade 4 astrocytoma had a complete response and remains on treatment after 33 months. The other 2 responders with grade 4 astrocytoma had response durations of 4.1 and 9.8 months. DCR was 28% (95% CI 12.7–47.2%) with 5 additional pts demonstrating stable disease. With a median follow-up of 33 months, mOS was 9.5 months (95% CI 4.3–19.3) and mPFS was 1.9 months (95% CI 1.8–3.0). There was no treatment-related grade 3–4 toxicities. Any grade toxicities included fatigue (48%), nausea (17%), diarrhea (10%), and cytopenias (3%). Using serial cfMeDIP-seq, cell free DNA methylomes comparing responders versus progressors using the top differentially methylated regions can predict treatment response with high accuracy (AUC 0.833). Post progression, differentially methylated genes converge on TGF-β and signal transduction pathways, suggesting possible mechanisms of resistance. Multi-modal analysis of long-term responders will additionally be presented. Conclusions: Combination treatment with olaparib and durvalumab for pts with IDHmt glioma is well tolerated but has limited efficacy in unselected pts. cfMeDIP-seq can reliably predict tumour progression providing a blood-based biomarker of treatment response. Clinical trial information: NCT03991832 .

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.512
Teacher spread0.400 · 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".

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Citations6
Published2024
Admission routes2
Has abstractyes

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