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A signal-seeking trial of olaparib and durvalumab in homologous repair-deficient tumors: A sub-study of the cancer molecular screening and therapeutics (MoST) program.

2020· article· en· W3030227576 on OpenAlexaff
Anthony M. Joshua, Amy Prawira, Subotheni Thavaneswaran, Rasha Cosman, Chee Khoon Lee, Katrin Marie Sjoquist, John Simes, David M. Thomas, David Espinoza, Lucille Sebastian, Mandy L. Ballinger, Wendy Hague, Sarah Chinchen, Emily Collignon, Maya Kansara, Talia Palacios, John P. Grady, Hayley P Barker, Keith Thornton

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsOlaparibMedicineCohortDurvalumabInternal medicineOncologyClinical endpointCancerSurgeryClinical trialImmunotherapyNivolumabGeneticsBiology

Abstract

fetched live from OpenAlex

3073 Background: Data on the utility of a PARP inhibitor in combination with a checkpoint inhibitor remain limited, particularly in the histology agnostic setting with homologous recombination deficiency (HRD). This study evaluated the clinical activity of the combination of olaparib and durvalumab with the primary study endpoint of progression-free survival (PFS) at 6 months (PFS6m). Methods: This was a phase II, single-arm, signal-seeking study of the MoST program. Patients were recruited into two cohorts based on HRD genes, agnostic to histology: (1) BRCA 1/2 deficient tumours, excluding breast, prostate, ovarian cancers, and (2) other HRD related genes. Molecular testing was performed using in-house and commercial panels on archival tumour tissue centrally adjudicated by a molecular tumour board. All patients were treated with olaparib 300mg bid for 1 month, followed by combination with durvalumab 1500mg q4 weekly for 13 cycles. Olaparib treatment was then continued until disease progression. Results: Between Nov 2017-Feb 2019, 48 patients were enrolled (16 to BRCA 1/2 cohort 1 and 32 to HRD related genes cohort 2). Most common tumour sites were bone/soft tissue (15%, N=7), pancreas (13%, N=6) and stomach (8%, N=4). Overall best response in cohort 1 was PR (25%, N=4) and SD 4 (25%, N=4), and cohort 2 was PR (6%, N=2) and SD (56%, N=18). Median PFS was 3.65m (Cohort 1) and 3.56m (Cohort 2) respectively. PFS6m was 35% (Cohort 1) and 38% (Cohort 2) respectively. PDL1 status was not predictive of olaparib and durvalumab benefit. The most common grade 3/4 adverse events were anemia (11%%, N=4), abdominal pain (9%, N=3), increased lipase (9%,N=3), increased amylase (9%, N=3), dyspnea (6%, N=2), Hyperglycemia dyspnea (6%, N=2), Pancreatitis dyspnea (6%, N=2) and hematuria (6%, N=2). Conclusions: Olaparib and durvalumab show promising activity in a histology agnostic setting, particularly in BRCA deficient tumours. Further research is needed to identify biomarkers that correlate with treatment benefit. Results from longer clinical follow-up and additional biomarker analyses will be presented. Clinical trial information: ACTRN12617001000392 .

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)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0040.001

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 head0.168
GPT teacher head0.475
Teacher spread0.307 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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