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DUO-O: A randomized phase III trial of durvalumab (durva) in combination with chemotherapy and bevacizumab (bev), followed by maintenance durva, bev and olaparib (olap), in newly diagnosed advanced ovarian cancer patients.

2019· article· en· W2947257322 on OpenAlexaff
Philipp Harter, Mariusz Bidziński, Nicoletta Colombo, Anne Floquet, M.J. Rubio Pérez, Jae‐Weon Kim, Stéphanie Lheureux, Christian Marth, Gitte‐Bettina Nyvang, Aikou Okamoto, Alexander Reuß, Giovanni Scambia, Fabian Trillsch, Mehmet Ali Vardar, Els Van Nieuwenhuysen, Jasmine Lichfield, Paul Rugman, Philip Twumasi‐Ankrah, Carol Aghajanian

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineBevacizumabOlaparibOncologyInternal medicineBRCA mutationOvarian cancerCancerPARP inhibitorChemotherapyMaintenance therapySurgery

Abstract

fetched live from OpenAlex

TPS5598 Background: Ovarian cancer (OC) is the leading cause of death from gynecologic cancers in US women. Despite high response rates to first-line treatment, ~70% of patients (pts) relapse within 3 years and then remain largely incurable. First-line treatment needs to be improved to achieve long-term remission in pts and improve the cure rate. The Phase III SOLO1 trial showed a meaningful clinical benefit for olap maintenance therapy in newly diagnosed OC pts with a BRCA mutation (Moore et al N Engl J Med 2018). Preliminary data suggest that combining a PD-L1 inhibitor, anti-angiogenic and PARP inhibitor (triplet therapy) may achieve a synergistic antitumor effect. The DUO-O study (NCT03737643) evaluates the efficacy and safety of treatment combinations involving standard-of-care platinum-based chemotherapy (chemo), VEGF inhibitor bev, anti-PD-L1 antibody durva and PARP inhibitor olap, in women with newly diagnosed advanced OC. Methods: Eligible pts for this double-blind, randomized, Phase III study must have newly diagnosed, advanced, high-grade epithelial OC and either have completed primary surgery or plan to have interval debulking surgery. Depending on their tumor BRCA mutation (tBRCAm) status (determined by central test), pts will join one of two independent cohorts. Pts in the non-tBRCAm cohort (n~906) will be randomized (1:1:1) before cycle 2 to: a) chemo + bev + placebo (for 6 cycles) followed by bev (15 mg/kg [total 15 months]) + placebo maintenance treatment (IV and tablets); b) chemo + bev + durva (6 cycles) followed by bev + durva (1120 mg q3w [total 15 months]) + placebo (tablets) maintenance treatment; or c) chemo + bev + durva (6 cycles) followed by bev + durva + olap (300 mg bd tablets [24 months]) maintenance treatment. Pts in the open-label tBRCAm cohort (n~150) will receive 6 cycles of chemo + durva followed by durva + olap maintenance therapy, with optional use of bev. The primary endpoint of progression-free survival will be assessed by modified RECIST 1.1. Key secondary endpoints include overall survival, overall response rate and duration of response. Enrollment began in January 2019. Clinical trial information: NCT03737643.

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.022
GPT teacher head0.385
Teacher spread0.363 · 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

Citations46
Published2019
Admission routes1
Has abstractyes

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