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Phase III, double-blind, placebo-controlled, 2-cohort, randomized study of saruparib (AZD5305) in combination with new hormonal agents in patients with metastatic castration-sensitive prostate cancer with and without homologous recombination repair mutation (EvoPAR-Prostate01).

2024· article· en· W4399394761 on OpenAlexaff
Kim N., Neeraj Agarwal, Andrew J. Armstrong, Eva Hellmis, Friederike Schlürmann, Mikio Sugimoto, Yüksel Ürün, Nianzeng Xing, Mehreteab Aregay, Julianne Lima, Didier Meulendijks, Arun Azad

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineProstate cancerPlaceboHomologous recombinationOncologyHormonal therapyInternal medicineCancerHormoneCohortProstateUrologyPathologyGene

Abstract

fetched live from OpenAlex

TPS5123 Background: PARP inhibitors (PARPi) in combination with new hormonal agents (NHAs) are approved for treatment of metastatic castration-resistant prostate cancer (mCRPC). PARPi utilization in earlier lines of treatment may result in greater magnitude of benefit. Saruparib is a potential best-in-class PARPi, which selectively inhibits and traps PARP1, has minimal effect on PARP2, and hence may offer an improved therapeutic window compared with currently approved nonselective PARPi. The efficacy and safety of saruparib plus NHAs for the treatment of metastatic castration-sensitive prostate cancer (mCSPC) and mCRPC are being assessed in the phase I/IIa PETRANHA study (NCT05367440). The phase III EvoPAR-Prostate01 study (NCT06120491) is evaluating the efficacy and safety of saruparib plus physician’s choice of NHA (abiraterone, darolutamide, or enzalutamide) compared with placebo plus physician’s choice of NHA in participants with mCSPC. Methods: This is a 2-cohort, 2-arm, randomized, double-blind, placebo-controlled, multicenter global study. Key eligibility criteria include age ≥18 years, histologically confirmed mCSPC ( de novo or recurrent low- or high-volume disease), ECOG PS 0-1, and confirmed, prospectively defined homologous recombination repair gene mutation (HRRm) status (defined by the presence/absence of pathogenic/likely pathogenic mutations in ≥1 of the genes BRCA1, BRCA2, ATM, CDK12, PALB2, RAD51B, RAD51C, RAD51D,and BARD1). Participants must be receiving androgen deprivation therapy throughout the study or have undergone bilateral orchiectomy, and must be suitable for treatment with NHAs. Key exclusion criteria include prior therapy with PARPi, prior chemotherapy or NHAs in the mCSPC setting (prior NHAs for localized disease permitted), and history of, or suspected, myelodysplastic syndrome/acute myeloid leukemia. Participants are allocated to either the HRRm or non-HRRm cohort based on prospective testing of both tumor tissue and circulating tumor DNA. Participants are randomized 1:1 to receive saruparib plus physician’s choice of NHA or placebo plus physician’s choice of NHA. Treatment continues until disease progression, unacceptable toxicity, or participant-initiated withdrawal. The primary endpoint is radiographic progression-free survival (rPFS), with overall survival (OS) a key secondary endpoint. Planned statistical analyses of rPFS and OS will be conducted within each cohort using a stratified log-rank test. Approximately 1,800 participants (550 HRRm; 1,250 non-HRRm) will be randomized. Enrollment began in November 2023 and is ongoing. Clinical trial information: NCT06120491 .

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)0.003
metaresearch head score (Gemma)0.003
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 score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.002

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 head0.082
GPT teacher head0.455
Teacher spread0.373 · 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

Citations13
Published2024
Admission routes1
Has abstractyes

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