MétaCan
Menu
Back to cohort
Record W4405696229 · doi:10.1080/14796694.2024.2442900

Combination niraparib and abiraterone for HRR-altered metastatic castration-resistant prostate cancer

2024· review· en· W4405696229 on OpenAlexaffabout
H. Roberts, Corinne Maurice‐Dror, Kim Nguyen

Bibliographic record

VenueFuture Oncology · 2024
Typereview
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsMedicineProstate cancerAbiraterone acetatePARP inhibitorAndrogen receptorEnzalutamideOncologyInternal medicinePARP1Cancer researchAndrogen deprivation therapyAbirateroneCancerPoly ADP ribose polymeraseGeneBiology

Abstract

fetched live from OpenAlex

Metastatic prostate cancer remains incurable. Though significant progress has been made in the field, the search for agents that improve outcomes for patients is ongoing. Several clinical trials have explored the benefit of combining PARP inhibitors (PARPi) with androgen receptor pathway inhibitors (ARPIs) for metastatic castrate resistant prostate cancer (mCRPC), especially those cancers with alterations in homologous recombination repair (HRR) genes. Niraparib, a highly selective inhibitor of PARP1 and PARP2, has been shown to confer a radiographic progression-free survival benefit in the treatment of mCRPC with HRR-associated gene alterations, particularly BRCA1 and BRCA2 (BRCA1/2), when combined with abiraterone acetate plus prednisolone (AAP). This combination has recently been approved in the USA, Canada and Europe for patients with mCRPC and a BRCA1/2 gene mutation. This review summarizes the evidence with regards to the pharmacologic activity and clinical efficacy of niraparib with a specific focus on its efficacy in combination with AAP in mCRPC patients with HRR alterations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.100
GPT teacher head0.464
Teacher spread0.364 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueFuture OncologySame topicPARP inhibition in cancer therapyFrench-language works237,207