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Rucaparib vs docetaxel (DTX) or second-generation androgen pathway inhibitor (ARPI) therapy for metastatic castration-resistant prostate cancer (mCRPC): TRITON3 final overall survival (OS) and safety.

2025· article· en· W4407700602 on OpenAlexaff
Alan H. Bryce, Josep M. Piulats, M. Neil Reaume, Peter Ostler, Joel Roger Gingerich, Elias Pintus, Srikala S. Sridhar, Richard Bambury, Urban Emmenegger, Henriette Lindberg, David Morris, Franco Nolè, John Nicholas Staffurth, Wassim Abida, Lisa Caunt, Darrin Despain, Charles J. Ryan, Karim Fizazi, Simon Chowdhury

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoHealth Sciences CentreCancerCare ManitobaOttawa HospitalPrincess Margaret Cancer CentreUniversity of Ottawa
Fundersnot available
KeywordsMedicineDocetaxelProstate cancerOncologyAndrogen deprivation therapyCabazitaxelOverall survivalInternal medicineAbirateroneCastrationAndrogen receptorUrologyCancerHormone

Abstract

fetched live from OpenAlex

155 Background: Primary results from the randomized, multicenter, open-label, phase 3 TRITON3 (NCT02975934) study of rucaparib, a poly(ADP-ribose) polymerase inhibitor (PARPi) in patients with chemotherapy-naive mCRPC and BRCA1/2 (BRCA) vs the control arm of physician’s choice of DTX or ARPI (abiraterone acetate [ABI] or enzalutamide [ENZ]) demonstrated that rucaparib significantly improved radiographic progression-free survival (rPFS, primary efficacy endpoint) vs physician’s choice. Here, we report final OS and safety results from TRITON3. Methods: Patients with disease progression after 1 prior second-generation ARPI in any setting were randomized 2:1 to rucaparib 600 mg BID or physician’s choice of DTX, ABI, or ENZ (control). OS was a key secondary endpoint tested initially in the BRCA subgroup, followed by the intent-to-treat (ITT) population in an ordered step-down multiple-comparisons procedure. Crossover from placebo to rucaparib was allowed after radiographic progression was confirmed by independent radiology review. Results: As of March 1, 2024 (final analysis data cutoff),patients with BRCA (N = 302) and ATM (N = 103) alterations were randomized (ITT, N = 405). After an overall median follow-up of 44.0 months, median OS in the BRCA subgroup in the rucaparib arm was 23.2 months vs 21.2 months for the physician’s choice control arm (HR, 0.91 [95% CI, 0.68–1.20]; P = 0.5044; Table). Hierarchical testing did not continue due to lack of statistical significance. No OS benefit was observed in the ITT population or ATM subgroup (Table). Median duration of treatment in rucaparib and physician’s choice arms was 8.3 and 5.1 months, respectively. The most frequent any-grade treatment emergent adverse event (TEAE) in the rucaparib (n = 270) and physician’s choice (n = 130) arms was asthenia/fatigue (61.5% and 63.1%, respectively). The most frequent grade ≥3 TEAE was anemia (23.7%) with rucaparib, and asthenia/fatigue (9.2%) with physician’s choice. Of the 135 patients in the physician’s choice arm, 77 patients had radiographic progression and 70 crossed over to rucaparib. Conclusions: Rucaparib remains the only PARPi to show improved rPFS vs a DTX-containing control arm and has a similar OS even when most patients cross over to rucaparib. Safety was consistent with prior reports. These data support rucaparib as a treatment option for patients with BRCA-mutated mCRPC. Clinical trial information: NCT02975934 . Median OS at final analysis. Group Rucaparib, n Physician's choice, n Rucaparib, months Physician's choice, months HR (95% CI) a BRCA 201 101 23.2 21.2 0.91 (0.68–1.20) ITT 270 135 22.8 21.7 0.99 (0.78–1.26) ATM 69 34 18.4 22.1 1.21 (0.77–1.90) a Calculated by stratified Cox proportional hazard model.

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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
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)0.0050.000

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 head0.204
GPT teacher head0.487
Teacher spread0.283 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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