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Final patient-reported outcomes (PROs) in unselected men receiving talazoparib (TALA) + enzalutamide (ENZA) vs placebo (PBO) + ENZA as initial treatment for metastatic castration-resistant prostate cancer (mCRPC): Results from the phase 3 TALAPRO-2 study.

2025· article· en· W4410811633 on OpenAlexaff
Nobuaki Matsubara, Arun Azad, Neeraj Agarwal, Fred Saad, Ugo De Giorgi, Jae Young Joung, Peter C.C. Fong, Robert Jones Jones, Stefanie Zschaebitz, Jan Oldenburg, Neal D. Shore, Curtis Dunshee, Joan Carles, André P. Fay, Paul Cislo, Cynthia G. Healy, Melissa Kirker, Karim Fizazi

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersPfizer
KeywordsEnzalutamideMedicineProstate cancerPlaceboInternal medicineOncologyCancerAndrogen receptorAlternative medicinePathology

Abstract

fetched live from OpenAlex

11120 Background: TALAPRO-2 demonstrated statistically significant improvement with TALA + ENZA vs PBO + ENZA in radiographic progression-free survival (primary endpoint; HR=0.63; 95% CI, 0.51–0.78; P <0.0001) in unselected men with mCRPC. Prior PRO analyses (data cutoff: Aug 16, 2022) reported no clinically meaningful between-arm differences in any functioning scales and a longer time to definitive deterioration (TTDD) in global health status (GHS)/quality of life (QoL) for TALA + ENZA (median 30.8 mo) vs PBO + ENZA (25.0 mo; HR=0.780; 95% CI, 0.62–0.99; P =0.038). Here we report updated (data cutoff: Sep 3, 2024) final PROs for the unselected cohort. Methods: PROs were assessed at day 1 (baseline) and scheduled visits (every 4 weeks until week 53, and then every 8 weeks) until radiographic progression using the EORTC QLQ-C30 and its prostate cancer module, QLQ-PR25, and worst pain by BPI-SF item 3. Prespecified PRO analyses included overall mean change from baseline (per longitudinal repeated measures mixed-effects model), time to deterioration (TTD), and TTDD. The clinically meaningful threshold was ≥10 points for EORTC scales and ≥2 points for BPI-SF. Between-arm comparisons of TTD/TTDD were made using a stratified log-rank test and a Cox proportional hazards model. Results: Of the 805 men randomized to treatment, 793 (TALA + ENZA, n=395; PBO + ENZA, n=398) had 1 baseline + ≥1 follow-up PRO score. With extended follow-up, median TTDD for GHS/QoL in the TALA + ENZA arm was 41.5 mo vs 34.1 mo in the PBO + ENZA arm (HR=0.878; 95% CI, 0.704–1.096; P =0.2487). Median TTDD for urinary symptoms in the TALA + ENZA arm was 59.8 mo vs 58.0 mo in the PBO + ENZA arm (HR=0.861; 95% CI, 0.622–1.191; P =0.3655). No clinically meaningful between-arm differences in QLQ-C30 functioning and symptoms scales were observed (Table). No between-arm difference in TTD for worst pain by BPI-SF was observed. Conclusions: With extended follow-up, QoL was maintained with TALA + ENZA. These data confirm that QoL is not compromised when TALA is added to ENZA, for initial treatment of unselected men with mCRPC. Clinical trial information: NCT03395197 . QLQ-C30 Scale Estimated Mean Difference, TALA + ENZA – PBO + ENZA (95% CI) P Value Functioning GHS/QoL -2.2 (-4.3, -0.1) 0.0382 Physical -1.6 (-3.9, 0.7) 0.1663 Role -1.7 (-4.2, 0.9) 0.2009 Emotional -0.9 (-2.7, 1.0) 0.3620 Cognitive -0.9 (-3.0, 1.1) 0.3791 Social -0.9 (-2.9, 1.2) 0.4088 Symptoms Fatigue 2.4 (0.1, 4.7) 0.0437 Nausea + Vomiting 0.8 (-0.1, 1.6) 0.0723 Pain -0.8 (-3.3, 1.7) 0.5270 Positive values favor TALA + ENZA for GHS/QoL and functioning scales; negative values favor TALA + ENZA for symptoms scales.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.191
GPT teacher head0.529
Teacher spread0.338 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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