Patient reported outcomes (PROs) among patients with metastatic castration-resistant prostate cancer (mCRPC) by homologous recombination repair mutations (HRRm) gene clusters: Findings from the phase 3 TALAPRO-2 study cohort 2.
Bibliographic record
Abstract
109 Background: Cohort 2 of the TALAPRO-2 (NCT03395197) study demonstrated benefit in radiographic progression-free survival (rPFS) with talazoparib (TALA) plus enzalutamide (ENZA) (n=200) vs placebo (PBO) + ENZA (n=199) across gene subgroups in men with HRRm receiving first-line treatment for mCRPC. Post-hoc analyses aimed to understand PROs by HRR gene clusters. Methods: PROs were assessed at day 1 and scheduled visits (every 4 weeks until week 53, then every 8 weeks) until radiographic progression using the EORTC QLQ-C30 and PR25 and BPI-SF. Prespecified PRO endpoints included overall mean change from baseline (per longitudinal repeated measures mixed-effects model) and time to definitive deterioration (TTDD) with a clinically meaningful change of ≥10-points for the EORTC QLQ-C30. Stratified log-rank test and Cox proportional hazards model were used to make TTDD between-arm comparisons. Mutually exclusive gene clustering alteration dominance hierarchy was applied in the following order: any BRCA1/2 alteration (BRCAm cluster), PALB2 (PALB2 cluster), CDK12 (CDK12 cluster), ATM (ATM cluster), then any of all other HRR7genes (MLH1, CHEK2, NBN, FANCA, ATR, RAD51C, MRE11A). Results: A significantly longer TTDD in GHS/QoL was observed for TALA + ENZA vs PBO + ENZA in the BRCAm (HR=0.54, 95% CI (0.29, 0.99); p=0.043; median NE vs 19.0) and CDK12 clusters (HR=0.43 (0.19, 0.98); p=0.019, median 30.7 vs 16.6). Overall changes from baseline in GHS/QoL and worst pain are reported in the Table. Conclusions: PRO findings by HRR gene clusters are consistent with rPFS benefit analyses by gene clusters. This was an exploratory post-hoc analysis limited by missing PRO assessments and sample sizes especially in the PALB2 cluster. Clinical trial information: NCT03395197 . [Table: see text]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".