TALAPRO-1: A phase II study of talazoparib (TALA) in men with DNA damage repair mutations (DDRmut) and metastatic castration-resistant prostate cancer (mCRPC)—First interim analysis (IA).
Bibliographic record
Abstract
119 Background: Phase 2 and 3 studies with poly(ADP-ribose) polymerase inhibitors (PARPi) have demonstrated antitumor activity in patients (pts) with mCRPC with DDRmut who were previously treated with novel hormonal therapy (NHT). We report the first IA of a Phase 2 study of TALA, a potent inhibitor and trapper of PARP. Methods: TALAPRO-1 (NCT03148795) is enrolling pts (N ≈ 100) with measurable soft tissue disease, progressive mCRPC, and DDRmut likely to sensitize to PARPi (including ATM, ATR, BRCA1, BRCA2, CHEK2, FANCA, MLH1, MRE11A, NBN, PALB2, RAD51C), who received 1–2 chemotherapy regimens (≥1 taxane-based) and progressed on ≥1 NHT (enzalutamide/abiraterone acetate). Pts receive oral TALA 1 mg/d (moderate renal impairment, 0.75 mg/d) until radiographic progression, unacceptable toxicity, or consent withdrawal. Primary endpoint is objective response rate (ORR; blinded independent review). Secondary endpoints are time to OR, duration of response, prostate-specific antigen (PSA) decrease ≥50%, circulating tumor cell (CTC) count conversion (to CTC = 0 and <5 per 7.5 mL of blood), time to PSA progression, radiographic progression-free survival (rPFS), overall survival, safety, pt-reported outcomes, and pharmacokinetics. A planned IA of safety and efficacy was performed after 20 pts with BRCA1/2 mutations were on treatment for ≥8 wks. Results: 81 pts received TALA as of June 5, 2019; 43 pts enrolled by Feb 12, 2019 were evaluable for the primary endpoint (20 BRCA1/2, 2 PALB2, 14 ATM, 7 other). All had received docetaxel and 49% prior cabazitaxel. Overall ORR (95% CI) was 25.6% (13.5–41.2), ORRBRCA1/2 50.0% (27.2–72.8), ORRATM 7.1% (0.2–33.9). Overall median (95% CI) rPFS was 5.6 months (mo) (3.5–8.2), rPFSBRCA1/2 8.2 mo (5.6–NE), rPFSATM 3.5 mo (1.7–8.1). Most common treatment-emergent adverse events (≥20%) were anemia, nausea, asthenia, decreased appetite, constipation, and platelet count decreased. Conclusions: TALA monotherapy demonstrates encouraging antitumor activity in docetaxel-pretreated mCRPC pts, especially those with BRCA1/2mut, and was generally well tolerated. This study was sponsored by Pfizer Inc. Clinical trial information: NCT03148795.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".