Poly-ADP ribose polymerase inhibitor and androgen receptor signaling inhibitor for all comers for first-line treatment of metastatic castration-resistant prostate cancer: is gene sequencing out?
Bibliographic record
Abstract
PURPOSE OF REVIEW: The landscape for first-line therapy (1L) of metastatic castration-resistant prostate cancer (mCRPC) is rapidly shifting. In the past 2 years, three phase 3 trials have examined the addition of a poly-ADP ribose polymerase inhibitor (PARPi) to an androgen receptor-signaling inhibitor (ARSI) in 1L. The FDA and the EMA recently considered whether one of these combinations should be approved for "all comers." Here, we review the trial designs, assays for homologous recombination repair mutations (HRRm) and BRCA mutations ( BRCA m), and predictive capacity of mutational status on treatment efficacy to understand the basis for the FDA decision. RECENT FINDINGS: The phase 3 trials, PROpel, MAGNITUDE, and TALAPRO-2, each compared PARPi and ARSI to placebo (PBO) plus ARSI. PROpel and TALAPRO-2 (cohort 1) included all comers (i.e., no prospective biomarker selection), while MAGNITUDE prospectively assigned patients to HRRm and HRR nonmutated cohorts and TALAPRO-2 (cohort 2) included only those with HRRm. Radiographic progression-free survival (rPFS) was the primary endpoint, and overall survival (OS) was a key secondary endpoint in all trials. Although rPFS with a PARPi and ARSI was improved versus PBO with ARSI, major conclusions differed. SUMMARY: The nuances and interpretation of these trials provide an understanding of the rationale for the FDA's decision to restrict the approval of olaparib and abiraterone and prednisone (AAP) as 1L therapy to those with biomarker evidence of BRCA m.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".