PROfound: Efficacy of olaparib (ola) by prior taxane use in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC) and homologous recombination repair (HRR) gene alterations.
Bibliographic record
Abstract
134 Background: Optimal sequencing of therapies for mCRPC is not established. In the Phase III PROfound study (NCT02987543), ola significantly prolonged radiographic progression-free survival (rPFS) vs physician’s choice of new hormonal agent (pcNHA) in pts with mCRPC and an alteration in genes with a direct or indirect role in HRR. We report exploratory subgroup analyses by prior taxane (yes vs no). Methods: Men with mCRPC that had progressed on prior NHA were randomized to ola (tablets; 300 mg bid) or pcNHA (enzalutamide or abiraterone). Pts had alterations in BRCA1, BRCA2 or ATM (Cohort A) or ≥1 of 12 other prespecified genes with a direct or indirect role in HRR (Cohort B). Stratification factors were prior taxane use and measurable disease. rPFS was assessed by blinded independent central review with RECIST v1.1 + PCWG3. Results: Subgroup analyses of rPFS and overall survival (OS) favored ola vs pcNHA irrespective of prior taxane in Cohort A, Cohorts A+B and pts with a BRCA1 and/or BRCA2 or CDK12 alteration (Table). In the ATM subgroup hazard ratio (HR) point estimates for rPFS and OS were lower in pts who had received prior taxane vs pts who had not, but 95% CIs overlapped and pt numbers were small so data should be interpreted with caution. Conclusions: The benefit of ola over pcNHA in pts with mCRPC and HRR gene alterations was generally independent of prior taxane status in the overall study population. Clinical trial information: NCT02987543. [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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".