Matching-adjusted indirect comparisons (MAICs) of talazoparib plus enzalutamide (TALA+ENZA) versus olaparib plus abiraterone and prednisone/prednisolone (OLAP+AAP) for first-line (1L) therapy in patients with metastatic castration-resistant prostate cancer (mCRPC) and homologous recombination repair mutations (HRRm)/BRCAm.
Bibliographic record
Abstract
5063 Background: Poly-ADP ribose polymerase inhibitors (PARPi) in combination with a novel hormonal therapy (NHT) have shown benefit for the 1L treatment of mCRPC in an all-comers population as well as HRRm and BRCAm subpopulations (TALA+ENZA [TALAPRO-2; NCT03395197] and OLAP+AAP [PROpel; NCT03732820]). In the absence of head-to-head studies, their comparative efficacy is unknown. The relative efficacy of TALA+ENZA (n=200 HRRm; n=71 BRCAm) vs OLAP+AAP (n=111 HRRm; n=47 BRCAm) in these subpopulations were estimated using MAICs for radiographic progression-free survival (rPFS) based on blinded independent central review and overall survival (OS). Methods: Unanchored MAICs were conducted using individual patient data from TALAPRO-2 Cohort 2 (data cutoff [DCO]: 03/10/22 [rPFS/OS]) and published summary level data from PROpel (DCO: 30/07/21 [rPFS]; 12/10/22 [OS]). To align across the two trials, patients from TALAPRO-2 with specific HRRm/BRCAm (co-occurring or standalone) that were not assessed in PROpel were removed from the dataset for each analysis. TALAPRO-2 patients were also matched based on PROpel’s eligibility criteria and characteristics were adjusted for key prognostic factors identified in the literature and clinical expertise including prior taxane chemotherapy in castration sensitive prostate cancer (CSPC), visceral metastasis, bone only metastasis, Eastern Cooperative Oncology Group score, prostate-specific antigen levels, Gleason score, BRCA1 and BRCA2. Results: After the removal of patients with specific gene mutations not assessed in PROpel and those who received prior NHT in CSPC, 157 and 64 patients remained in the TALA+ENZA arm for HRRm and BRCAm, respectively. The comparative effect estimates for rPFS and OS are presented in the Table. None of the results were statistically significant. Conclusions: These analyses demonstrate numerically favorable results for TALA+ENZA compared to OLAP+AAP highlighting its therapeutic potential in 1L mCRPC for patients with HRRm and BRCAm. Limitations include inability to adjust for all characteristics and biases due to unobserved trial differences. [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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".