Matching-adjusted indirect comparison of talazoparib plus enzalutamide versus abiraterone acetate and docetaxel in mCRPC
Bibliographic record
Abstract
Aims The absence of direct comparisons between talazoparib plus enzalutamide (TALA+ENZA) and current standard of care hinders evaluating their relative efficacy for first-line (1 L) metastatic castration resistant prostate cancer (mCRPC). This study aimed to compare TALA+ENZA (TALAPRO-2) to abiraterone acetate plus prednisone (AAP) (COU-AA-302) and docetaxel (TAX 327) using a matching-adjusted indirect treatment comparison (MAIC).Methods A systematic literature review using the Ovid® interface was performed to identify relevant evidence. Patient-level data from TALAPRO-2 and published data from COU-AA-302 and TAX 327 were used to match populations on clinically relevant confounders. The MAICs were conducted for radiographic progression-free survival (rPFS), overall survival (OS), objective response rate (ORR), along with additional efficacy outcomes.Results In all-comers, TALA+ENZA statistically significantly prolonged rPFS (HR: 0.256; 95% confidence interval [CI]: 0.183, 0.359; p < 0.0001), OS (HR: 0.557; 0.405, 0.766; p = 0.0003), and improved ORR (OR: 3.924; 2.017, 7.634; p = 0001) versus AAP. In all-comers, TALA+ENZA significantly prolonged OS (HR: 0.446; 0.316, 0.631; p < 0.0001) and improved ORR (OR: 13.081; 5.757, 29.721; p < 0.0001) versus docetaxel. All other efficacy outcomes statistically favored TALA+ENZA.Conclusions These results suggest TALA+ENZA improves clinical outcomes relative to AAP and docetaxel in the 1 L mCRPC all-comers population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".