Comparative efficacy and safety of talazoparib plus enzalutamide and other first-line treatments for metastatic castration-resistant prostate cancer
Bibliographic record
Abstract
BACKGROUND: Talazoparib plus enzalutamide (TALA + ENZA) has demonstrated antitumor activity in the phase 3 clinical trial (TALAPRO-2; NCT03395197) as first-line (1L) therapy in men with asymptomatic or mildly symptomatic metastatic castration-resistant prostate cancer (mCRPC). Although many active interventions are available, randomized controlled trials (RCTs) involving talazoparib have only been conducted to assess its efficacy and safety compared to enzalutamide. To estimate comparisons between all relevant interventions, indirect comparisons are needed. OBJECTIVE: To estimate the comparative efficacy and safety of TALA + ENZA in 1L patients with mCRPC by conducting a systematic literature review and network meta-analyses (NMAs). METHODS: Databases were searched using Ovid, along with several gray literature sources to identify RCTs evaluating treatments in 1L mCRPC (PROSPERO registration: CRD42021283512). Feasibility assessment evaluated trial suitability for NMA inclusion and Bayesian or frequentist NMAs were conducted for evaluable efficacy and safety outcomes, respectively. RESULTS: Thirty-three RCTs met the eligibility criteria and were feasible for NMAs. Across multiple efficacy outcomes assessed, except for overall survival (OS), TALA + ENZA was ranked the most efficacious treatment. For OS, TALA + ENZA showed the second-highest probability of being the most effective treatment; second to docetaxel 50 mg plus prednisolone 10 mg. With respect to safety outcomes, TALA + ENZA, in general, showed increased rates of hematological adverse events. CONCLUSIONS: TALA + ENZA showed favorable results across multiple efficacy endpoints, but not across hematological toxicities compared with other 1L treatments in asymptomatic or mildly symptomatic mCRPC in the all-comers patient population.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".