Efficacy and Safety of Darolutamide in Combination With Androgen-Deprivation Therapy and Docetaxel in Black Patients From the Randomized ARASENS Trial
Bibliographic record
Abstract
BACKGROUND: In the ARASENS trial (NCT02799602), darolutamide in combination with androgen-deprivation therapy (ADT) and docetaxel significantly reduced the risk of death by 32.5% (HR, 0.68; 95% CI, 0.57-0.80; P < .0001) compared with placebo plus ADT with docetaxel in patients with metastatic hormone-sensitive prostate cancer (mHSPC). We present efficacy and safety of darolutamide versus placebo in Black patients from ARASENS. PATIENTS AND METHODS: Patients with mHSPC were randomized 1:1 to darolutamide 600 mg or placebo twice daily in combination with ADT and docetaxel. The primary endpoint was overall survival. Key secondary endpoints included time to castration-resistant prostate cancer (CRPC) and safety. RESULTS: In ARASENS, 54 Black patients received darolutamide (n = 26) or placebo (n = 28) plus ADT and docetaxel. In Black patients, overall survival favored darolutamide versus placebo (median, not reached vs. 38.7 months; stratified HR, 0.41; 95% CI, 0.17-1.02), with 4-year survival rates of 62% versus 41%. The darolutamide group also had longer time to CRPC compared with the placebo group (median, not reached vs .12.6 months; HR, 0.09; 95% CI, 0.02-0.30). The safety profile of darolutamide in Black patients was consistent with that observed for the overall ARASENS population (grade 3/4 treatment-emergent adverse events, TEAEs: 61.5% vs. 66.1%; serious TEAEs: 42.3% vs. 44.8%). CONCLUSION: In this small population of Black patients with mHSPC from the ARASENS trial, darolutamide was associated with an improvement in survival and time to CRPC and was well tolerated. Efficacy and safety findings in Black patients were consistent with the overall ARASENS 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".