Effects of Prior Local Therapy by Radical Prostatectomy or Radiotherapy on the Efficacy and Quality of Life of Patients Treated With Darolutamide in ARAMIS
Bibliographic record
Abstract
BACKGROUND: Darolutamide plus androgen-deprivation therapy (ADT) improved metastasis-free survival (MFS) by 2 years and reduced the risk of death by 31% in nonmetastatic castration-resistant prostate cancer (nmCRPC) in ARAMIS. Prior local therapy may influence the efficacy of subsequent systemic therapy. This post hoc analysis of ARAMIS evaluated the effect of prior local therapy on the efficacy and health-related quality of life (HRQoL) of darolutamide. METHODS: Patients with nmCRPC were randomized to darolutamide (n = 955) or placebo (n = 554) while continuing ADT. MFS, overall survival (OS), time to prostate-specific antigen (PSA) progression, and HRQoL deterioration-free survival (DetFS) were estimated for patients with and without local therapy and by treatment using Kaplan-Meier methods. RESULTS: Darolutamide increased MFS versus placebo in patients with (HR, 0.36; 95% CI, 0.26-0.48) and without (HR, 0.46; 95% CI, 0.36-0.59) local therapy. Median OS was 48.6 months for placebo without local therapy and not reached in either the darolutamide group or placebo group with local therapy. Darolutamide 3-year OS rates were 86.9% (95% CI, 83.0-90.8) and 79.0% (95% CI, 66.2-78.1) in patients with and without local therapy, respectively. Darolutamide showed evidence of improved OS versus placebo in patients with prior local therapy (HR, 0.80; 95% CI, 0.50-1.30) and a greater effect in those without local therapy (HR, 0.67; 95% CI, 0.50-0.90). Darolutamide delayed time to PSA progression and HRQoL deterioration regardless of local therapy. CONCLUSIONS: Darolutamide versus placebo improved MFS, OS, time to PSA progression, and HRQoL DetFS independent of prior local therapy, consistent with the overall ARAMIS population. TRIAL REGISTRATION: ClinicalTrials.gov registration: NCT02200614.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".