Darolutamide plus androgen-deprivation therapy in high-risk biochemical recurrence of prostate cancer (ARASTEP)
Bibliographic record
Abstract
Patients with prostate cancer treated with radiotherapy (RT) or radical prostatectomy (RP) as primary therapy may develop biochemical recurrence (BCR), which requires effective treatment to delay disease progression. The ARASTEP study (NCT05794906) aims to determine whether the addition of darolutamide to androgen-deprivation therapy (ADT) improves radiologic progression-free survival (rPFS) using prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) compared with placebo plus ADT in patients with high-risk BCR.Approximately 970 patients from 243 sites globally will receive either darolutamide 600 mg or placebo twice daily, both with ADT, for 24 months or until disease progression, unacceptable toxicity, or withdrawal of consent. Eligible patients will have been treated by primary RT or RP ± adjuvant RT (ART) or salvage RT (SRT), and present with high-risk BCR (prostate-specific antigen [PSA] doubling time <12 months and PSA ≥0.2 ng/mL after RP [± ART/SRT] or PSA ≥2 ng/mL above nadir after primary RT only), ≥1 PSMA PET/CT-positive lesion (negative on conventional imaging), serum testosterone >150 ng/dL, and Eastern Cooperative Oncology Group performance status 0/1. The primary endpoint is rPFS using PSMA PET/CT, with secondary endpoints including metastasis-free survival, time to castration-resistant prostate cancer, overall survival, quality of life, and safety.CLINICAL TRIAL REGISTRATION: www.clinicaltrials.gov identifier is NCT05794906.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.004 | 0.001 |
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".