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Efficacy and safety of darolutamide (DARO) in combination with androgen-deprivation therapy (ADT) and docetaxel (DOC) by disease volume and disease risk in the phase 3 ARASENS study.

2023· article· en· W4324136162 on OpenAlexaff
Maha Hussain, Bertrand Tombal, Fred Saad, Karim Fizazi, Cora N. Sternberg, E. David Crawford, Neal D. Shore, Evgeny Kopyltsov, Arash Rezazadeh, Martin Boegemann, Dingwei Ye, Felipe Melo Cruz, Hiroyoshi Suzuki, Shivani Kapur, Shankar Srinivasan, Frank Verholen, Iris Kuss, Heikki Joensuu, Matthew R. Smith

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineDocetaxelInternal medicineDiseaseProstate cancerProportional hazards modelAndrogen deprivation therapyOncologyCancer

Abstract

fetched live from OpenAlex

15 Background: In ARASENS (NCT02799602), DARO plus ADT and DOC significantly reduced the risk of death by 32.5% (HR 0.68; 95% CI: 0.57–0.80; P<0.0001) vs placebo (PBO) + ADT + DOC in patients (pts) with metastatic hormone-sensitive prostate cancer (mHSPC), with similar overall incidences of treatment-emergent adverse events (TEAEs) between groups. The effect of DARO on overall survival (OS) was consistent across prespecified subgroups, including de novo and recurrent disease. For pts with mHSPC, outcomes based on disease volume and risk provide additional information to clinicians. Methods: Pts with mHSPC were randomized 1:1 to DARO 600 mg twice daily or PBO, with ADT + DOC. High-volume disease was defined as visceral metastases and/or ≥4 bone metastases with ≥1 beyond the vertebral column/pelvis (CHAARTED criteria). High-risk disease was defined as ≥2 risk factors: Gleason score ≥8, ≥3 bone lesions, and presence of measurable visceral metastasis (LATITUDE criteria). OS for these subgroups was assessed using an unstratified Cox regression model. Results: Of 1305 pts in the full analysis set, 1005 (77%) had high-volume disease, 912 (70%) had high-risk disease, 300 (23%) had low-volume disease, and 393 (30%) had low-risk disease. DARO + ADT + DOC prolonged OS regardless of high- or low-volume disease with HRs of 0.69 and 0.68 vs PBO + DOC + ADT, respectively. OS benefit of DARO vs PBO was also similar for pts with high- or low-risk disease. DARO improved clinically relevant secondary endpoints vs PBO in high/low-volume and risk subgroups, with HRs generally in the range of those observed in the overall population. Incidences of TEAEs were consistent with the overall ARASENS population across subgroups by high/low volume and high/low risk. Conclusions: In pts with mHSPC, the benefits of early treatment intensification with DARO + ADT + DOC on OS and key pt-relevant secondary efficacy endpoints vs PBO + ADT + DOC were similar in patients with high- and low-volume as well as high- and low-risk mH+SPC. The favorable safety profile of DARO was reconfirmed in high/low-volume and high/low-risk populations. DARO + ADT + DOC sets a new standard of care for pts with mHSPC. Clinical trial information: NCT02799602 . [Table: see text]

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.081
GPT teacher head0.465
Teacher spread0.384 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2023
Admission routes1
Has abstractyes

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