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Concomitant G-CSF use in maintaining an efficacious dose and safe delivery of docetaxel in combination with darolutamide in patients with metastatic hormone sensitive prostate cancer (mHSPC): ARASENS, a phase 3 study.

2025· article· en· W4407699679 on OpenAlexaff
Michael Ong, Hiroyoshi Suzuki, Matthew R. Smith, Bertrand Tombal, Maha Hussain, Fred Saad, Karim Fizazi, Frank Verholen, My H. Pham, Shankar Srinivasan, Aly‐Khan A. Lalani

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsMcMaster UniversityJuravinski Cancer CentreUniversité de MontréalOttawa Hospital
Fundersnot available
KeywordsMedicineDocetaxelConcomitantProstate cancerOncologyInternal medicineCancer

Abstract

fetched live from OpenAlex

152 Background: In ARASENS, darolutamide (DARO) + androgen deprivation therapy (ADT) + docetaxel (DOC) significantly reduced risk of death by 32.5% vs placebo (PBO) + ADT + DOC in patients (pts) with mHSPC, with a similar incidence of treatment-emergent adverse events (TEAEs) between DARO and PBO treatment arms. DOC is associated with the risk of febrile neutropenia, which can be managed by DOC dose reduction and/or use of granulocyte colony stimulating factor (G-CSF). We report the impact of DOC dose intensity on the safety and efficacy of the ARASENS triplet regimen and evaluate the benefits of G-CSF use in maintaining effective dose and safe delivery of DOC. Methods: Pts were randomized to receive DARO 600 mg orally twice daily or PBO, with ADT + DOC. Baseline characteristics, G-CSF use, safety, overall survival (OS), and time to prostate-specific antigen (PSA) progression were analyzed according to DOC relative dose intensity (RDI; ≤85% vs >85%), defined as the ratio of DOC dose received vs protocol-defined full planned dose (75 mg/m 2 × 6 cycles). Results: Of the 1305 pts (DARO n=651; PBO n=654), 32 (2%) never received DOC or had no RDI data; 800 (60%) had DOC dose modifications. Of 1273 pts with DOC RDI data (DARO n=637; PBO n=636), >97% received an efficacious dose (RDI >80%), and use of DARO did not impact DOC RDI. Concomitant G-CSF was used in 48% (DARO) and 46% (PBO) of pts with DOC dose modifications vs 42% (DARO) and 45% (PBO) in the overall population, and was mainly used for secondary prophylaxis after first DOC dose in both the DOC dose modification population (DARO 184/186 [99%]; PBO 188/190 [99%]) and the overall population (DARO 269/272 [99%]; PBO 282/284 [99%]). G-CSF use was higher in pts with DOC RDI ≤85% (DARO 70%; PBO 74%) vs RDI >85% (DARO 39%; PBO 41%). Pt demographics and baseline disease characteristics were broadly similar between RDI ≤85% and >85% subgroups; >60% of pts with RDI ≤85% were from Asia Pacific. Incidences of grade ≥3 TEAEs/grade ≥3 neutropenia/grade ≥3 febrile neutropenia were higher with DOC RDI ≤85%, but DOC discontinuation rates were similar between RDI subgroups (≤85%: DARO 7%, PBO 11%; >85%: DARO 8%, PBO 11%). TEAEs leading to DOC dose modification were higher with DOC RDI ≤85% (DARO 93%; PBO 97%) vs RDI >85% (DARO 26%; PBO 25%). OS and time to PSA progression were similar between the RDI ≤85% and >85% subgroups within each treatment group. Conclusions: Appropriate DOC dose modification and G-CSF use allowed almost all pts (97%) to receive an efficacious dose of DOC, with no difference in OS and time to PSA progression for RDI ≤85% vs >85%. Addition of DARO to ADT + DOC did not increase DOC dose modification rates or G-CSF use. Clinical trial information: NCT02799602 .

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.443
Teacher spread0.380 · 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 designNon-randomized 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

Citations1
Published2025
Admission routes1
Has abstractyes

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