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Prognostic significance of PSA>0.2 after 6-12 months treatment for metastatic hormone-sensitive prostate cancer (mHSPC) intensified by androgen-receptor pathway inhibitors (ARPI): A multinational real-world analysis of the IRONMAN registry.

2025· article· en· W4410811842 on OpenAlexaffabout
Michael Ong, Soumyajit Roy, Kim N., Tanya B. Dorff, Sebastién J. Hotte, Alexander W. Wyatt, Lauren E. Howard, Karen A. Autio, Deborah Enting, Aurelius Omlin, Joaquı́n Mateo, Ian D. Davis, Anders Bjartell, Alyssa Chan-Cuzydlo, Philip W. Kantoff, Lorelei A. Mucci, Daniel J. George

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsMcMaster UniversityJuravinski Cancer CentreUniversity of British ColumbiaOttawa Hospital
FundersMovember Foundation
KeywordsMedicineProstate cancerAndrogen receptorOncologyAndrogen deprivation therapyInternal medicineCancer

Abstract

fetched live from OpenAlex

5002 Background: Phase III post-hoc analyses show poor prognosis of PSA >0.2 in mHSPC treated by androgen deprivation therapy (ADT) and ARPI, but it remains unclear 1) when PSA cutoffs should be interpreted for prognostic significance, and 2) how PSA cutoffs may differ in real-world multinational data. IRONMAN (International Registry for Men with Advanced Prostate Cancer) prospectively enrolled mHSPC patients from 16 countries and is a unique large data set to investigate these questions. Methods: Patients with mHSPC who received ADT, ARPI +/- docetaxel with PSA data enrolled in the IRONMAN registry were included. 3 PSA strata (>0.2, 0.02 to 0.2, and <0.02ng/ml) were defined at 6- and 12-months (primary analysis) after treatment start. Multivariable Cox proportional hazard regression models were constructed for overall survival (OS) and progression-free survival (PFS, as defined by any of biochemical, radiographic or clinically progression) with adjustment for disease characteristics. A 12-month landmark population was constructed to determine conditional OS and PFS in each PSA stratum. Results: 1288 patients received ADT and ARPI within 90 days of IRONMAN enrolment and met inclusion. Key characteristics were median age 70 years, 69.5% de-novo metastatic, 59% Gleason 8-10, 73% Caucasian, 8.2% Black, 1.5% Asian, 7.3% lung metastases, 3.4% liver metastases, and 53.2% enrolment from centers outside US/Canada. Intensification agents were: abiraterone acetate (576, 44.7%), apalutamide (283, 22.0%), darolutamide (135, 10.5%), or enzalutamide (294, 22.8%), and 122 (8.7%) received docetaxel in addition to ADT-ARPI. PSA at 6, 12 month landmarks respectively were: <0.02 (10%, 21%); 0.02-0.2 (41%, 45%); >0.2 (49%, 34%), with 70% of patients with 6-month PSA >0.2 retained at 12-months. Outcome data in the 12-month landmark cohort are detailed in Table 1, with 3-year OS for the PSA >0.2 stratum significantly worse than the PSA<0.02 stratum (45.3 vs 92.7%, p<0.001), representing a 7-fold mortality risk in the Cox model adjusted hazard ratio (aHR) and 8-fold risk of progression. Conclusions: IRONMAN provides large real-world data validating the poor prognosis of mHSPC with PSA>0.2 after 6-12 months ADT-ARPI treatment and these patients could be targeted for intensification in future trials. Conversely, PSA<0.02 at 6-12 months defines the best prognosis and may be of interest for de-intensification strategies. OS and PFS outcomes by 12-month PSA strata. 12-mo PSA (ng/ml) n 3-yr OS [95%CI] 3-yr PFS [95% CI] OS Cox model mortality risk [95% CI] >0.2 264 45.3% [36.7-55.9] 36.7% [28.6-47.1] aHR 7.34 [3.66-14.71] 0.02-0.2 585 80.0% [74.5-85.9] 72.9% [66.9-79.1] aHR 2.16 [1.06-4.41] <0.02 439 92.7% [87.9-97.8] 93.0% [88.6-97.5] reference

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.432
Teacher spread0.362 · 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 designObservational
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".

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Citations3
Published2025
Admission routes2
Has abstractyes

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