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Blood biomarkers and association with clinical outcomes in metastatic castration-resistant prostate cancer (mCRPC): prespecified longitudinal analysis from the ACIS study of apalutamide (APA) or placebo combined with abiraterone acetate plus prednisone (AAP).

2022· article· en· W4213325738 on OpenAlexaff
Eleni Efstathiou, Gerhardt Attard, Justin Lucas, Shibu Thomas, Michael Gormley, Clemente Aguilar-Bonavides, Thomas W. Flaig, Fábio Franke, Oscar B. Goodman, Stéphane Oudard, Christopher Pieczonka, Susan Li, Shiva Dibaj, Sabine Brookman‐May, Kesav Yeruva, Sharon McCarthy, Thomas Steuber, Hiroyoshi Suzuki, Dana E. Rathkopf, Fred Saad

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersJanssen Research and Development
KeywordsMedicineAbiraterone acetateProstate cancerOncologyEnzalutamideInternal medicineAndrogen receptorProportional hazards modelBiomarkerUnivariate analysisAbirateronePopulationLog-rank testCancerMultivariate analysisAndrogen deprivation therapyBiology

Abstract

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142 Background: In ACIS, APA + AAP improved radiographic progression-free survival in mCRPC vs AAP; difference in overall survival (OS) was not statistically significant. We report a prespecified analysis of androgen receptor (AR) or non-AR genomic/transcriptional aberrations, known to be associated with poor prognosis, and their associations with OS in patients (pts) with mCRPC. Methods: Circulating tumor (ct)DNA and aberrations in 17 PC-relevant genes were assessed using next-generation sequencing at baseline (BL; n = 197) and at end of study treatment (EOST; n = 140) (biomarker population). ctDNA was summarized qualitatively; genomic aberrations were normalized by ctDNA detection. AR splice variant version 7 (ARv7) was detected by quantitative RT-PCR. Cox proportional hazards model assessed association of OS with biomarkers in univariate/multivariate analyses overall and in pts receiving subsequent treatment (tx). Results: BL characteristics of biomarker and total study populations were similar. From BL to EOST: ctDNA detection did not differ (123/196 [63%] to 92/140 [66%], p=0.6); significant increases occurred in ARv7, AR mutations, and any AR aberration (Table). Prevalence of aberrations in PI3K and homologous recombination repair (HRR) pathways did not change from BL to EOST (40/123 [33%] to 34/92 [37%], p=0.5 and 18/123 [15%] to 14/92 [15%], p>0.9, respectively). Worse OS was associated with ctDNA detection or HRR pathway inactivation at BL (HR, 2.5 or 2.2; all p < 0.001) or presence of ctDNA, ARv7, AR amplification or inactivation of TP53, RB1, or RB1/TP35 pathway at EOST (2.2, p < 0.001; 2.1, p < 0.001; 2.6, p < 0.001; 1.5, p < 0.05; 1.7, p < 0.05; 2.1, p < 0.001, respectively) in univariate analyses. EOST ARv7, AR amplification, and inactivation of RB1, TP53, or RB1/TP53 pathway was associated with worse OS in pts receiving subsequent tx. Detection of ctDNA and RB1 inactivation at BL and RB1/TP53 pathway inactivation at EOST was strongly associated with worse OS (2.1, 3.3, 2.9, respectively, all p < 0.01) in multivariate analyses. Conclusions: In ACIS, AAP or APA + AAP tx was associated with increased AR mutations and ARv7 expression. Detection of ctDNA and select AR/non-AR aberrations may predict poor survival in mCRPC. These markers may be used to improve tx selection following confirmation of their predictive value. Clinical trial information: NCT02257736. [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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.147
GPT teacher head0.460
Teacher spread0.313 · 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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Citations1
Published2022
Admission routes1
Has abstractyes

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