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Prostate-specific membrane antigen ligand positron emission tomography (PSMA-PET) disease extent and overall survival (OS) in patients (pts) with high-risk nonmetastatic castration-resistant prostate cancer (nmCRPC): An international multicenter retrospective study.

2023· article· en· W4379283675 on OpenAlexaff
Boris Hadaschik, Matthias Eiber, Manuel Weber, Aravind Ravi Kumar, Jérémie Calais, Johannes Czernin, Harun Ilhan, Fred Saad, Alexander Kretschmer, Sabine Brookman‐May, Suneel Mundle, Eric J. Small, Matthew R. Smith, Paola M. Perez Rivera, Thomas A. Hope, Ken Herrmann, Michael S. Hofman, Wolfgang P. Fendler

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineProstate cancerPositron emission tomographyProportional hazards modelInternal medicineNuclear medicineOncologyCancerRadiology

Abstract

fetched live from OpenAlex

5010 Background: PSMA-PET was positive for distant metastases (39% distant nodes, 24% bone, 6% visceral organ) in >50% of nmCRPC pts who were nonmetastatic by conventional imaging (Fendler et al. CCR 2019). However, the prognostic impact of PSMA-PET disease extent and its association with oncologic outcomes is unknown. We assessed the prognostic utility of PSMA-PET disease extent in nmCRPC pts defined by conventional imaging for OS and new metastases-free survival (nMFS). Methods: 200 pts (6 centers) with nmCRPC by conventional imaging and prostate-specific antigen doubling time (PSADT) ≤10 mo and/or ISUP grade group ≥4 underwent PSMA-PET. Clinical course and treatment management after PSMA-PET imaging were recorded for 4-9 y. Pt characteristics and PSMA-PET disease extent were analyzed retrospectively. OS and PSMA-PET nMFS (time from primary PSMA-PET to appearance of new distant metastases by PSMA-PET or death) were analyzed for pt subgroups based on disease extent by univariate Cox regression. Results: Median OS was 74 mo, similar to the SPARTAN study of nmCRPC pts (74 mo; Smith et al. Eur Urol 2021). Polymetastatic disease (≥5 distant lesions by PSMA-PET) was associated with shorter OS (median 61 mo vs not reached [NR]) and shorter PSMA-PET nMFS (HR 1.8, 95% CI 1.1-2.9; median 38 vs 60 mo; p=0.021). Any metastatic disease by PSMA-PET and whole-body PSMA tumor volume were not prognostic for OS and PSMA-PET nMFS (all p>0.05). Initial pN1 status was associated with shorter OS (median 55 mo vs NR), but not with PSMA-PET nMFS (p>0.05). Baseline age, baseline Gleason grade ≥8, prior radiotherapy (RT), and PSA and PSADT at time of primary PSMA-PET were not associated with outcomes (all p>0.05). Management after PSMA-PET imaging was mostly local/targeted therapy in pts with no visible/locoregional disease (40/30%) and androgen receptor signaling inhibition therapy in pts with nodal/bone distant metastases (35/43%). Conclusions: Polymetastases (>5) by PSMA-PET and initial pN1 status were significantly associated with worse OS. PSMA-PET disease extent provides a potential novel additional risk stratification for pts with nmCRPC without distant metastasis based on conventional imaging. Further validation is needed to prove its independent prognostic value. Clinical trial information: NCT01946204 . [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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.046
GPT teacher head0.406
Teacher spread0.359 · 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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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