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Radiographic progression without PSA progression in metastatic hormone-sensitive prostate cancer (mHSPC): A retrospective analysis from the ENZAMET trial (ANZUP 1304).

2024· article· en· W4391303024 on OpenAlexaff
Ian D. Davis, Andrew Martin, Robert Zielinski, Alastair Thomson, Thean Hsiang Tan, Shahneen Sandhu, M. Neil Reaume, David Pook, Francis Parnis, Scott North, Gavin Marx, John McCaffrey, Andrisha Jade Inderjeeth, Lisa G. Horvath, Mark Frydenberg, Simon Chowdhury, Kim N., Martin R. Stockler, Christopher J. Sweeney

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer AgencyUniversity of AlbertaUniversity of British ColumbiaOttawa Hospital
FundersCancer Council AustraliaPfizer
KeywordsMedicineOncologyProstate cancerInternal medicineCancerGynecology

Abstract

fetched live from OpenAlex

151 Background: ENZAMET randomized 1125 participants with mHSPC to compare enzalutamide (ENZA) versus a standard non-steroidal anti-androgen (NSAA) and demonstrated superior progression-free survival and overall survival (PFS and OS) with ENZA. Radiographic progression in the absence of prior/concurrent PSA progression (rProg1st) is an emerging biomarker of poor clinical outcomes. We sought to determine the frequency of rProg1st, and correlate the impact of enzalutamide on transitions between disease states for the ENZAMET cohort. Methods: The ENZAMET dataset was analyzed using a multi-state Cox proportional hazards regression model that partitioned the clinical experience of participants (pts) into 4 states: (1) Evt-Free (event-free), (2) rProg1st (radiologic progression recorded without prior/concurrent evidence of confirmed PSA progression), (3) OtherProg (All Other type of clinical progression events (PSA and treatment switch, excluding death), (4) Death. Results: Radiographic progression was recorded in 388/1125 (34%) pts. Radiographic progression without confirmed prior/concurrent PSA progression per protocol was recorded in 114/1125 (10%) with similar proportions in those assigned ENZA 55/114 (48%) vs NSAA 59/114 (52%). Baseline characteristics of the 114 pts with rProg1st were similar to the other pts in ENZAMET, and were similar in the ENZA and NSAA groups (Table 1). Compared with NSAA, ENZA delayed both rProg1st (HR 0.66, 95%CI: 0.46 to 0.96, p=0.03) and OtherProg (HR 0.37, 95%CI: 0.31 to 0.44, p<0.001). 5-year OS rates were 24% (95%CI: 18-34) in the rProg1st group versus 42% (95%CI: 38-47) in the OtherProg group. Of those who had not progressed (495/1125) with a median follow-up of 68 months, 8% had died of causes other than prostate cancer. As previously reported ENZA prolonged overall survival in the whole trial cohort (N=1125, HR 0·70, 95%CI 0·58 to 0·84, p<0·0001). Conclusions: Participants who had radiographic progression without prior/concurrent PSA progression had worse overall survival whether assigned NSAA or enzalutamide. Enzalutamide reduced the hazards for, and delayed the times to, rProg1st and OtherProg. There were no baseline characteristics that helped identify these pts upfront; we plan molecular biological analyses to help identify this unique group earlier. Clinical trial information: NCT02446405 . [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)0.003
metaresearch head score (Gemma)0.004
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 score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.103
GPT teacher head0.527
Teacher spread0.423 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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