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Record W3131780647 · doi:10.2967/jnumed.120.259069

Prospective, Single-Arm Trial Evaluating Changes in Uptake Patterns on Prostate-Specific Membrane Antigen–Targeted <sup>18</sup>F-DCFPyL PET/CT in Patients with Castration-Resistant Prostate Cancer Starting Abiraterone or Enzalutamide

2021· article· en· W3131780647 on OpenAlexaff
Katherine Zukotynski, Urban Emmenegger, Sebastién J. Hotte, Anil Kapoor, Wei Fu, Amanda L. Blackford, John F. Valliant, François Bénard, Chun K. Kim, Mark C. Markowski, Mario A. Eisenberger, Emmanuel S. Antonarakis, Kenneth J. Pienta, Michael A. Gorin, Matthew Lubanovic, Martin G. Pomper, Steve Y. Cho, Steven P. Rowe

Bibliographic record

VenueJournal of Nuclear Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsSunnybrook Health Science CentreMcMaster UniversityUniversity of British Columbia
Fundersnot available
KeywordsMedicineProstate cancerEnzalutamideGlutamate carboxypeptidase IINuclear medicineUrologyProspective cohort studyProstate-specific antigenClinical trialInternal medicineOncologyCancerAndrogen receptor

Abstract

fetched live from OpenAlex

PET with small molecules targeting prostate-specific membrane antigen (PSMA) is being adopted as a clinical standard for prostate cancer imaging. In this study, we evaluated changes in uptake on PSMA-targeted PET in men starting abiraterone or enzalutamide. Methods: This prospective, single-arm, 2-center, exploratory clinical trial enrolled men with metastatic castration-resistant prostate cancer initiating abiraterone or enzalutamide. Each patient was imaged with 18F-DCFPyL at baseline and within 2–4 mo after starting therapy. Patients were followed for up to 48 mo from enrollment. A central review evaluated baseline and follow-up PET scans, recording change in SUVmax at all disease sites and classifying the pattern of change. Two parameters were derived: the δ-percent SUVmax (DPSM) of all lesions and the δ-absolute SUVmax (DASM) of all lesions. Kaplan–Meier curves were used to estimate time to therapy change (TTTC) and overall survival (OS). Results: Sixteen evaluable patients were accrued to the study. Median TTTC was 9.6 mo (95% CI, 6.9–14.2), and median OS was 28.6 mo (95% CI, 18.3–not available [NA]). Patients with a mixed-but-predominantly-increased pattern of radiotracer uptake had a shorter TTTC and OS. Men with a low DPSM had a median TTTC of 12.2 mo (95% CI, 11.3–NA) and a median OS of 37.2 mo (95% CI, 28.9–NA), whereas those with a high DPSM had a median TTTC of 6.5 mo (95% CI, 4.6–NA, P = 0.0001) and a median OS of 17.8 mo (95% CI, 13.9–NA, P = 0.02). Men with a low DASM had a median TTTC of 12.2 mo (95% CI, 11.3–NA) and a median OS of NA (95% CI, 37.2 mo–NA), whereas those with a high DASM had a median TTTC of 6.9 mo (95% CI, 6.1–NA, P = 0.003) and a median OS of 17.8 mo (95% CI, 13.9–NA, P = 0.002). Conclusion: Findings on PSMA-targeted PET 2–4 mo after initiation of abiraterone or enzalutamide are associated with TTTC and OS. Development of new lesions or increasing intensity of radiotracer uptake at sites of baseline disease are poor prognostic findings suggesting shorter TTTC and OS.

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)0.002
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 score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.338
Teacher spread0.267 · 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

Citations52
Published2021
Admission routes1
Has abstractyes

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