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PSMA-targeted imaging with <sup>18</sup>F-DCFPyL-PET/CT in patients (pts) withbiochemically recurrent prostate cancer (PCa): A phase 3 study (CONDOR)—A subanalysis of correct localization rate (CLR) and positive predictive value (PPV) by standard of truth.

2021· article· en· W3134832274 on OpenAlexaff
Frédéric Pouliot, Michael A. Gorin, Steven P. Rowe, Lawrence Saperstein, David Josephson, Peter R. Carroll, Jeffrey Y.C. Wong, Austin R. Pantel, Steve Y. Cho, Kenneth L. Gage, Morand Piert, Andrei Iagaru, Janet H. Pollard, Vivien Wong, Jessica Jensen, Nancy Stambler, Michael J. Morris, Barry A. Siegel

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité Laval
FundersProgenics Pharmaceuticals
KeywordsMedicineNuclear medicineConfidence intervalHistopathologyProstate cancerPopulationClinical endpointRadiation therapyRadiologyCancerClinical trialPathologyInternal medicine

Abstract

fetched live from OpenAlex

5023 Background: PSMA-targeted PET/CT is superior to conventional imaging modalities to localize biochemically recurrent (BCR) PCa after local therapy, particularly in pts with low PSA ( < 2 ng/mL). However, few studies have reported PSMA-targeted PET/CT accuracy compared to a pre-specified rigorous standard of truth (SOT) including histopathology, correlative imaging or treatment response in this population. Here, we report the CLR and PPV of PSMA-targeted 18F-DCFPyLPET/ CT, for each of the pre-defined SOT criteria for the CONDOR prospective phase 3 study. Methods: The study enrolled men with rising PSA after definitive therapy and negative or equivocal standard of care imaging (e.g., CT/MRI, bone scintigraphy, F-18 fluciclovine). A single 9 mCi (333 MBq) ± 20% dose of 18F-DCFPyL was injected, followed by PET/CT 1-2 hours later. Pts with positive 18F-DCFPyL-PET/CT scans based on local interpretation were scheduled for follow up within 60 days to verify suspected lesion(s) using a composite SOT. The primary endpoint was CLR defined as PPV with the requirement of anatomic lesion co-localization between 18F-DCFPyL-PET/CT and the SOT. The SOT consisted of, in descending priority: 1) histopathology, 2) subsequent correlative imaging findings determined by twocentral readers, or 3) post-radiation PSA response. The trial was successful if the lower bound of the 95% confidence interval for CLR exceeded 20% for at least two of three independent, blinded central 18F-DCFPyL-PET/CT reviewers. Results: 208 men (median PSA 0.8 ng/mL) underwent 18F-DCFPyL-PET/CT and the study achieved its primary endpoint: CLR was between 84.8% to 87.0% (lower bound of 95% CI: 77.8%-80.4%) among the three 18F-DCFPyL-PET/CT readers, against the composite SOT. The performance of 18F-DCFPyL-PET/CT by CLR (≥1 lesion co-localized) and PPV (≥1 lesion confirmed) was maintained through all 3 SOT categories. Histopathology (N = 31): 78.6-82.8% and 92.9-93.3% for CLR and PPV, respectively; correlative imaging (N = 100): 86.1-88.6% and 87.0-89.5% for CLR and PPV, respectively; and PSA response (N = 1): 100% for both CLR and PPV. Further analyses of the correlative imaging results showed CLR remained high across the different modalities used a) 18F-fluciclovine-PET/CT (N = 71): (86.8-90.9%); b) MRI (N = 23): (80.0-86.7%); and c) CT (n = 6): (80.0-100%). Conclusions: PSMA-targeted 18F-DCFPyL-PET/CT detected and localized metastatic lesions with high CLR and PPV regardless of which criterion defined CLR that was used, in men with BCR who had negative or equivocal baseline imaging. Clinicaltrials.gov: NCT03739684 Clinical trial information: NCT03739684.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.031
GPT teacher head0.422
Teacher spread0.390 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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