Diagnostic performance of <sup>18</sup>F-DCFPyL in the OSPREY Trial: A prospective phase 2/3 multicenter study of <sup>18</sup>F-DCFPyL PET/CT imaging in patients (Pts) with known or suspected metastatic prostate cancer (mPC).
Bibliographic record
Abstract
5012 Background: Accurate detection of prostate cancer is imperative to patient management, yet standard imaging methods perform poorly in accurately detecting mPC. 18F-DCFPyL is a novel PET imaging agent that selectively binds to prostate-specific membrane antigen, a recognized target for prostate cancer. OSPREY was a prospective, multicenter study in pts with either newly diagnosed high-risk prostate cancer (cohort A), or known or suspected mPC (cohort B). Here we focus on Cohort B. Methods: 117 men planned for biopsy of recurrent or mPC received 18F-DCFPyL. Pts underwent image-guided biopsy. Sensitivity, positive predictive value (PPV), and safety of 18F-DCFPyL PET/CT were the key endpoints for Cohort B. 18F-DCFPyL PET/CT scans were evaluated by three independent, blinded central readers; and results were compared to histopathology as the truth standard. Results: The sensitivity and PPV of 18F-DCFPyL PET/CT as compared to histopathology ranged from 92.9-98.6% (lower bound of 95% CI: 84.0-91.6%) and 81.2-87.8%, respectively. Diagnostic performance by anatomic location showed high sensitivity and high PPV in all sites of disease (Table). Only two (1.7%) cohort B pts experienced ≥1 drug-related AE (dysgeusia and generalized rash), both were mild (Grade 1) in severity. Conclusions: 18F-DCFPyL PET/CT was well tolerated and demonstrated high sensitivity and PPV in accurately detecting nodal, bone, and visceral/soft tissue metastases. A positive 18F-DCFPyL PET/CT scan is highly likely to represent pathologically proven distant disease, demonstrating the potential of 18F-DCFPyL as a PET imaging agent to favorably influence treatment planning. Clinical trial information: NCT02981368. [Table: see text]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".