Oligometastasis in Prostate Cancer: Can We Learn from Those “Excluded” from a Phase 2 Trial?
Bibliographic record
Abstract
We conducted and previously published a phase 2 trial of metastasis-directed therapy (MDT) in men with recurrence of prostate cancer at a low prostate-specific antigen level following radical prostatectomy and postoperative radiotherapy. All patients had negative conventional imaging and underwent prostate-specific membrane antigen (PSMA) positron emission tomography (PET). Patients without visible disease (n = 16) or with metastatic disease not amenable to MDT (n = 19) were excluded from the interventional study. The remaining patients with disease visible on PSMA-PET received MDT (n = 37). We analyzed all three groups to identify distinct phenotypes in the era of molecular imaging–based characterization of recurrent disease. Median follow up was 37 mo (interquartile range 27.5–43.0). There was no significant difference in time to the development of metastasis on conventional imaging among the groups; however, castrate-resistant prostate cancer-free survival was significantly shorter for patients with PSMA-avid disease not amenable to MDT (p = 0.047). Our findings suggest that PSMA-PET findings can help in discriminating diverging clinical phenotypes among men with disease recurrence and negative conventional imaging after local therapies with curative intent. There is a pressing need for better characterization of this rapidly growing population of patients with recurrent disease defined by PSMA-PET to derive robust selection criteria and outcome definitions for ongoing and future studies. In men with prostate cancer with rising PSA levels following surgery and radiation, a newer type of scan called PSMA-PET (prostate-specific membrane antigen positron emission tomography) can be used to characterize and differentiate the patterns of recurrence, and inform future cancer outcomes.
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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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".