Oligometastatic Disease Detection with 68Ga-PSMA-11 PET/CT in Hormone-Sensitive Prostate Cancer Patients (HSPC) with Biochemical Recurrence after Radical Prostatectomy: Predictive Factors and Clinical Impact
Bibliographic record
Abstract
Metastasis-directed therapy (MDT) in oligometastatic prostate cancer has the potential of delaying the start of androgen deprivation therapy (ADT) and disease progression. We aimed to analyze the efficacy of PSMA-PET/CT in detecting oligometastatic disease (OMD), to look for predictive factors of OMD, and to evaluate the impact of PSMA-PET/CT findings on clinical management. We retrospectively analyzed a homogeneous population of 196 hormone-sensitive prostate cancer patients (HSPC), considered potential candidates for MDT, with a PSMA-PET/CT performed at biochemical recurrence (BCR) after radical prostatectomy (RP). Multivariable logistic regression analysis was performed based on several clinico-pathological factors. Changes in clinical management before and after PSMA-PET/CT were analyzed. The OMD detection rate was 44% for a total positivity rate of 60%. PSMA-PET/CT positivity was independently related to PSA (OR (95% CI), p) (1.7 (1.3–2.3), p < 0.0001) and PSAdt (0.4 (0.2–0.8), p = 0.013), and OMD detection was independently related to PSA (1.6 (1.2–2.2), p = 0.001) and no previous salvage therapy (0.3 (0.1–0.9), p = 0.038). A treatment change was observed in 58% of patients, mostly to perform MDT after OMD detection (60% of changes). This study showed that PSMA-PET/CT is an excellent imaging technique to detect OMD early in HSPC patients with BCR after RP, changing therapeutic management mostly into MDT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".