Influence of molecular imaging on patient selection for treatment intensification prior to salvage radiation therapy for prostate cancer: a post hoc analysis of the PROPS trial
Bibliographic record
Abstract
BACKGROUND: The impact of molecular imaging (MI) on patient management after biochemical recurrence (BCR) following radical prostatectomy has been described in many studies. However, it is not known if MI-induced management changes are appropriate. This study aimed to determine if androgen deprivation therapy (ADT) management plan is improved by MI in patients who are candidates for salvage radiation therapy. METHODS: Data were analyzed from the multicenter prospective PROPS trial evaluating PSMA/Choline PET in patients being considered for salvage radiotherapy (sRT) with BCR after prostatectomy. We compared the pre- and post-MI ADT management plans for each patient and cancer outcomes as predicted by the MSKCC nomogram. A higher percentage of predicted BCR associated with ADT treatment intensification after MI was considered as an improvement in a patient's management. RESULTS: Seventy-three patients with a median PSA of 0.38 ng/mL were included. In bivariate analysis, a positive finding on MI (local or metastatic) was associated with decision to use ADT with an odds ratio of 3.67 (95% CI, 1.25 to 10.71; p = 0.02). No factor included in the nomogram was associated with decision to use ADT. Also, MI improved selection of patients to receive ADT based on predicted BCR after sRT : the predicted nomogram 5-year biochemical-free survivals were 52.5% and 43.3%, (mean difference, 9.2%; 95% CI 0.8 to 17.6; p = 0.03) for sRT alone and ADT±sRT subgroups, while there was no statistically significant difference between subgroups before MI. CONCLUSIONS: PSMA and/or Choline PET/CT before sRT can potentially improve patient ADT management by directing clinicians towards more appropriate intensification.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".