PSMA PET/CT guided intensification of therapy in patients at risk of advanced prostate cancer (PATRON): a pragmatic phase III randomized controlled trial
Bibliographic record
Abstract
Abstract Background Positron emission tomography targeting the prostate specific membrane antigen (PSMA PET/CT) has demonstrated unparalleled performance as a staging examination for prostate cancer resulting in substantial changes in management. However, the impact of altered management on patient outcomes is largely unknown. This study aims to assess the impact of intensified radiotherapy or surgery guided by PSMA PET/CT in patients at risk of advanced prostate cancer. Methods This pan-Canadian phase III randomized controlled trial will enroll 776 men with either untreated high risk prostate cancer (CAPRA score 6–10 or stage cN1) or biochemically recurrent prostate cancer post radical prostatectomy (PSA > 0.1 ng/mL). Patients will be randomized 1:1 to either receive conventional imaging or conventional plus PSMA PET imaging, with intensification of radiotherapy or surgery to newly identified disease sites. The primary endpoint is failure free survival at 5 years. Secondary endpoints include rates of adverse events, time to next-line therapy, as well as impact on health-related quality of life and cost effectiveness as measured by incremental cost per Quality Adjusted Life Years gained. Discussion This study will help create level 1 evidence needed to demonstrate whether or not intensification of radiotherapy or surgery based on PSMA PET findings improves outcomes of patients at risk of advanced prostate cancer in a manner that is cost-effective. Trial registration This trial was prospectively registered in ClinicalTrials.gov as NCT04557501 on September 21, 2020.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".