Guideline of guidelines: <scp>PSMA PET</scp> in staging newly diagnosed intermediate‐risk prostate cancer
Bibliographic record
Abstract
OBJECTIVE: To provide a comprehensive review and analysis of guidelines from various professional and medical organisations regarding the use of prostate-specific membrane antigen (PSMA) positron emission tomography (PET) as a staging scan for men with newly diagnosed intermediate-risk prostate cancer (PCa). MATERIALS AND METHODS: English-language guidelines and recommendations from the following associations and societies were reviewed and critically analysed: European Association of Urology (EAU), American Urological Association (AUA), National Comprehensive Cancer Network (NCCN), National Institute for Health and Care Excellence (NICE), Canadian Urological Association (CUA), American Society for Clinical Oncology (ASCO), Society for Nuclear Medicine and Medical Imaging (SNMMI). RESULTS: There is significant disagreement among guidelines regarding whether PSMA PET is a useful staging tool for men with a new diagnosis of intermediate-risk PCa. There is a stronger consensus that PSMA PET is useful in staging high-risk PCa. CONCLUSION: Whilst there is a growing body of evidence that supports the use of PSMA PET in newly diagnosed PCa, there is significant disagreement regarding its use for men with intermediate-risk disease. Recommendations are generally weak and based on expert opinions. This is an area of considerable ongoing research, and guidelines are likely to change as new evidence emerges.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".