Updates on controversies surrounding the staging and management of newly diagnosed localized prostate cancer using prostate-specific membrane antigen (PSMA) positron emission tomography
Bibliographic record
Abstract
There are controversies surrounding indications for prostate-specific membrane antigen (PSMA) positron-emission tomography (PET) and the subsequent management of localized disease. Conventional imaging is not a necessary prerequisite to PSMA PET, which serves as an equally effective, if not more effective frontline imaging tool. However, research conducted in different countries has shown conflicting results regarding its cost-effectiveness. Following accurate staging using PSMA PET, subsequent management is discussed by our expert team in this review, which incorporates the latest updates: (1) Brief global overview: the sustainability and cost-effectiveness of routine PET, as well as the treatment sequences of neoadjuvant vs. adjuvant androgen deprivation therapy (ADT) with radiotherapy, require further research. (2) Gonadotropin-releasing hormone antagonists demonstrate better response rates, lower recurrence rates, and fewer complications compared to agonists. (3) The unfavorable intermediate-risk group may undergo prostatectomy or radiotherapy combined with 4–6 months of ADT. Radiotherapy alone may be considered for patients with co-morbidities, Gleason score 7 (3 + 4), and positive biopsy cores < 50%, provided an escalated radiation dose is applied. (4) Three Prostate Advances in Comparative Evidence (PACE) studies demonstrated that stereotactic radiotherapy, greatly relying on PSMA PET, is as effective as surgery or conventional radiotherapy. (5) Findings from clinical trials indicate that pelvic nodal radiotherapy coverage provides a survival benefit. (6) A brachytherapy boost provides better outcomes compared to external beam boost, eliminating the need for ADT in intermediate-risk cancers and reducing ADT duration to 6 months in high-risk cancers. Even short-term use (4–6 months) of gonadotropin releasing hormone agonists can lead to cardiac morbidity. In summary, localized prostate cancer, as identified through the relatively new PSMA PET, can be managed in various ways. This review highlights significant updates on controversial issues relevant to both cancer patients and researchers.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".