The role of prophylactic prostatectomy as a primary prevention strategy in high-risk germline mutation carriers
Bibliographic record
Abstract
PURPOSE OF REVIEW: Men with high-risk germline mutations are at significantly higher risk of developing and dying from prostate cancer. Current screening and treatment paradigms may lead to missed opportunities for cure. Herein we review the current literature on prevention, screening and treatment of these carriers and explore the potential role of prophylactic prostatectomy in primary prevention of prostate cancer mortality. RECENT FINDINGS: Prostate-specific antigen (PSA)-based screening has demonstrated marginal benefits in prostate cancer (PCa) survival and uncertainty remains on its true benefit among high-risk carriers. Recent results indicate that PCa in BRCA 2 carriers occurs at a higher incidence, younger age and progresses more rapidly compared with noncarriers. An intensified screening protocol of MRI and PSA in young carriers demonstrated how using PSA values alone may be insufficient. Current evidence indicates that high-risk carriers have worse survival outcomes after undergoing radical treatment for screening detected disease when compared with noncarriers. SUMMARY: Prophylactic prostatectomy within the context of a clinical trial is a reasonable primary prevention option for discussion with high-risk carriers, especially BRCA2 carriers during the shared decision-making process. Limitations exist in the current strategies of early PSA screening followed by radical treatment in this group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.004 | 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".