Clinical Management of Prostate Cancer in High-Risk Genetic Mutation Carriers
Bibliographic record
Abstract
BACKGROUND: Prostate cancer is a leading cause of death. Approximately one in eight men who are diagnosed with prostate cancer will die of it. Since there is a large difference in mortality between low- and high-risk prostate cancers, it is critical to identify individuals who are at high-risk for disease progression and death. Germline genetic differences are increasingly recognized as contributing to risk of lethal prostate cancer. The objective of this paper is to review prostate cancer management options for men with high-risk germline mutations. METHODS: We performed a review of the literature to identify articles regarding management of prostate cancer in individuals with high-risk germline genetic mutations. RESULTS: We identified numerous publications regarding the management of prostate cancer among high-risk germline carriers, but the overall quality of the evidence is low. CONCLUSIONS: We performed a review of the literature and compiled clinical considerations for the management of individuals with high-risk germline mutations when they develop prostate cancer. The quality of the evidence is low, and there is an immediate need for further research and the development of consensus guidelines to guide clinical practice for these individuals.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| 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".