Prostate cancer screening characteristics in men with BRCA1/2 mutations attending a high-risk prevention clinic
Bibliographic record
Abstract
INTRODUCTION: The prostate-specific antigen (PSA) era and resultant early detection of prostate cancer has presented clinicians with the challenge of distinguishing indolent from aggressive tumours. Mutations in the BRCA1/2 genes have been associated with prostate cancer risk and prognosis. We describe the prostate cancer screening characteristics of BRCA1/2 mutation carriers, who may be classified as genetically-defined high risk, as compared to another high-risk cohort of men with a family history of prostate cancer to evaluate the utility of a targeted screening approach for these men. METHODS: We reviewed patient demographics, clinical screening characteristics, pathological features, and treatment outcomes between a group of BRCA1 or BRCA2 mutation carriers and age-matched men with a family history of prostate cancer followed at our institutional Prostate Cancer Prevention Clinic from 1995 to 2012. RESULTS: Screening characteristics were similar between the mutation carriers (n = 53) and the family history group (n = 53). Some cancers would be missed in both groups by using a PSA cut-off of >4 ug/L. While cancer detection was higher in the family history group (21% vs. 15%), the mutation carrier group was more likely to have intermediate- or high-risk disease (88% vs. 36%). BRCA2 mutation carriers were more likely to have aggressive disease, biological recurrence, and distant metastasis. CONCLUSIONS: In our cohort, regular screening appears justified for detecting prostate cancer in BRCA1 and BRCA2 carriers and other high-risk populations. Lowering PSA cut-offs and defining monitoring of PSA velocity as part of the screening protocol may be useful. BRCA2 is associated with more aggressive disease, while the outcome for BRCA1 mutation carriers requires further study. Large multinational studies will be important to define screening techniques for this unique high-risk population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".