Cancer Risks for Male Carriers of Germline Mutations in <i>BRCA1</i> or <i>BRCA2</i>: A Review of the Literature
Bibliographic record
Abstract
Major risks conferred by BRCA1 and BRCA2 in women are for cancers of the breast, ovary, fallopian tube, and peritoneum. Male carriers of mutations in BRCA1 or BRCA2 are also susceptible to cancer; however, their risks remain poorly understood and their optimal clinical management has not yet been defined. This article reviews studies that estimate risk associated with mutations in BRCA1 or BRCA2, with a focus on the cancer sites most relevant to men. Male BRCA1 mutation carriers are at increased risk of cancers of the prostate and breast. Evidence supporting increased susceptibility to colon cancer is limited. In contrast to women, who have a greater lifetime risk of cancer with mutations of the BRCA1 gene, BRCA2 is the more important gene for men. The spectrum of cancers is wide for BRCA2 and some studies report that the overall cancer risk for male BRCA2 carriers exceeds the risk for female carriers. In particular, the relative risk to male BRCA2 mutation carriers is high before age 65 years, largely attributable to breast, prostate, and pancreatic cancers. BRCA2 mutation carriers are also at risk of stomach cancer and melanoma (of the skin and eye). Additional research into risks to male BRCA1 or BRCA2 mutation carriers is necessary, specifically to determine the magnitude of excess cancer risk among BRCA2 carriers and to increase our understanding of the basis for the observed site-specificity in cancer development.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.002 | 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".