Genetic predisposition to male breast cancer in Poland
Bibliographic record
Abstract
BACKGROUND: Breast cancer in men accounts for fewer than 1 % of all breast cancer cases diagnosed in men and women. Genes which predispose to male breast cancer include BRCA1 and BRCA2. The role of other genes is less clear. In Poland, 20 founder mutations in BRCA1, BRCA2, CHEK2, PALB2, NBN, RECQL are responsible for the majority of hereditary breast cancer cases in women, but the utility this genes panel has not been tested in men. METHODS: We estimated the prevalence of 20 alleles in six genes (BRCA1, BRCA2, CHEK2, PALB2, NBN, RECQL) in 165 Polish male breast cancer patients. We compared the frequency of selected variants in male breast cancer cases and controls. RESULTS: One of the 20 mutations was seen in 22 of 165 cases (13.3%). Only one BRCA1 mutation and two BRCA2 mutations were found. We observed statistically significant associations for PALB2 and CHEK2 truncating mutations. A PALB2 mutation was detected in four cases (OR = 11.66; p < 0.001). A CHEK2 truncating mutation was detected in five cases (OR = 2.93;p = 0.02). CONCLUSION: In conclusion, we recommend that a molecular test for BRCA1, BRCA2, PALB2 and CHEK2 recurrent mutations should be offered to male breast cancer patients in Poland.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".