Prevalence of Recurrent Mutations Predisposing to Breast Cancer in Early-Onset Breast Cancer Patients from Poland
Bibliographic record
Abstract
There are twenty recurrent mutations in six breast-cancer-predisposing genes in Poland (BRCA1, BRCA2, CHEK2, PALB2, NBN, and RECQL). The frequencies of the twenty alleles have not been measured in a large series of early-onset breast cancer patients from Poland unselected for family history. We genotyped 2464 women with breast cancer diagnosed below age 41 years for twenty recurrent germline mutations in six genes, including BRCA1, BRCA2 CHEK2, PALB2, NBN, and RECQL. A mutation in one of the six genes was identified in 419 of the 2464 early-onset breast cancer cases (17%), including 22.4% of those cases diagnosed below age 31. The mutation frequency was 18.8% for familial breast cancer cases and 6% for non-familial cases. Among women with breast cancer below age 31, the mutation frequency was 23.6% for familial cases and 17.4% in non-familial cases. The majority of mutations (76.2%) were seen in BRCA1 and BRCA2. In Poland, a panel of twenty recurrent mutations in six genes can identify a genetic basis for a high percentage of early-onset cases and testing is recommended for all women with breast cancer at age 40 or below.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".