Rare germline mutations in<i>PALB2</i>and breast cancer risk: A population-based study
Bibliographic record
Abstract
Germline mutations in the PALB2 gene are associated with an increased risk of developing breast cancer but little is known about the frequencies of rare variants in PALB2 and the nature of the variants that influence risk. We selected participants recruited to the Women's Environment, Cancer, and Radiation Epidemiology (WECARE) Study and screened lymphocyte DNA from cases with contralateral breast cancer (n = 559) and matched controls with unilateral breast cancer (n = 565) for PALB2 mutations. Five pathogenic PALB2 mutations were identified among the cases (0.9%) versus none among the controls (P = 0.04). The first-degree female relatives of these five carriers demonstrated significantly higher incidence of breast cancer than relatives of noncarrier cases, indicating that pathogenic PALB2 mutations confer an estimated 5.3-fold increase in risk (95% CI: 1.8-13.2). The frequency of rare (<1% MAF) missense mutations was similar in both groups (23 vs. 21). Our findings confirm in a population-based study setting of women with breast cancer the strong risk associated with truncating mutations in PALB2 that has been reported in family studies. Conversely, there is no evidence from this study that rare PALB2 missense mutations strongly influence breast cancer risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".