Breastfeeding and the risk of epithelial ovarian cancer among women with a BRCA1 or BRCA2 mutation
Bibliographic record
Abstract
OBJECTIVE: BRCA mutation carriers face a high lifetime risk of developing ovarian cancer. The strong inverse association between breastfeeding and the risk of ovarian cancer is established in the general population but is less well studied among women with a germline BRCA1 or BRCA2 mutation. METHOD: Thus, we conducted a matched case-control analysis to evaluate the association between breastfeeding history and the risk of developing ovarian cancer. After matching for year of birth, country of residence, BRCA gene and personal history of breast cancer, a total of 1650 cases and 2702 controls were included in the analysis. Conditional logistic regression was used to estimate the odds ratio (OR) and 95% confidence intervals (CI) associated with various breastfeeding exposures. RESULTS: A history of ever-breastfeeding was associated with a 23% reduction in risk (OR = 0.77; 95%CI 0.66-0.90; P = 0.001). The protective effect increased with breastfeeding from one month to seven months after which the association was relatively stable. Compared to women who never breastfed, breastfeeding for seven or more months was associated with a 32% reduction in risk (OR = 0.68; 95%CI 0.57-0.81; P < 0.0001) and did not vary by BRCA gene or age at diagnosis. The combination of breastfeeding and oral contraceptive use was strongly protective (0.47; 95%CI 0.37-0.58; P < 0.0001). CONCLUSIONS: These findings support a protective effect of breastfeeding for at least seven months among women with a BRCA1 or BRCA2 mutation, that is independent of oral contraceptive use.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".