Abstract A65: Does the lifetime number of ovulatory cycles predict the risk of breast cancer in BRCA1 and BRCA2 mutation carriers?
Bibliographic record
Abstract
Abstract Background: In the general population, various reproductive factors are believed to influence breast cancer risk via their effects on the number of ovulatory cycles and subsequently on cumulative endogenous hormonal exposure. It is not clear to what extent this is true for women with a BRCA1 or BRCA2 mutation. We undertook a case-control study to evaluate the effect of the cumulative number of ovulatory cycles and each of the contributing components) on the risk of developing breast cancer among BRCA mutation carriers. Methods: A matched case-control study was conducted in 2,632 pairs of women with a deleterious mutation in either BRCA1 (n = 1,915 pairs) or BRCA2 (n = 717 pairs). Women diagnosed with breast cancer were matched to unaffected control subjects by year of birth, mutation status, and country of residence. Information about reproductive factors, hormonal exposures and menopausal status was collected from a routinely administered questionnaire and was used to estimate the cumulative number of ovulatory cycles. Conditional logistic regression was used to estimate the association between various exposures and the risk of breast cancer. Results: The risk of breast cancer decreased with the number of ovulatory cycles (ρ = −0.69;P = 0.03). Age at menarche and breastfeeding were inversely related with risk of breast cancer among BRCA1 (P-trend < 0.0001) but not BRCA2 (P-trend ≥ 0.36) mutation carriers. Parity, oral contraceptive use, and the number of ovulatory cycles, were not associated with risk (P-trend ≥ 0.21). The reduction in breast cancer risk associated with surgical menopause (OR = 0.49; 95%CI 0.37–0.64; P-trend < 0.001) was stronger than that conferred by natural menopause (OR = 0.78; 95%CI 0.58–1.06; P-trend = 0.11). There was a significant reduction in breast cancer risk among women who had an oophorectomy after natural menopause (OR = 0.13; 95%CI 0.02–0.54; P = 0.006). Conclusions: These data challenge the prevailing hypothesis that the risk of breast cancer in a woman can be predicted by her lifetime number of ovulatory cycles in women with a BRCA1 or BRCA2 mutation. Reproductive risk factors, such as age at menarche and breastfeeding are important in BRCA1, but not BRCA2 carriers. The observation that a postmenopausal oophorectomy protects against breast cancer is consistent with either a direct carcinogenic activity of ovarian androgens or through aromatization of androgen to estrogen. It is important to distinguish between these two possibilities because of the different implications for chemoprevention. Citation Information: Cancer Prev Res 2011;4(10 Suppl):A65.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".