An inverse association between ovarian cysts and breast cancer in the breast cancer family registry
Bibliographic record
Abstract
Ovarian cysts of several types are common in women of reproductive age. Their etiology is not well understood but is likely related to perturbations in the hypothalamic-pituitary-gonadal axis. The relationship of ovarian cysts to breast cancer risk is not known, although a negative association with polycystic ovarian syndrome has been reported. Incident, invasive female breast cancer cases, population-based controls and unaffected sisters of cases were studied from 3 countries participating in the Breast Cancer Family Registry: Melbourne and Sydney, Australia; the San Francisco Bay Area, USA; and Ontario, Canada. Using the same questionnaire, information was collected on self-reported history of ovarian cysts and other risk factors. Analyses were based on 3,049 cases, 2,344 population controls and 1,934 sister controls from all sites combined. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using both unconditional and conditional logistic regression using an offset term to account for sampling fractions at 2 of the sites. A significantly reduced risk of breast cancer was observed for women reporting a history of ovarian cysts (OR = 0.70, 95% CI 0.59-0.82, among all cases and all controls). This risk estimate was similar regardless of control group used, within all 3 sites and in both premenopausal and postmenopausal women (ORs ranging from 0.68-0.75, all 95% CI excluded 1.00). A self-reported history of ovarian cysts was strongly and consistently associated with a reduced risk of breast cancer. Further study of ovarian cysts may increase our understanding of hormonal and other mechanisms of breast cancer etiology.
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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 | 0.002 | 0.012 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".