Endometriosis in Carriers of a Pathogenic Variant in BRCA1 or BRCA2: A Descriptive Analysis of a Large Multicentral BRCA Carrier Cohort
Bibliographic record
Abstract
Background: Endometriosis affects an estimated 10% of reproductive-aged women and is associated with increased ovarian cancer risk. While BRCA1/2 mutations are established risk factors for ovarian cancer, their association with endometriosis remains unclear. This study aimed to characterize the prevalence and clinical features of endometriosis within a large cohort of BRCA mutation carriers. Methods: A descriptive analysis was conducted using data from a multi-center longitudinal cohort of women with pathogenic BRCA variants. Reproductive history and related factors were collected through self-reported questionnaires and compared. Results: Among 16,950 BRCA carriers, the prevalence of endometriosis was 2.4%. Compared to BRCA carriers without endometriosis, those with endometriosis were more likely to carry a BRCA2 mutation, have post-secondary education, and experience earlier menarche. BRCA carriers with endometriosis had a lower ovarian cancer prevalence than those without (10% vs. 15%, p < 0.001). Conclusions: This is the first study of this scale to report the prevalence of endometriosis among BRCA mutation carriers, which was lower than previously reported in the general population. The association between endometriosis and ovarian cancer does not appear to be generalizable to this population. Further prospective studies are warranted to clarify this association among BRCA mutation carriers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".