Beyond the pill: contraception and the prevention of hereditary ovarian cancer
Bibliographic record
Abstract
BRCA1 and BRCA2 mutation carriers face an elevated lifetime risk of developing ovarian cancer. Oral contraceptives have been shown to significantly decrease the risk of ovarian cancer by approximately 50% in this high-risk population. Changes in contraceptive formulations and patterns of use over time have introduced lower hormonal dosages, different steroid types and non-oral routes of administration. Specifically, there has been a considerable shift in patterns of contraceptive use and the increase in the uptake of non-oral, long-acting, reversible contraception (e.g., intrauterine devices, implants, injections) has corresponded to a decline in oral contraceptive pill use. Whether or not these other methods confer a protective effect against ovarian cancer in the general population is not clear. To our knowledge, there have been no such studies conducted among BRCA mutation carriers. Furthermore, the impact of these changes on the risk of developing ovarian cancer is not known. In this article, we will review the existing epidemiologic evidence regarding the role of contraceptives and the risk of ovarian cancer with a focus on women with a BRCA1 or BRCA2 mutation. We will discuss recent findings and gaps in the knowledge while extrapolating from studies conducted among women from the noncarrier population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".