Abstract SS02-03: Cancer risk associated with exogenous hormone use in BRCA mutation carriers
Bibliographic record
Abstract
Abstract Women with a pathogenic vari ant (mutation hereafter) in the BRCA1 or BRCA2 gene face the highest known lifetime risks of developing breast cancer. Notably, incidence rates increase rapidly in early adulthood but remain high even after age 60. Thus, understanding how exogenous (anti)hormones impact these risks is important for the safe clinical management of high-risk women, especially following early surgical menopause. In this session, I will review the current data on the role of tamoxifen chemoprevention, as well as the impact of oral contraceptives, hormone replacement therapy and fertility medication on breast cancer risk. Where possible, I will also discuss associations with ovarian cancer, given that managing BRCA-cancer risks is a balancing act, and present findings by gene mutation. Gaps in the literature and opportunities for further research will also be described. Our goal should be to maximize survival while optimizing health following risk-reducing salpingo-oophorectomy. Citation Format: J. Kotsopoulos. Cancer risk associated with exogenous hormone use in BRCA mutation carriers [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr SS02-03.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".