Tamoxifen and contralateral breast cancer in <i>BRCA1</i> and <i>BRCA2</i> carriers: An update
Bibliographic record
Abstract
Women with a mutation in BRCA1 or BRCA2 face a lifetime risk of breast cancer of approximately 80%, and following the first diagnosis the 10-year risk of contralateral breast cancer is approximately 30%. It has been shown that both tamoxifen and oophorectomy prevent contralateral breast cancer, but it is not clear whether there is a benefit in giving tamoxifen to women who have previously undergone an oophorectomy. Furthermore, the relative degree of protection in BRCA1 and BRCA2 carriers has not been well evaluated. We studied 285 women with bilateral breast cancer and a BRCA1 or BRCA2 mutation, and 751 control women with unilateral breast cancer and a BRCA1 or BRCA2 mutation in a matched case-control study. Control women were of similar age and had a similar age of diagnosis of breast cancer and had been followed for as long as the case for a second primary breast cancer. The history of tamoxifen use for treating the first breast cancer was compared between bilateral and unilateral cases. The multivariate odds ratio for contralateral breast cancer associated with tamoxifen use was 0.50 for carriers of BRCA1 mutations (95% CI, 0.30-0.85) and was 0.42 for carriers of BRCA2 mutations (95% CI, 0.17-1.02). The protective effect of tamoxifen was not seen among women who had undergone an oophorectomy (OR = 0.83; 95%CI, 0.24-2.89) but this subgroup was small. In contrast, a strong protective effect of tamoxifen was apparent among women who were premenopausal or who had undergone natural menopause (OR = 0.44; 95% CI, 0.27-0.65).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".