A Comparison of Bilateral Breast Cancers in <i>BRCA</i> Carriers
Bibliographic record
Abstract
BACKGROUND: Women with breast cancer and a BRCA mutation have a high risk of developing a contralateral breast cancer. It is generally believed that the two cancers represent independent events. However, the extent of concordance between the first and second tumors with respect to hormone receptor expression and other pathologic features is unknown. PURPOSE: To determine the degree of concordance of estrogen receptor (ER) status, tumor grade, and histology in tumors from women with bilateral breast cancer and a BRCA mutation. SUBJECTS AND METHODS: Women with a history of bilateral invasive breast cancers were selected from an international registry of women with BRCA1 or BRCA2 mutations. Medical records were reviewed to document the characteristics of each cancer and the treatments received. RESULTS: Data were available for 286 women with bilateral breast cancer and a BRCA mutation (211 BRCA1; 75 BRCA2). The mean interval between first and second tumor was 5.1 years. The two tumors were concordant more often than expected for ER status (P < 0.0001) and for grade (P < 0.0001), but not for histology (P = 0.55). The ER status of the first tumor was highly predictive of the ER status of the second tumor (odds ratio, 8.7; 95% confidence interval, 3.5-21.5; P < 0.0001). Neither age, menopausal status, oophorectomy nor tamoxifen use was predictive of the ER status of the second tumor. CONCLUSIONS: There is strong concordance in ER status and tumor grade between independent primary breast tumors in women with a BRCA mutation. The excess concordance may be due to common risk factors, genetic variation, or the existence of a preneoplastic lesion that is common to both tumors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".