The Impact of Pregnancy on Breast Cancer Survival in Women who Carry a BRCA1 or BRCA2 Mutation
Bibliographic record
Abstract
Background: Young BRCA mutation carries with a history of breast cancer often inquire about the impact of pregnancy upon their risks of cancer recurrence and survival. \nMethods: We identified 128 BRCA carriers who were diagnosed with breast cancer while pregnant or who became pregnant after breast cancer diagnosis. Women were matched to 269 controls. Women were followed from the date of breast cancer diagnosis until the date of death. The Kaplan-Meier method and a left-truncated Cox proportional hazard model were used to estimate 15-year survival rates. \nResults: The adjusted hazard ratio associated with 15-year survival for women diagnosed with breast cancer who were or became pregnant after breast cancer diagnosis, compared to women who did not become pregnant was 0.76 (95% CI 0.31 to 1.91 p = 0.56). \nConclusion: Pregnancy concurrent with or after a diagnosis of breast cancer does not appear to adversely affect survival among BRCA1/2 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".