Abstract B127: Family history of breast cancer and risk of contralateral breast cancer
Bibliographic record
Abstract
Abstract Purpose: Family history of breast cancer increases a woman's risk of developing a first primary breast cancer. A meta-analysis of case-control studies of first primary breast cancer reported an increased risk associated with having an affected first-degree relative (OR=2.1, 95% CI=2.0–2.2), and the risk was even greater when subject and relative were diagnosed before age 50 (OR=3.3, 95% CI=2.8–3.9) (Int J Ca 1997;71:800–9). In this study, we examined family history of breast cancer as a risk factor for developing asynchronous contralateral breast cancer (CBC) and compared these risks to those from the aforementioned meta-analysis. Methods: The Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study is a case-control study including women from five population-based cancer registries: four in the US and one in Denmark. The 708 cases in this study were women with CBC and the 1399 individually matched controls were women with unilateral breast cancer (UBC). All participants were initially diagnosed between January 1985 and December 2000 at age 54 years or younger, and were queried about family history of breast cancer among female first- and second-degree relatives. Multivariable-adjusted rate ratios (RR) and corresponding 95% confidence intervals (CI) were calculated using conditional logistic regression. Results: Compared with women who reported no affected relatives, women with at least one first-degree relative with breast cancer were at increased risk of developing CBC (RR=2.1, 95% CI=1.6–2.7); the risk was greater when more than one relative was affected (RR=2.6, 95% CI=1.5–4.6), and was nearly 4-fold (RR=3.9, 95% CI=2.3–6.4) for women having a relative diagnosed with CBC. The risk of CBC was 3.1 (95% CI=1.8–5.3) when both relative and subject were diagnosed before age 45. When the relative was diagnosed before age 45, regardless of subject age, the risk of CBC was 2.6 (95% CI=1.7–4.1). Similarly, when the subject was diagnosed before age 45, regardless of relative's age, the risk of CBC was 2.5 (95% CI=1.7–3.6). Conclusions: The risk of developing CBC is increased among women with a family history of breast cancer, and this risk is significantly greater among those with an affected relative with bilateral cancer, having more than one affected relative, and having relatives affected at young ages. Our results comparing CBC cases to UBC controls were similar to studies where UBC cases are compared to population controls. Citation Information: Cancer Prev Res 2010;3(1 Suppl):B127.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".