Race, ethnicity and risk of second primary contralateral breast cancer in the United States
Bibliographic record
Abstract
Breast cancer survivors have a high risk of a second primary contralateral breast cancer (CBC), but there are few studies of CBC risk in racial/ethnic minority populations. We examined whether the incidence and risk factors for CBC differed by race/ethnicity in the United States. Women with a first invasive Stage I-IIB breast cancer diagnosis at ages 20-74 years between 2000 and 2015 in the Surveillance, Epidemiology, and End Results Program (SEER) 18 registries were followed through 2016 for a diagnosis of invasive CBC ≥1 year after the first breast cancer diagnosis. We used cause-specific Cox proportional hazards models to test the association between race/ethnicity and CBC, adjusting for age, hormone receptor status, radiation therapy, chemotherapy and stage at first diagnosis, and evaluated the impact of contralateral prophylactic mastectomy, socioeconomic status, and insurance status on the association. After a median follow-up of 5.9 years, 9247 women (2.0%) were diagnosed with CBC. Relative to non-Hispanic (NH) White women, CBC risk was increased in NH Black women (hazard ratio = 1.44, 95% CI 1.35-1.54) and Hispanic women (1.11, 95% CI 1.02-1.20), with the largest differences among women diagnosed at younger ages. Adjustment for contralateral prophylactic mastectomy, socioeconomic status and health insurance did not explain the associations. Therefore, non-Hispanic Black and Hispanic women have an increased risk of CBC that is not explained by clinical or socioeconomic factors collected in SEER. Large studies of diverse breast cancer survivors with detailed data on treatment delivery and adherence are needed to inform interventions to reduce this disparity.
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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 | 0.000 | 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 | 0.000 |
| 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 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".