Racial Differences in Premenopausal Endogenous Hormones
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Bibliographic record
Abstract
Differences in breast cancer incidence across racial groups are well documented. African Americans have the highest rates of premenopausal breast cancer and Asians have lower breast cancer rates across all age groups. We hypothesized that levels of premenopausal endogenous hormones and growth factors, risk factors that have been predictive of breast cancer, would differ by race. Using a cross-sectional study design, we tested this hypothesis in the Nurses' Health Study II. We assayed estradiol, progesterone, prolactin, sex hormone binding globulin (SHBG), insulin-like growth factor-I (IGF-I), and IGFBP-3 in 111 African American and 111 Asian American women, matched to 111 Caucasian women on age, day of luteal phase, and day, time, and fasting status at blood collection. We analyzed the association between race and hormone levels using robust linear regression methods. In multivariate models, compared with Caucasians, African Americans had 18% higher levels of estradiol (P < 0.01), 17% higher free estradiol (P < 0.01), 11% lower SHBG (P = 0.05), 11% higher IGF-I (P < 0.01), 25% higher free IGF-I (P < 0.01), and 9% lower IGFBP-3 (P < 0.01) levels. In multivariate models, compared with Caucasian women, Asian Americans had 22% higher calculated free estradiol (P < 0.01), 31% lower SHBG (P < 0.01), and 25% higher free IGF-I (P < 0.01) levels. No racial differences were found in progesterone and prolactin levels. Our study showed hormone differences consistent with breast cancer risk between Caucasians and African Americans but inconsistent with breast cancer risk between Asian Americans and Caucasians. Further research is needed to explore differences across racial groups and the link between endogenous hormones and breast cancer risk.
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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) | 0.001 | 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 it