Circulating anti-Müllerian hormone and breast cancer risk: A study in ten prospective cohorts
Bibliographic record
Abstract
A strong positive association has been observed between circulating anti-Müllerian hormone (AMH), a biomarker of ovarian reserve, and breast cancer risk in three prospective studies. Confirming this association is important because of the paucity of biomarkers of breast cancer risk in premenopausal women. We conducted a consortium study including ten prospective cohorts that had collected blood from premenopausal women. A nested case–control design was implemented within each cohort. A total of 2,835 invasive (80%) and in situ (20%) breast cancer cases were individually matched to controls (n = 3,122) on age at blood donation. AMH was measured using a high sensitivity enzyme-linked immunoabsorbent assay. Conditional logistic regression was applied to the aggregated dataset. There was a statistically significant trend of increasing breast cancer risk with increasing AMH concentration (ptrend across quartiles <0.0001) after adjusting for breast cancer risk factors. The odds ratio (OR) for breast cancer in the top vs. bottom quartile of AMH was 1.60 (95% CI = 1.31–1.94). Though the test for interaction was not statistically significant (pinteraction = 0.15), the trend was statistically significant only for tumors positive for both estrogen receptor (ER) and progesterone receptor (PR): ER+/PR+: ORQ4–Q1 = 1.96, 95% CI = 1.46–2.64, ptrend <0.0001; ER+/PR−: ORQ4–Q1 = 0.82, 95% CI = 0.40–1.68, ptrend = 0.51; ER−/PR+: ORQ4–Q1 = 3.23, 95% CI = 0.48–21.9, ptrend = 0.26; ER−/PR−: ORQ4–Q1 = 1.15, 95% CI = 0.63–2.09, ptrend = 0.60. The association was observed for both pre- (ORQ4–Q1= 1.35, 95% CI = 1.05–1.73) and post-menopausal (ORQ4–Q1 = 1.61, 95% CI = 1.03–2.53) breast cancer (pinteraction = 0.34). In this large consortium study, we confirmed that AMH is associated with breast cancer risk, with a 60% increase in risk for women in the top vs. bottom quartile of AMH.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".