Serum insulin‐like growth factor (IGF)‐I and IGF binding protein‐3 in relation to terminal duct lobular unit involution of the normal breast in Caucasian and African American women: The Susan G. Komen Tissue Bank
Bibliographic record
Abstract
Lesser degrees of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini/TDLU, are associated with elevated breast cancer risk. In rodent models, the insulin‐like growth factor (IGF) system regulates involution of the mammary gland. We examined associations of circulating IGF measures with TDLU involution in normal breast tissues among women without precancerous lesions. Among 715 Caucasian and 283 African American (AA) women who donated normal breast tissue samples to the Komen Tissue Bank between 2009 and 2012 (75% premenopausal), serum concentrations of IGF‐I and binding protein (IGFBP)‐3 were quantified using enzyme‐linked immunosorbent assay. Hematoxilyn and eosin‐stained tissue sections were assessed for numbers of TDLUs (“TDLU count”). Zero‐inflated Poisson regression models with a robust variance estimator were used to estimate relative risks (RRs) for association of IGF measures (tertiles) with TDLU count by race and menopausal status, adjusting for potential confounders. AA (vs. Caucasian) women had higher age‐adjusted mean levels of serum IGF‐I (137 vs. 131 ng/mL, p = 0.07) and lower levels of IGFBP‐3 (4165 vs. 4684 ng/mL, p < 0.0001). Postmenopausal IGFBP‐3 was inversely associated with TDLU count among AA (RRT3vs.T1 = 0.49, 95% CI = 0.28–0.84, p‐trend = 0.04) and Caucasian (RRT3vs.T1=0.64, 95% CI = 0.42–0.98, p‐trend = 0.04) women. In premenopausal women, higher IGF‐I:IGFBP‐3 ratios were associated with higher TDLU count in Caucasian (RRT3vs.T1=1.33, 95% CI = 1.02–1.75, p‐trend = 0.04), but not in AA (RRT3vs.T1=0.65, 95% CI = 0.42–1.00, p‐trend = 0.05), women. Our data suggest a role of the IGF system, particularly IGFBP‐3, in TDLU involution of the normal breast, a breast cancer risk factor, among Caucasian and AA women.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".