Longitudinal Changes in IGF-I and IGFBP-3, and Mammographic Density among Postmenopausal Women
Bibliographic record
Abstract
A relation between the breast cancer risk factors, insulin-like growth factor-I (IGF-I) and mammographic density, is biologically plausible, but results from cross-sectional epidemiologic studies have been mixed. Our objective was to examine the relation in a longitudinal manner, that is, between the change in circulating IGF-I concentrations and the change in mammographic measures over one year. Data from an exercise intervention trial conducted in 302 postmenopausal women ages 50 to 74 years were used. Blood drawn at baseline and postintervention was assessed for IGF-I and its binding protein (IGFBP-3) by direct chemiluminscent immunoassay. Area and volumetric measurements of mammographic dense fibroglandular and nondense fatty tissue were made. Statistical analyses were based on multiple linear regression. A one SD (20.2 ng/mL) change in IGF-I over one year was associated with small changes in percent dense area [mean: 0.8%; 95% confidence interval (CI), 0.1-1.4] and dense area (mean: 1.2 cm(2); 95% CI, 0.2-2.1). Change in IGFBP-3 was also associated with percent and absolute dense area. Absolute and percent dense volume, and mammographic measures representing fatty tissue (nondense area and volume) were not associated with changes in IGF-I and IGFBP-3. Longitudinal associations may be more detectable than cross-sectional associations due to the absence of confounding by invariant personal factors. Absolute and percent dense area, measures that are related to breast cancer risk, may be affected by IGF-I. Confirmation should be sought in further longitudinal studies in which larger changes in the IGF system are evoked.
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 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) | 0.000 | 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".