Insulin-like growth factor-I, its binding proteins (IGFBP-1 and IGFBP-3), and growth hormone and breast cancer risk in The Nurses Health Study II
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Earlier data suggest that the relationship between circulating insulin-like growth factor I (IGF-I) levels and breast cancer risk differs according to menopausal status. We evaluated the association between IGF levels as well as the primary regulator of IGF-I production, growth hormone (GH), and breast cancer risk in the Nurses' Health Study II (NHS II) cohort, a large cohort of primarily premenopausal women. We conducted a case-control study nested within the prospective NHS II cohort. Plasma concentrations of IGF-I, IGF binding protein (IGFBP)-3, IGFBP-1, and GH were measured in blood samples collected between 1996 and 1999. Totally 317 women were identified who had a diagnosis of invasive or in situ breast cancer between the date of blood collection and June 1 2003; 75% of these women were premenopausal at blood collection. To each of the 317 women, two controls were age-matched for a total of 634 controls. We used conditional logistic regression models to estimate the relative risk of breast cancer. Overall, plasma IGF-I, IGFBP-1, IGFBP-3, and GH levels were not associated with breast cancer risk (relative risks, top vs bottom quartile; IGF-I, 0.98, 95% confidence interval (CI), 0.69-1.39; IGFBP-1, 0.95, 95% CI, 0.63-1.41; IGFBP-3, 1.10, 95% CI, 0.78-1.54; GH, 1.09, 95% CI, 0.82-1.46). These risks were similar for premenopausal women of age 45 years or less. Further adjustment for additional breast cancer risk factors did not change these estimates. In conclusion, circulating IGF-I, IGFBP-1, IGFBP-3, and GH levels appear to have no important association with breast cancer risk in a large cohort of premenopausal women.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it