A Prospective Evaluation of Insulin and Insulin-like Growth Factor-I as Risk Factors for Endometrial Cancer
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Bibliographic record
Abstract
Obesity is a major risk factor for endometrial cancer, a relationship thought to be largely explained by the prevalence of high estrogen levels in obese women. Obesity is also associated with high levels of insulin, a known mitogen. However, no prospective studies have directly assessed whether insulin and/or insulin-like growth factor-I (IGF-I), a related hormone, are associated with endometrial cancer while accounting for estrogen levels. We therefore conducted a case-cohort study of incident endometrial cancer in the Women's Health Initiative Observational Study, a prospective cohort of 93,676 postmenopausal women. The study involved all 250 incident cases and a random subcohort of 465 subjects for comparison. Insulin, total IGF-I, free IGF-I, IGF-binding protein-3, glucose, and estradiol levels were measured in fasting baseline serum specimens. Cox models were used to estimate associations with endometrial cancer, particularly endometrioid adenocarcinomas, the main histologic type (n = 205). Our data showed that insulin levels were positively associated with endometrioid adenocarcinoma [hazard ratio contrasting highest versus lowest quartile (HR(q4-q1)), 2.33; 95% confidence interval (95% CI), 1.13-4.82] among women not using hormone therapy after adjustment for age and estradiol. Free IGF-I was inversely associated with endometrioid adenocarcinoma (HR(q4-q1), 0.53; 95% CI, 0.31-0.90) after adjustment for age, hormone therapy use, and estradiol. Both of these associations were stronger among overweight/obese women, especially the association between insulin and endometrioid adenocarcinoma (HR(q4-q1), 4.30; 95% CI, 1.62-11.43). These data indicate that hyperinsulinemia may represent a risk factor for endometrioid adenocarcinoma that is independent of estradiol. Free IGF-I levels were inversely associated with endometrioid adenocarcinoma, consistent with prior cross-sectional data.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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