Plasma Adiponectin Levels and Endometrial Cancer Risk in Pre- and Postmenopausal Women
Bibliographic record
Abstract
BACKGROUND: Adiponectin, an adipocytokine secreted by adipose tissue, is decreased in obesity, insulin resistance, type 2 diabetes, and polycystic ovary syndrome, all of which are well-established risk factors for endometrial cancer. METHODS: We conducted a case-control study nested within the European Prospective Investigation into Cancer and Nutrition to examine the relation between prediagnostic plasma adiponectin levels and endometrial cancer risk. Among pre- and postmenopausal women who were not currently using exogenous hormones, 284 women developed incident endometrial cancer during an average of 5.1 yr of follow-up. Using risk set sampling, 548 control subjects were selected, matched on center, age, menopausal status, phase of menstrual cycle, time of blood draw, and fasting status. Conditional logistic regression models were used to estimate relative risks and 95% confidence intervals. RESULTS: Adiponectin levels were inversely associated with endometrial cancer risk [body mass index-adjusted relative risk for the top vs. bottom quartile = 0.56 (95% confidence interval 0.36-0.86), P(trend) = 0.006]. There was evidence of a stronger inverse association among obese women than among nonobese women (P(heterogeneity) = 0.03). The inverse association also appeared stronger for women who were postmenopausal or perimenopausal than premenopausal at baseline, but this was not statistically significantly heterogeneous (P(heterogeneity) = 0.51). The association remained statistically significant after separate adjustment for other obesity-related physiological risk factors such as C-peptide, IGF binding protein-1, IGF binding protein-2, SHBG, estrone, or free testosterone but only marginally statistically significant after simultaneous adjustment for these factors. CONCLUSIONS: High circulating adiponectin levels are associated with reduced endometrial cancer risk, largely independent of other obesity-related risk factors.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| 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 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".