Metabolic syndrome, plasma lipid, lipoprotein and glucose levels, and endometrial cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC)
Bibliographic record
Abstract
To clarify the role of metabolic factors in endometrial carcinogenesis, we conducted a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC), and examined the relation between prediagnostic plasma lipids, lipoproteins, and glucose, the metabolic syndrome (MetS; a cluster of metabolic factors) and endometrial cancer risk. Among pre- and postmenopausal women, 284 women developed endometrial cancer during follow-up. Using risk set sampling, 546 matched control subjects were selected. From conditional logistic regression models, high-density lipoprotein cholesterol (HDL-C) levels were inversely associated with risk body mass index (BMI)-adjusted relative risk (RR) for top versus bottom quartile 0.61 (95% confidence intervals (CI) 0.38-0.97), P(trend) = 0.02). Glucose levels were positively associated with risk (BMI-adjusted RR top versus bottom quartile 1.69 (95% CI 0.99-2.90), P(trend) = 0.03), which appeared stronger among postmenopausal women (BMI-adjusted RR top versus bottom tertile 2.61 (95% CI 1.46-4.66), P(trend) = 0.0006, P(heterogeneity) = 0.13) and never-users of exogenous hormones (P(heterogeneity) = 0.005 for oral contraceptive (OC) use and 0.05 for hormone replacement therapy-use). The associations of HDL-C and glucose with risk were no longer statistically significant after further adjustment for obesity-related hormones. Plasma total cholesterol, Low-density lipoprotein cholesterol (LDL-C), and triglycerides were not significantly related to overall risk. The presence of MetS was associated with risk (RR 2.12 (95% CI 1.51-2.97)), which increased with the number of MetS factors (P(trend) = 0.02). An increasing number of MetS factors other than waist circumference, however, was marginally significantly associated with risk only in women with waist circumference above the median (P(interaction) = 0.01). None of the associations differed significantly by fasting status. These findings suggest that metabolic abnormalities and obesity may act synergistically to increase endometrial cancer risk.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".