Case–Control Study of the Metabolic Syndrome and Metabolic Risk Factors for Endometrial Cancer
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome may predict endometrial cancer risk better than diabetes, hypertension, dyslipidemia, dysglycemia, or weight alone, but few studies have examined this issue. METHODS: We conducted a population-based case-control study in Alberta, Canada (2002-2006) that included 515 incident endometrial cancer cases and 962 frequency age-matched controls. Data were collected through in-person interviews, anthropometric measurements, and 8-hour fasting bloods drawn either pre- or postsurgery. Bloods were analyzed using quantitative colorimetric or absorbance-based assays (ELISA), specific to metabolic syndrome markers. Metabolic syndrome was defined using harmonized guidelines requiring presence of ≥ 3 of the following risk factors: waist circumference ≥ 88 cm, triglycerides ≥ 150 mg/dL, high-density lipoprotein cholesterol <50 mg/dL, treatment of previously diagnosed hypertension, and fasting blood glucose ≥ 100 mg/dL. OR and 95% CIs for endometrial cancer risk with presence of metabolic syndrome and individual metabolic syndrome components were estimated using logistic regression analysis. RESULTS: Metabolic syndrome was significantly more prevalent among cases (62%) than controls (38%). A statistically significant increased risk for endometrial cancer was observed for metabolic syndrome (OR = 1.53; 95% CI: 1.17-2.00), as well as for some of the individual components of metabolic syndrome including waist circumference ≥ 88 cm (OR = 1.57; 95% CI: 1.18-2.08), hypertension (OR = 1.57; 95% CI: 1.18-2.09), and fasting blood glucose ≥ 100 mg/dL (OR = 1.31; 95% CI: 1.03-1.67). Some evidence for effect modification by menopausal status and body mass index was also found. CONCLUSION: Metabolic syndrome is clearly associated with increased endometrial cancer risk. IMPACT: Targeting the entire metabolic syndrome may optimize endometrial cancer risk reduction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".