Glycaemic index, glycaemic load and risk of endometrial cancer: a prospective cohort study
Bibliographic record
Abstract
OBJECTIVE: High-glycaemic-load diets may increase endometrial cancer risk by increasing circulating insulin levels and, as a consequence, circulating oestrogen levels. Given the paucity of epidemiological data regarding the relationship between dietary glycaemic index and glycaemic load and endometrial cancer risk, we sought to examine these associations using data from a prospective cohort study. DESIGN, SETTING AND SUBJECTS: We examined the association between dietary glycaemic load and endometrial cancer risk in a cohort of 49,613 Canadian women aged between 40 and 59 years at baseline who completed self-administered food-frequency questionnaires between 1982 and 1985. Linkages to national mortality and cancer databases yielded data on deaths and cancer incidence, with follow-up ending between 1998 and 2000. RESULTS: During a mean of 16.4 years of follow-up, we observed 426 incident cases of endometrial cancer. Hazard ratios for the highest versus the lowest quartile level of overall glycaemic index and glycaemic load were 1.47 (95% confidence interval (CI) = 0.90-2.41; P for trend = 0.14) and 1.36 (95% CI = 1.01-1.84; P for trend = 0.21), respectively. No association was observed between total carbohydrate or total sugar consumption and endometrial cancer risk. Among obese women (body mass index >30 kg m(-2)) the hazard ratio for the highest versus the lowest quartile level of glycaemic load was 1.88 (95% CI = 1.08-3.29; P for trend = 0.54) and there was a 55% increased risk for the highest versus the lowest quartile level of glycaemic load among premenopausal women. There was also evidence to support a positive association between glycaemic load and endometrial cancer risk among postmenopausal women who had used hormone replacement therapy. CONCLUSIONS: Our data suggest that diets with high glycaemic index or high glycaemic load may be associated with endometrial cancer risk overall, and particularly among obese women, premenopausal women and postmenopausal women who use hormone replacement therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".