Serum Fructosamine and Subsequent Breast Cancer Risk: A Nested Case-Control Study in the ORDET Prospective Cohort Study
Bibliographic record
Abstract
There is evidence that abnormal glucose metabolism may contribute to the risk of breast cancer. The measurement of markers of glucose metabolism could help to identify women at risk for breast cancer. Serum fructosamine is one such marker. In this study, we investigated whether prediagnostic serum fructosamine was associated with breast cancer. Between 1987 and 1992, 10,786 women ages 35 to 69 were recruited in Italy for a prospective study. Women with a history of cancer or on hormone therapy were excluded at baseline. Blood samples were collected after 12 hours fasting from all participants at recruitment. After 5.5 years of follow-up, 144 breast cancer cases were identified and four matched controls were selected from the cohort; serum fructosamine levels were measured in both groups at baseline. Adjusted odds ratios (OR) for the highest tertile of serum fructosamine compared to the lowest was 1.60 [95% confidence interval (CI), 0.95-2.73]. In premenopausal women, the OR was 1.58 (95% CI, 0.76-3.40) and in postmenopausal women, the OR was 1.60 (95% CI, 0.76-3.48). Serum fructosamine levels tended to be positively associated with breast cancer risk independent of menopausal status.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".