C-Peptide, Insulin-like Growth Factor Binding Protein-1, Glycosylated Hemoglobin, and the Risk of Distal Colorectal Adenoma in Women
Bibliographic record
Abstract
BACKGROUND: Determinants of insulin secretion and insulin-like growth factors (IGF) have been directly associated with risk for colorectal cancer. However, few studies have evaluated whether these factors are also associated with risk of colorectal adenoma, the main precursor lesion to colorectal cancer. METHODS: We identified 380 distal colorectal adenoma cases diagnosed between 1989 and 1998 and 380 controls among nondiabetic women from the cohort of 32,826 women, nested in the Nurses' Health Study, who provided blood samples in 1989 to 1990. Cases and controls were individually matched on year of birth, time period of and indication(s) for endoscopy, and date of blood draw. RESULTS: High concentrations of C-peptide, an indicator of insulin secretion, were statistically significantly associated with risk of distal colorectal adenoma [multivariable relative risk (MVRR) top versus bottom quartile, 1.63; 95% confidence interval (95% CI), 1.01-2.66; P = 0.01], even after including body mass index and physical activity in the statistical model. Fasting IGF binding protein-1 (IGFBP-1) concentrations did not show any clear association with risk for adenoma (MVRR top versus bottom quartile, 1.08; 95% CI, 0.56-2.07). These associations did not differ significantly by size/stage of adenoma. Glycosylated hemoglobin (HbA1c) was associated with a nonstatistically significant increased risk of colorectal adenoma (MVRR top versus bottom quartile, 1.47; 95% CI, 0.89-2.44). CONCLUSIONS: High HbA1c and low IGFBP-1 were not clearly associated with increased risk of distal colorectal adenoma. However, our current results and previous associations between C-peptide and colorectal cancer suggest that hyperinsulinemia may play a role throughout the development of colorectal neoplasia.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".