Plasma Biomarkers of Insulin and the Insulin-like Growth Factor Axis, and Risk of Colorectal Adenoma and Serrated Polyp
Bibliographic record
Abstract
Abstract Background Hyperinsulinemia, high insulin-like growth factor 1 (IGF1) levels, and low IGF binding protein 1 (IGFBP1) levels have been implicated in the relationship between obesity and increased risk of colorectal cancer (CRC). However, it remains inconclusive whether circulating biomarkers of insulin and the IGF axis are associated with conventional adenoma and serrated polyp, the two distinct groups of CRC precursors. Methods We prospectively examined the associations of plasma C-peptide, IGF1, IGFBP1, IGFBP3, and IGF1 to IGFBP3 ratio with conventional adenoma and serrated polyp among 11 072 women from the Nurses’ Health Studies. Multivariable logistic regression was used to calculate the odds ratio (OR) per 1-SD increase in each biomarker for overall risk of conventional adenoma and serrated polyp and according to polyp feature. Results During 20 years of follow-up, we documented 1234 conventional adenomas and 914 serrated polyps. After adjusting for various lifestyle factors (including body mass index), higher concentrations of IGFBP1 were associated with lower risk of serrated polyp (OR = 0.84, 95% confidence interval = 0.75 to 0.95, P = .005). The association was particularly strong for large serrated polyp (≥10 mm) located in the distal colon and rectum (OR = 0.59, 95% confidence interval = 0.39 to 0.87, P = .01). In contrast, we did not find any statistically significant association between the biomarkers and conventional adenoma. Conclusions A higher plasma level of IGFBP1 was associated with lower risk of serrated polyp. Our findings support a potential role of IGFBP1 in the serrated pathway of CRC in women.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".