Circulating insulin‐like growth factor I in relation to melanoma risk in the European prospective investigation into cancer and nutrition
Bibliographic record
Abstract
Insulin-like growth factor-I (IGF-I) regulates cell proliferation and apoptosis, and is thought to play a role in tumour development. Previous prospective studies have shown that higher circulating concentrations of IGF-I are associated with a higher risk of cancers at specific sites, including breast and prostate. No prospective study has examined the association between circulating IGF-I concentrations and melanoma risk. A nested case-control study of 1,221 melanoma cases and 1,221 controls was performed in the European Prospective Investigation into Cancer and Nutrition cohort, a prospective cohort of 520,000 participants recruited from 10 European countries. Conditional logistic regression was used to estimate odds ratios (ORs) for incident melanoma in relation to circulating IGF-I concentrations, measured by immunoassay. Analyses were conditioned on the matching factors and further adjusted for age at blood collection, education, height, BMI, smoking status, alcohol intake, marital status, physical activity and in women only, use of menopausal hormone therapy. There was no significant association between circulating IGF-I concentration and melanoma risk (OR for highest vs lowest fifth = 0.93 [95% confidence interval [CI]: 0.71 to 1.22]). There was no significant heterogeneity in the association between IGF-I concentrations and melanoma risk when subdivided by gender, age at blood collection, BMI, height, age at diagnosis, time between blood collection and diagnosis, or by anatomical site or histological subtype of the tumour (Pheterogeneity≥0.078). We found no evidence for an association between circulating concentrations of IGF-I measured in adulthood and the risk of melanoma.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".