Insulin-like growth factor-1, insulin-like growth factor-binding protein-3, and breast cancer risk: observational and Mendelian randomization analyses with ∼430 000 women
Bibliographic record
Abstract
Background Epidemiological evidence supports a positive association between circulating insulin-like growth factor-1 (IGF-1) concentrations and breast cancer risk, but both the magnitude and causality of this relationship are uncertain. We conducted observational analyses with adjustment for regression dilution bias, and Mendelian randomization (MR) analyses allowed for causal inference. Patients and methods We investigated the associations between circulating IGF-1 concentrations and incident breast cancer risk in 206 263 women in the UK Biobank. Multivariable hazard ratios (HRs) and 95% confidence intervals (CI) were estimated using Cox proportional hazards models. HRs were corrected for regression dilution using repeat IGF-1 measures available in a subsample of 6711 women. For the MR analyses, genetic variants associated with circulating IGF-1 and IGF-binding protein-3 (IGFBP-3) levels were identified and their association with breast cancer was examined with two-sample MR methods using genome-wide data from 122 977 cases and 105 974 controls. Results In the UK Biobank, after a median follow-up of 7.1 years, 4360 incident breast cancer cases occurred. In the multivariable-adjusted models corrected for regression dilution, higher IGF-1 concentrations were associated with a greater risk of breast cancer (HR per 5 nmol/l increment of IGF-1 = 1.11, 95% CI = 1.07–1.16). Similar positive associations were found by follow-up time, menopausal status, body mass index, and other risk factors. In the MR analyses, a 5 nmol/l increment in genetically-predicted IGF-1 concentration was associated with a greater breast cancer risk (odds ratio = 1.05, 95% CI = 1.01–1.10; P = 0.02), with a similar effect estimate for estrogen-positive (ER + ) tumours, but no effect found for estrogen-negative (ER − ) tumours. Genetically-predicted IGFBP-3 concentrations were not associated with breast cancer risk (odds ratio per 1-standard deviation increment = 1.00, 95% CI = 0.97–1.04; P = 0.98). Conclusion Our results support a probable causal relationship between circulating IGF-1 concentrations and breast cancer, suggesting that interventions targeting the IGF pathway may be beneficial in preventing breast tumorigenesis.
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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 | 0.024 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".