Insulin-Like Growth Factors and Insulin-Like Growth Factor–Binding Proteins and Prostate Cancer Risk: Results from the Prostate Cancer Prevention Trial
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Bibliographic record
Abstract
The role of the insulin-like growth factor (IGF) axis and whether IGFs interact with androgen-suppressing agents in relation to prostate carcinogenesis is unclear. This nested case-control study (n = 1,652 cases/1,543 controls) examined whether serum IGF1, IGF2, IGFBP2, IGFBP3, and the IGF1:IGFBP3 ratio were associated with prostate cancer in the Prostate Cancer Prevention Trial (PCPT), a randomized, placebo-controlled trial of finasteride for prostate cancer prevention. Presence or absence of cancer was determined by prostate biopsy. Baseline serum was assayed for IGF-axis analytes using ELISA. Logistic regression estimated ORs and 95% confidence intervals for risk of total, low-grade (Gleason 2-6) and high-grade (Gleason 7-10) cancers. Results were stratified by intervention assignment. In both the placebo and finasteride arms, serum IGF1, IGF2, IGFBP3, and the IGF1:IGFBP3 ratio were not associated with prostate cancer. However, men in the highest versus lowest quartile of serum IGFBP2 had a 48% (P(trend) = 0.02) and 55% (P(trend) = 0.01) increased risk for total and low-grade cancers, respectively. These IGFBP2 associations were attenuated and no longer statistically significant in the finasteride arm. Our results suggest that in general, serum IGF-axis analytes were not associated with prostate cancer risk in the PCPT in which presence or absence of all cancers was biopsy-determined. The exception was the finding that high serum IGFBP2 is a risk factor for low-grade disease, which was attenuated for men on finasteride. Further research is needed to understand better the risk incurred by high IGFBP2 and whether androgen-suppressing agents such as finasteride influence aspects of IGFBP2 physiology relevant to prostate carcinogenesis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it