Serum Insulin-Like Growth Factor-I Levels and Prostatic Intraepithelial Neoplasia: A Clue to the Relationship Between IGF-I Physiology and Prostate Cancer Risk
Bibliographic record
Abstract
Serum insulin-like growth factor-I (IGF-I) levels at the higher end of the reference range have been associated with increased risk for the future development of prostate cancer. We determined whether high serum IGF-I levels are associated with precancerous lesions of the prostate. We conducted a case-control study to determine whether high serum IGF-I levels were associated with the presence of high-grade prostatic intraepithelial neoplasia (HGPIN) among patients who presented for prostate biopsy because of an abnormal serum prostate-specific antigen level or digital rectal exam. We measured serum IGF-I and insulin-like growth factor binding protein-3 (IGFBP-3) prior to prostate biopsy and compared them between 103 men with HGPIN (cases) and 205 men with normal prostate histology (controls). The mean IGF-I level in patients with HGPIN (130.2 ng/mL) was significantly higher compared with controls (118.8 ng/mL, P = 0.01). The mean IGFBP-3 level in patients with HGPIN (2,393.9 ng/mL) was also higher compared with controls (2,276.0 ng/mL, P = 0.06). After adjusting for age, prostate-specific antigen, digital rectal examination, and ethnic background, the odds ratio for a HGPIN diagnosis among men in the highest relative to the lowest quartile of serum IGF-I level was 1.94 (95% confidence interval, 1.0-3.7; P = 0.04). The potential association between a high serum IGF-I level and the presence of HGPIN may represent an important clue to understanding the basis for the relationship between IGF-I physiology and prostate cancer risk. Larger studies will be required to confirm this relationship.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".