Serum markers, obesity and prostate cancer risk: results from the prostate cancer prevention trial
Bibliographic record
Abstract
Molecular mechanisms linking obesity to prostate cancer involve steroid hormone and insulin/insulin-like growth factor 1 (IGF1) pathways. We investigated the association of circulating serum markers (e.g. androgens and IGFs/IGFBPs) with BMI and in modifying the association of obesity with prostate cancer risk. Data and specimens for this nested case-control study are from the Prostate Cancer Prevention Trial, a randomized, placebo-controlled trial of finasteride for prostate cancer prevention. Presence or absence of cancer was determined by prostate biopsy. Serum samples were assayed for sex steroid hormone concentrations and IGF1 axis analytes. Logistic regression estimated odds ratio and 95% CIs for risk of overall, low-grade (Gleason 2-6), and high-grade (Gleason 7-10) cancers. We found significant associations between BMI with serum steroids and IGFs/IGFBPs; the IGF1 axis was significantly associated with several serum steroids. Serum steroid levels did not affect the association of BMI with prostate cancer risk; however, IGFBP2 and IGFs modified the association of obesity with low- and high-grade disease. While serum steroids and IGFs/IGFBPs are associated with BMI, only the IGF1 axis contributed to obesity-related prostate cancer risk. Understanding the biological mechanisms linking obesity to prostate cancer risk as it relates to circulating serum markers will aid in developing effective prostate cancer prevention strategies and treatments.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".