Abstract 749: Plasma insulin-like growth factor 1-related biomarkers and risk of lethal prostate cancer
Bibliographic record
Abstract
Abstract Background Experimental and epidemiologic evidence supports the role of plasma IGF-1 and risk of prostate cancer. About 5% of IGF-1 circulates in a free or bioavailable form, and is only weakly correlated with total IGF-1; we hypothesized that higher levels of free IGF-1 would be associated with risk of lethal prostate cancer. Methods Lethal prostate cancer was defined as fatal prostate cancer plus metastatic prostate cancer. Non-lethal prostate cancer was defined as cases in which the men remained free of known metastases for at least eight years. Using prospectively collected samples in a nested design, we identified 434 lethal cases and 524 men with non-lethal prostate cancer in two prospective cohorts: the Physicians' Health Study (mean years of follow-up 33.2) and the Health Professionals Follow-up Study (mean years of follow-up 18.5). Circulating levels in prediagnostic plasma samples were assayed for IGF-1-related biomarkers, including free and total IGF-1, acid labile subunit (ALS), pregnancy-associated plasma protein A (PAPP-A, a protease that cleaves the IGF complex), intact IGF binding protein 4 (IGFBP-4), and total IGFBP-4, with risk of lethal prostate cancer. We estimated odds ratios (ORs) and corresponding 95% confidence intervals (CI) for the associations between IGF-1-related biomarkers (in quartiles) and lethal prostate cancer using unconditional logistic regression models adjusted for age, height, weight, and body mass index. Subgroup analyses were conducted by time from blood draw to diagnosis, and tumor biomarkers, ERG as a marker of the TMPRSS2:ERG fusion, phosphatase and tensin homolog (PTEN) loss, and IGF-1 receptor (IGF1R) protein expression. Results We observed no significant association between free IGF-1 and lethal prostate cancer (pooled adjusted OR for the highest versus lowest group 0.93, 95% CI 0.64 to 1.35) after adjusting for potential covariates. However, men in the highest quartile of PAPP-A levels had 43% higher odds of developing lethal prostate cancer (pooled adjusted OR 1.43, 95% CI 1.05 to 1.95) compared to men in the lowest three quartiles. The positive association between PAPP-A and lethal prostate cancer was present among men without PTEN loss, but not among those with (P for interaction = 0.002). There were no significant differences across the two cohorts (P for heterogeneity > 0.05 for all) and no significant associations were observed between other plasma biomarkers and lethal prostate cancer. Conclusions We found no significant association between free IGF-1 and lethal prostate cancer, but provide suggestive evidence that higher PAPP-A levels are associated with an increased risk of developing lethal prostate cancer. This observation merits testing in other cohorts. Citation Format: Chaoran Ma, Ye Wang, Lorelei A. Mucci, Meir J. Stampfer, Michael Pollak, Kathryn L. Penney. Plasma insulin-like growth factor 1-related biomarkers and risk of lethal prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 749.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".