Abstract 4936: The association between plasma IGFBP7 and cancer incidence, cancer mortality, and all-cause mortality in ARIC
Bibliographic record
Abstract
Abstract Background: Insulin-like Growth Factor Binding Protein 7 (IGFBP7) may modulate IGF signaling and influence non-IGF molecular mechanisms. We analyzed whether IGFBP7 concentration in plasma is associated with risk of cancer incidence, cancer mortality, and all-cause mortality. Methods: We conducted a prospective cohort analysis of 10, 834 participants (54.8% female, 24.3% Black) with no cancer history for cancer incidence and mortality analyses, and 11, 761 participants (55.6% female, 23.6% Black) for the all-cause mortality analysis in the Atherosclerosis Risk in Communities study. The median follow-up time was 22.8, 23.5, and 25.6 years for the respective analyses. Participants were aged 46-70 years old at start of follow-up. Plasma IGFBP7 was measured using SomaScan® 5K assay, an aptamer-based technology for protein profiling. Incident cancer diagnoses were ascertained by state cancer registry linkage supplemented with medical records and death certificates. Mortality was ascertained by death certificates, including via the National Death Index. We estimated the association between IGFBP7 plasma levels (log2transformed) and outcomes including cancer incidence, cancer mortality, and all-cause mortality using Cox proportional hazards regression models adjusting for age, sex, race, and other potential risk factors for cancer and/or mortality. Results: The association between IGFBP7 and total cancer incidence (3, 347 cases, 200, 279 person-years) was null (HR=0.99, 95% CI 0.85-1.16). However, IGFBP7 was positively associated with lung cancer incidence (479 cases, 199, 823 person-years; HR=1.40, 95% CI 0.93-2.10), unlike for other common cancer sites. The association between IGFBP7 and total cancer mortality (1, 420 deaths, 222, 320 person-years) was statistically significant (HR=1.39, 95% CI 1.10-1.76). Of the common cancers, IGFBP7 was positively associated with lung cancer mortality (HR=1.69, 95% CI 1.10-2.60) and breast cancer mortality (HR=2.09, 95% CI 0.88-4.97). The association between IGFBP7 and all-cause mortality (6, 981 deaths, 262, 734 person-years) was statistically significant and the strongest among the three main analyses (HR=1.72, 95% CI 1.55-1.91). Stratifying by age, the strongest association between IGFBP7 and all-cause mortality was in the youngest age quartile (ages 46.9-52.6 years; HR=2.69, 95% CI 2.01-3.59). IGFBP7 is not strongly correlated with IGF-1 and other family proteins. Conclusions: High circulating IGFBP7 levels may be a risk factor for cancer and all-cause mortality, especially among those in middle adulthood. High circulating IGFBP7 levels may also be a risk factor for both lung cancer incidence and mortality. Additional research and laboratory testing will be necessary to determine whether IGFBP7’s influence on IGF signaling or other mechanisms contribute to tumor progression and mortality, in general. Support: NHLBI, NCI, NPCR Citation Format: Vernon A. Burk, Michael N. Pollak, Corinne E. Joshu, Anna Prizment, Elizabeth A. Platz. The association between plasma IGFBP7 and cancer incidence, cancer mortality, and all-cause mortality in ARIC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4936.
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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 | 0.001 |
| 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) | 0.005 | 0.001 |
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".