Abstract 594: Associations of hemoglobin A1c with risk of diabetes-related cancers in the Cancer Prevention Study-II Nutrition Cohort (CPS-II NC)
Bibliographic record
Abstract
Abstract Self-reported type 2 diabetes mellitus (T2DM) is convincingly associated with higher risks of liver, pancreatic, colon, rectal, female breast, and endometrial cancers, and may also be associated with higher risks of ovarian, bladder and kidney cancers. This evidence largely relies on self-reported T2DM, which does not properly classify the many individuals with pre-diabetes or with undiagnosed T2DM or adequately reflect glucose control among people with T2DM. To clarify these associations, we conducted a case-cohort analysis of hemoglobin A1c (HbA1c), an indicator of circulating glucose over the past 2-to-3 months used to diagnose and monitor T2DM. Participants were identified from the CPS-II NC. From an initial cohort of 32,328 participants who were cancer-free and provided a blood sample at baseline in 1998-2001, we selected a random sub-cohort of 3,000 participants. Further, we selected all participants diagnosed between baseline and June, 2013 with a verified, incident cancer of the colorectum (n=479), liver (n=35), pancreas (n=176), female breast (n=889), endometrium (n=155), ovary (n=93), bladder (n=344), or kidney (n=110). Weighted Cox proportional hazards regression models estimated hazards ratios (HRs) and 95% confidence intervals (CI) for associations of HbA1c with cancer risks combined and stratified by organ site. HRs were adjusted for age, gender, smoking, physical activity, alcohol, and hormone-use (women only). HbA1c levels reflective of clinically-defined T2DM (>=6.5%), compared to HbA1c levels in the non-diabetes range (<5.7%), were associated with statistically significantly higher risks of all 9-T2DM-associated cancers combined (HR: 1.30; 95% CI: 1.05-1.60) and colorectal cancer (HR: 1.58; 95% CI: 1.14-2.19), and associations, although not statistically significant, were in the same, hypothesized directions for risks of liver (HR: 2.30), pancreas (HR: 1.60), endometrial (HR: 1.61), ovarian (HR: 1.85), bladder (HR: 1.23), and kidney (HR: 1.23) cancers. There was no suggestion of association between HbA1c and breast cancer risk (HR: 0.95). Further analyses of colorectal cancer risk combined self-reported T2DM and measured HbA1c levels. Compared to participants who had non-diabetes levels of HbA1c (<=6.5%) and did not report T2DM, participants with high HbA1c levels (>=6.5%) were at higher risk of CRC whether they self-reported T2DM (HR: 1.54), or not (HR:1.56), whereas participants who self-reported T2DM but had good glycemic control (HbA1c =<6.5%) were not at higher risk (HR: 0.96). Results for c-peptide and CRP are forthcoming. This study suggests that HbA1c, a clinically meaningful marker of circulating glucose, is related to the etiology of some cancers. Citation Format: Peter T. Campbell, Christina Newton, Eric J. Jacobs, Michael Pollak, Susan M. Gapstur. Associations of hemoglobin A1c with risk of diabetes-related cancers in the Cancer Prevention Study-II Nutrition Cohort (CPS-II NC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 594.
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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".