TY - JOUR
T1 - Prospective Association of Energy Balance Scores Based on Metabolic Biomarkers with Colorectal Cancer Risk
AU - Guinter, Mark A.
AU - Gapstur, Susan M.
AU - McCullough, Marjorie L.
AU - Flanders, W. Dana
AU - Wang, Ying
AU - Rees-Punia, Erika
AU - Alcaraz, Kassandra I.
AU - Pollak, Michael N.
AU - Campbell, Peter T.
N1 - Funding Information:
This work was supported by the American Cancer Society's Cancer Prevention Studies Postdoctoral Fellowship Program (to M.A. Guinter and E. Rees-Punia) and by American Cancer Society funds for the creation, maintenance, and updating of the Cancer Prevention Study-II cohort. The authors sincerely appreciate all Cancer Prevention Study-II participants and each member of the study and biospecimen management group. The authors acknowledge the contributions to this study from central cancer registries supported through the Centers for Disease Control and Prevention's National Program of Cancer Registries and cancer registries supported by the NCI's SEER Program.
Publisher Copyright:
©2020 American Association for Cancer Research.
PY - 2020/5
Y1 - 2020/5
N2 - Background: Energy balance–related factors, such as body mass index (BMI), diet, and physical activity, may influence colorectal cancer etiology through interconnected metabolic pathways, but their combined influence is less clear. Methods: We used reduced rank regression to derive three energy balance scores that associate lifestyle factors with combinations of prediagnostic, circulating levels of high-sensitivity C-reactive protein (hsCRP), C-peptide, and hemoglobin A1c (HbA1c) among 2,498 participants in the Cancer Prevention Study-II Nutrition Cohort. Among 114,989 participants, we verified 2,228 colorectal cancer cases. We assessed associations of each score with colorectal cancer incidence and by tumor molecular phenotypes using Cox proportional hazards regression. Results: The derived scores comprised BMI, physical activity, screen time, and 14 food groups, and explained 5.1% to 10.5% of the variation in biomarkers. The HR and 95% confidence interval (CI) for quartile 4 versus 1 of the HbA1cþC peptide–based score and colorectal cancer was 1.30 (1.15–1.47), the hsCRP-based score was 1.35 (1.19–1.53), and the hsCRP, C-peptide, and HbA1c-based score was 1.35 (1.19–1.52). The latter score was associated with non-CIMP tumors (HRQ4vsQ1: 1.59; 95% CI: 1.17–2.16), but not CIMP-positive tumors (Pheterogeneity ¼ 0.04). Conclusions: These results further support hypotheses that systemic biomarkers of metabolic health—inflammation and abnormal glucose homeostasis—mediate part of the relationship between several energy balance–related modifiable factors and colorectal cancer risk. Impact: Results support cancer prevention guidelines for maintaining a healthful body weight, consuming a healthful diet, and being physically active. More research is needed on these clusters of exposures with molecular phenotypes of tumors.
AB - Background: Energy balance–related factors, such as body mass index (BMI), diet, and physical activity, may influence colorectal cancer etiology through interconnected metabolic pathways, but their combined influence is less clear. Methods: We used reduced rank regression to derive three energy balance scores that associate lifestyle factors with combinations of prediagnostic, circulating levels of high-sensitivity C-reactive protein (hsCRP), C-peptide, and hemoglobin A1c (HbA1c) among 2,498 participants in the Cancer Prevention Study-II Nutrition Cohort. Among 114,989 participants, we verified 2,228 colorectal cancer cases. We assessed associations of each score with colorectal cancer incidence and by tumor molecular phenotypes using Cox proportional hazards regression. Results: The derived scores comprised BMI, physical activity, screen time, and 14 food groups, and explained 5.1% to 10.5% of the variation in biomarkers. The HR and 95% confidence interval (CI) for quartile 4 versus 1 of the HbA1cþC peptide–based score and colorectal cancer was 1.30 (1.15–1.47), the hsCRP-based score was 1.35 (1.19–1.53), and the hsCRP, C-peptide, and HbA1c-based score was 1.35 (1.19–1.52). The latter score was associated with non-CIMP tumors (HRQ4vsQ1: 1.59; 95% CI: 1.17–2.16), but not CIMP-positive tumors (Pheterogeneity ¼ 0.04). Conclusions: These results further support hypotheses that systemic biomarkers of metabolic health—inflammation and abnormal glucose homeostasis—mediate part of the relationship between several energy balance–related modifiable factors and colorectal cancer risk. Impact: Results support cancer prevention guidelines for maintaining a healthful body weight, consuming a healthful diet, and being physically active. More research is needed on these clusters of exposures with molecular phenotypes of tumors.
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U2 - 10.1158/1055-9965.EPI-19-1382
DO - 10.1158/1055-9965.EPI-19-1382
M3 - Article
C2 - 32094199
AN - SCOPUS:85084960906
SN - 1055-9965
VL - 29
SP - 974
EP - 981
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 5
ER -