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Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
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Oxidative Balance Score, Colorectal Adenoma, and Markers of Oxidative Stress and Inflammation

So Yeon J. Kong, Roberd M. Bostick, W. Dana Flanders, William M. McClellan, Bharat Thyagarajan, Myron D. Gross, Suzanne Judd and Michael Goodman
So Yeon J. Kong
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
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Roberd M. Bostick
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
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W. Dana Flanders
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
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William M. McClellan
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
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Bharat Thyagarajan
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
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Myron D. Gross
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
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Suzanne Judd
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
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Michael Goodman
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
1Department of Epidemiology, Rollins School of Public Health; 2Winship Cancer Institute, Emory University, Atlanta, Georgia; 3Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota; and 4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama
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DOI: 10.1158/1055-9965.EPI-13-0619 Published March 2014
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  • Table 1.

    OBS assignment scheme

    OBS componentsAssignment schemea
    1. PUFA intake0 = High (3rd tertile), 1 = Medium (2nd tertile), 2 = Low (1st tertile)
    2. Serum ferritin0 = High (3rd tertile), 1 = Medium (2nd tertile), 2 = Low (1st tertile)
    3. Totalb vitamin C intake0 = Low (1st tertile), 1 = Medium (2nd tertile), 2 = High (3rd tertile)
    4. Plasma lycopene0 = Low (1st tertile), 1 = Medium (2nd tertile), 2 = High (3rd tertile)
    5. Plasma α-carotene0 = Low (1st tertile), 1 = Medium (2nd tertile), 2 = High (3rd tertile)
    6. Plasma β-carotene0 = Low (1st tertile), 1 = Medium (2nd tertile), 2 = High (3rd tertile)
    7. Plasma lutein0 = Low (1st tertile), 1 = Medium (2nd tertile), 2 = High (3rd tertile)
    8. Plasma β-cryptoxanthin0 = Low (1st tertile), 1 = Medium (2nd tertile), 2 = High (3rd tertile)
    9. Plasma α-tocopherol0 = Low (1st tertile), 1 = Medium (2nd tertile), 2 = High (3rd tertile)
    10. Selenium supplements0 = No supplement, 1 = Unknown (missing data), 2 = Supplement
    11. Smoking history0 = Current smoker, 1 = Former smoker, 2 = Never smoker
    12. Regular aspirin use0 = No regular use, 1 = Unknown, 2 = Regular use
    13. Regular NSAID use0 = No regular use, 1 = Unknown, 2 = Regular use
    14. Alcohol consumption0 = Above median, 1 = Below median, 2 = Nondrinker

    Abbreviation: PUFA, polyunsaturated fatty acid.

    • ↵aLow, intermediate, and high categories correspond to study-specific tertile values among controls.

    • ↵bTotal intake = dietary intake + supplemental intake.

  • Table 2.

    Selected baseline characteristics of participants in the MAP I and II case–control studies of incident, sporadic colorectal adenomas

    MAP IMAP IIPooled analysis
    CharacteristicsCases (n = 106) mean (SD) or %Controls (n = 109) mean (SD) or %Cases (n = 33) mean (SD) or %Controls (n = 92) mean (SD) or %Cases (n = 139) mean (SD) or N (%)Controls (n = 201) mean (SD)
    Age, y57.4 (8.9)56.1 (10.2)55.4 (7.3)55.5 (7.9)56.9 (8.6)55.9 (9.2)
    Male (%)54.732.1a57.644.655.437.8b
    BMI, kg/m227.8 (6.1)27.1 (5.7)28.5 (5.2)28.6 (6.7)27.9 (5.9)27.8 (6.2)
    Physical activity, MET-hours/week216.8 (143.4)196.1 (127.3)163.7 (116.9)176.5 (125.2)204.2 (139.1)187.1 (126.4)
    Family history of colorectal cancerc (%)17.033.0a21.119.618.026.9
    HRT user (women only; %)62.554.178.670.666.160.8
    Regularly take an NSAID (%)21.232.133.334.824.133.3
    Regularly take aspirin (%)34.935.845.541.337.438.3
    Current smoker (%)34.020.2a24.213.031.716.9a
    Alcohol, drinks/week20.8 (25.6)14.6 (20.2)9.4 (9.1)13.4 (16.3)16.3 (21.4)13.9 (17.8)
    Dietary intakes per day
     Total energy, kcal2,061.3 (851.8)2,172.6 (2493.7)1,831.3 (765.3)1,648.0 (647.8)2,006.7 (835.1)1,932.5 (1,902.0)
     Total PUFA, gm14.0 (6.3)14.4 (14.5)15.5 (8.9)14.1 (10.4)14.3 (7.0)14.2 (12.8)
     Dietary fiber, gm22.8 (9.4)25.5 (26.6)16.6 (6.7)15.3 (6.7)21.3 (9.2)20.9 (20.7)
     Totald vitamin C, mg286.6 (388.5)302.1 (354.6)237.5 (273.6)298.9 (369.4)275.0 (364.2)300.7 (360.6)
    Plasma levels
     Plasma lycopene, μg/dL26.3 (14.3)25.8 (13.3)21.7 (11.4)24.6 (10.8)25.2 (13.8)25.2 (12.2)
     Plasma α-carotene, μg/dL2.7 (2.9)3.6 (4.8)2.6 (2.6)3.5 (3.1)2.7 (2.8)3.5 (4.1)b
     Plasma β-carotene, μg/dL15.3 (22.5)16.4 (15.5)12.6 (11.4)16.3 (13.0)14.6 (20.4)16.4 (14.4)
     Plasma lutein, μg/dL16.8 (7.2)18.1 (10.3)17.7 (6.2)15.7 (6.3)17.0 (6.9)17.0 (8.7)
     Plasma β-cryptoxanthin, μg/dL6.0 (4.7)6.9 (5.8)6.1 (4.1)8.1 (7.2)6.0 (4.5)7.5 (6.5)b
     Plasma α-tocopherol, mg/dL1.2 (0.5)1.1 (0.5)1.1 (0.3)1.2 (0.6)1.1 (0.5)1.2 (0.5)
     Plasma γ-tocopherol, mg/dL0.2 (0.1)0.2 (0.1)0.2 (0.1)0.2 (0.1)0.2 (0.1)0.2 (0.1)
     Plasma ferritin, mg/dL146.1 (135.2)148.8 (185.9)144.5 (108.3)130.8 (127.5)145.7 (129.0)140.6 (161.7)
     Plasma total cholesterol, mg/dL203.4 (35.8)206.3 (39.5)194.8 (32.4)199.3 (39.5)201.4 (35.1)203.1 (39.6)
    Biomarker levels
     FIP, pg/mL94.0 (41.8)88.8 (38.4)76.0 (25.0)78.0 (28.9)90.1 (39.3)84.4 (35.1)
     FOP, avg. std. ref. adj.e0.06 (0.03)0.05 (0.02)0.03 (0.01)0.04 (0.01)0.05 (0.11)0.05 (0.13)
     CRP, μg/mL6.1 (6.1)7.5 (23.8)3.7 (5.0)4.6 (6.2)5.5 (6.0)6.2 (18.0)

    Abbreviation: PUFA, polyunsaturated fatty acid.

    • ↵aP < 0.01 based on t test for continuous variable and χ2 test for categorical variables.

    • ↵bP < 0.05 based on t test for continuous variables and χ2 test for categorical variables.

    • ↵cIn a first-degree relative.

    • ↵dTotal = dietary + supplemental.

    • ↵eUnit for FOP measurement is “average standard reference adjusted,” in which samples were calculated against a 1-ppm fluorescent reference standard quinine in 0.1 N sulfuric acid.

  • Table 3.

    Association between OBS (with and without inclusion of γ-tocopherol) and incident, sporadic colorectal adenoma

    Cases (n)aControls (n)aOR (95% CI)bP trend
    OBS without γ-tocopherol (range, 2–24)
     Interval 1 (OBS, 2–9)44431.00.04
     Interval 2 (OBS, 10–16)811140.81 (0.46–1.43)
     Interval 3 (OBS, 17–24)14440.39 (0.17–0.89)
    OBS as continuous variable1392010.93 (0.87–0.99)
    OBS with γ-tocopherol (range, 2–25)
     Interval 1 (OBS, 2–9)34311.00.04
     Interval 2 (OBS, 10–17)881260.76 (0.40–1.43)
     Interval 3 (OBS, 18–25)17440.40 (0.17–0.97)
    OBS as continuous variable1392010.93 (0.88–0.99)
    • ↵aTotal number of subjects in the models is lower due to missing covariate data.

    • ↵bAdjusted for age, race, sex, BMI, total energy intake, plasma cholesterol, and family history of colorectal cancer in a first-degree relative, hormone replacement therapy (among women), dietary fiber, physical activity, and study (MAP I or MAP II).

  • Table 4.

    Associations between OBS and markers of oxidative stress and inflammation

    Biomarkersa
    OBSHighcLowcOR (95% CI)bP trend
    FIP
     Interval 1 (OBS, 2–9)51201.0<0.01
     Interval 2 (OBS, 10–16)91680.50 (0.25–1.01)
     Interval 3 (OBS, 17–24)17270.25 (0.10–0.65)
    Continuous1591150.87 (0.81–0.94)
    FOP
     Interval 1 (OBS, 2–9)33451.0<0.01
     Interval 2 (OBS, 10–16)107772.01 (1.13–3.75)
     Interval 3 (OBS, 17–24)36193.48 (1.51–8.02)
    Continuous1761411.10 (1.03–1.17)
    CRP
     Interval 1 (OBS, 2–9)56311.0<0.01
     Interval 2 (OBS, 10–16)108870.57 (0.31–1.04)
     Interval 3 (OBS, 17–24)19390.21 (0.09–0.49)
    Continuous1831570.88 (0.82–0.94)
    • ↵aEach biomarker was dichotomized into “high” and “low” based on study- and sex-specific median values among controls.

    • ↵bAdjusted for age, race, sex, BMI, total energy intake, plasma cholesterol, and family history of colorectal cancer in a first-degree relative, hormone replacement therapy (among women), dietary fiber, physical activity, and study (MAP I or MAP II).

    • ↵cTotal numbers of subjects in the models differ due to missing covariate or biomarker data.

  • Table 5.

    Associations of markers of oxidative stress and inflammation with incident, sporadic colorectal adenoma

    BiomarkeraCasescControlscOR (95% CI)bP
    FIP
     Low39761.00.03
     High80791.89 (1.08–3.30)
    Log (continuous)1191551.38 (0.79–2.38)
    FOP
     Low44971.00.02
     High82941.82 (1.11–2.99)
    Log (continuous)1261911.32 (0.94–1.87)
    CRP
     Low551021.00.14
     High84991.45 (0.88–2.40)
    Log (continuous)1392011.14 (0.97–1.33)
    • ↵aEach biomarker was dichotomized into “high” and “low” based on sex-specific median values among controls.

    • ↵bAdjusted for age, race, sex, BMI, total energy intake, plasma cholesterol, and family history of colorectal cancer in a first-degree relative, hormone replacement therapy (among women), dietary fiber, physical activity, and study (MAP I or MAP II).

    • ↵cTotal numbers of subjects in the models differ due to missing covariate or biomarker data.

Additional Files

  • Tables
  • Supplementary Data

    Files in this Data Supplement:

    • Supplementary Tables 1 through 4 and Supplementary Figure 1 - PDF - 145K, Supplemental Table 1: Sensitivity analyses to evaluate the impact of individual OBS components on the association between OBS and incident, sporadic colorectal adenoma. Supplemental Table 2: Associations of the OBS (in quartiles) with incident, sporadic colorectal adenoma. Supplemental Table 3: Associations of the biomarkers (divided into quartiles) with incident, sporadic colorectal adenoma. Supplemental Table 4. Association of individual OBS components with each biomarker. Supplemental Figure 1: A hypothetical directed acyclic graph (DAG) showing possible inter-relation of OBS, biomarkers of oxidative stress (FIP and FOP) and inflammation (CRP), and colorectal adenoma.
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Cancer Epidemiology Biomarkers & Prevention: 23 (3)
March 2014
Volume 23, Issue 3
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Oxidative Balance Score, Colorectal Adenoma, and Markers of Oxidative Stress and Inflammation
So Yeon J. Kong, Roberd M. Bostick, W. Dana Flanders, William M. McClellan, Bharat Thyagarajan, Myron D. Gross, Suzanne Judd and Michael Goodman
Cancer Epidemiol Biomarkers Prev March 1 2014 (23) (3) 545-554; DOI: 10.1158/1055-9965.EPI-13-0619

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Oxidative Balance Score, Colorectal Adenoma, and Markers of Oxidative Stress and Inflammation
So Yeon J. Kong, Roberd M. Bostick, W. Dana Flanders, William M. McClellan, Bharat Thyagarajan, Myron D. Gross, Suzanne Judd and Michael Goodman
Cancer Epidemiol Biomarkers Prev March 1 2014 (23) (3) 545-554; DOI: 10.1158/1055-9965.EPI-13-0619
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