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Please use this identifier to cite or link to this item: http://140.112.115.32:8080/ir/handle/987654321/932

Title: Aflatoxin B1 Exposure, Hepatitis B Virus Infection, and Hepatocellular Carcinoma in Taiwan
Authors: Hui-Chen Wu;Qiao Wang;Hwai-I Yang;Habibul Ahsan;Wei-Yann Tsai;Li-Yu Wang;Shu-Yuan Chen;Chien-Jen Chen;Regina M. Santella
Contributors: 醫學系
Date: 2009-03-01
Issue Date: 2012-02-14 15:01:43 (UTC+8)
Abstract: To evaluate the role of aflatoxin B1 (AFB1) exposure on risk of hepatocellular carcinoma (HCC), a case-control study nested within a community-based cohort was conducted. Baseline blood and urine samples were used to determine the level of AFB1-albumin adducts and urinary AFB1 metabolites. Conditional logistic regression analysis was used to calculate odds ratios (OR) and 95% confidence intervals (95% CI) to assess the effect of AFB1 exposure on risk of HCC. The adjusted ORs (95% CIs) were 1.54 (1.01-2.36) and 1.76 (1.18-2.58), respectively, for those with AFB1-albumin adducts and urinary AFB1 metabolite levels above the mean compared with those with levels below the mean. When compared with subjects in the lowest quartile of urinary AFB1 metabolites, there was an increase in risk of HCC, with adjusted ORs (95% CIs) of 0.57 (0.14-2.43), 1.43 (0.32-6.42), and 4.91 (1.18-20.48; Ptrend = 0.02), respectively, among noncarriers of hepatitis B virus (HBV) infection. The adjusted OR (95% CI) was 7.49 (5.13-10.93) for carriers of hepatitis B surface antigen compared with noncarriers, regardless of AFB1 status. The ORs (95% CI) were 10.38 (5.73-18.82) and 15.13 (7.83-29.25) for carriers of hepatitis B surface antigens with levels of AFB1-albumin adducts and urinary AFB1 metabolites above the mean, respectively. The combined effect of aflatoxin exposure and HBV infection did not differ by duration of follow-up. Consistent with our previous study with fewer subjects, these data show that AFB1 exposure is a risk factor for HCC risk. However, in this larger study, the effect of combined AFB1 exposure and HBV infection is more consistent with an additive than a multiplicative model. (Cancer Epidemiol Biomarkers Prev 2009;18(3):846–53)
Relation: Cancer Epidemiology Biomarkers Prevention, 18(3), 846-893. doi:10.1158/1055-9965.EPI-08-0697
https://doi.org/10.1158/1055-9965.EPI-08-0697
Appears in Collections:[醫學系] 期刊論文

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