Liao S.-F.Yang H.-I.Lee M.-H.Chen C.-J.WEN-CHUNG LEE2020-11-192020-11-1920121932-6203https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859608313&doi=10.1371%2fjournal.pone.0034779&partnerID=40&md5=3c45d53f4a8d42e28d5fed8a325774e8https://scholars.lib.ntu.edu.tw/handle/123456789/521804Development of hepatocellular carcinoma (HCC) is a multi-factorial process. Chronic infections with hepatitis B virus (HBV) and hepatitis C virus (HCV) are important risk factors of HCC. Host factors, such as alcohol drinking, may also play a role. This study aims to provide a synthesis view on the development of HCC by examining multiple risk factors jointly and collectively. Causal-pie modeling technique was applied to analyze a cohort of 11,801 male residents (followed up for 15 years) in Taiwan, during which a total of 298 incident HCC cases were ascertained. The rate ratios adjusted by age were further modeled by an additive Poisson regression. Population attributable fractions (PAFs) and causal-pie weights (CPWs) were calculated. A PAF indicates the magnitude of case-load reduction under a particular intervention scenario, whereas a CPW for a particular class of causal pies represents the proportion of HCC cases attributable to that class. Using PAF we observed a chance to reduce around 60% HCC risk moving from no HBV-related intervention to the total elimination of the virus. An additional ~15% (or ~5%) reduction can be expected, if the HBV-related intervention is coupled with an HCV-related intervention (or an anti-drinking campaign). Eight classes of causal pies were found to be significant, including four dose-response classes of HBV (total CPW=52.7%), one independent-effect class of HCV (CPW=14.4%), one HBV-alcohol interaction class (CPW=4.2%), one HBV-HCV interaction class (CPW=1.7%), and one all-unknown class (CPW=27.0%). Causal-pie modeling for HCC helps clarify the relative importance of each viral and host factor, as well as their interactions. ? 2012 Liao et al.English[SDGs]SDG3adult; age distribution; aged; alcohol consumption; article; cancer incidence; causal attribution; causal pie modeling; cigarette smoking; cohort analysis; follow up; hepatitis B; hepatitis C; human; liver carcinogenesis; liver cell carcinoma; major clinical study; male; Poisson distribution; population attributable fraction; population research; risk factor; statistical analysis; statistical model; Taiwan; hepatitis B; Hepatitis B virus; hepatitis C; Hepatitis C virus; isolation and purification; liver tumor; middle aged; risk factor; Taiwan; virology; Hepatitis B virus; Hepatitis C virus; Adult; Aged; Carcinoma, Hepatocellular; Cohort Studies; Follow-Up Studies; Hepacivirus; Hepatitis B virus; Hepatitis B, Chronic; Hepatitis C; Humans; Liver Neoplasms; Male; Middle Aged; Risk Factors; Taiwanjournal article10.1371/journal.pone.0034779225060502-s2.0-84859608313