Cardiovascular disease risk in patients with hepatitis C infection: Results from two general population health surveys in Canada and the United States (2007-2017).

The role of hepatitis C virus (HCV) infection in increasing the risk of cardiovascular disease (CVD) is controversial. The objective of the present study is to estimate the 10-year risk of CVD in HCV- positive subjects and describe their profile of cardiometabolic risk markers compared to HCV-negative subjects. We conducted a cross-sectional study to estimate 10-year CVD risk, calculated using the Framingham Risk Score (FRS), in participants from the Canadian Health Measures Survey (CHMS; 2007-2015, n = 10,115) and the US-National Health and Nutrition Examination Survey (NHANES; 2007-2016, n = 16,668). Subjects included in our analysis were aged 30 to 74 years with no prior history of CVD. FRS estimates, sociodemographic and cardiometabolic risk factors were compared between HCV- positive and -negative subjects in the two surveys. HCV-positive subjects had a distinct sociodemographic profile compared to their HCV-negative counterparts. Cardiometabolic risk factors, inflammatory markers and serum levels of micronutrients were comparable between the two survey populations, both in HCV-positive and -negative subjects. The average FRS in HCV-positive patients was in the range of "intermediate" 10-year CVD risk (i.e., 10-20%) and was significantly higher (P<0.01) than their HCV-negative counterparts who were within the "low" 10-year CVD risk range (i.e., ≤10%). Using a multivariable linear regression model adjusted for ethnicity, number of metabolic syndrome components and BMI, HCV infection was significantly associated with a 2.5-3.5% absolute risk increase of 10-year CVD (P<0.01). The results of the present study suggest a potential association between HCV infection and risk of subclinical and clinical CVD. The expansion of anti-HCV therapy may also contribute to reduced CVD risk and burden in patients with chronic HCV infection and should be explored further in other datasets and population modelling studies.