Cardiovascular disease (CVD) is one of the most common diseases affecting people throughout the world and second only to cancer as the most frequent cause of death in the Netherlands. Early detection of asymptomatic individuals at high risk of developing CVD events is an important goal since modification of risk and lifestyle factors (hypercholesterolaemia, hypertension, diabetes, smoking, diet, exercise) in these patients will reduce their risk of future fatal or nonfatal CVD events (coronary heart disease, cerebrovascular disease, arterial aneurysms or peripheral arterial occlusive disease). The main aim of this thesis was to investigate the feasibility and effectiveness of two different strategies to use computed tomography (CT) imaging as a tool to detect asymptomatic individuals at high risk of CVD events. First, we investigated the reproducibility and prognostic value of scoring coronary (CAC) and aortic calcifications (TAC) in routinely obtianed chest CT examinations in a clinical care population (n=14,366). We found that scoring these subclinical calcifications on semi-quantitative scale was reproducible with a weighted kappa value for inter-observer variability of 0.54-0.89. A follow-up study showed that these subclinical disease markers are strong predictors of incident CVD events in a routine clinical care population. Compared with subjects with no calcium, the adjusted risk for a CVD event was 3.7 times higher (95% CI, 2.7-5.2) among patients with severe coronary calcification (CAC score ? 6) and 2.7 times higher (95% CI, 2.0-3.7) among patients with severe aortic calcification (TAC score ? 5). These results demonstrate the feasibility of extracting prognostic information from diagnostic imaging. Second, we investigated whether scoring CAC/TAC as part of a lung cancer screening study with a low-dose, non-gated chest CT protocol could benefit patients. Reproducibility was assessed. Interscan agreement of classifying participants into the same CAC score-based risk category was good (? = 0.67). Only 6 participants (1%) were classified more than 1 risk category apart on consecutive CT scans. Next, we demonstrated that adding CAC scoring to a prediction model consiting of tradtional CVD risk factors would reclassify 1 in 3 participants at intermediate risk into higher or lower risk categories. By investigating which of the participants were already receiving preventive drug therapy, we calculated that 1 in 12 participants screened could benefit from optimized targeting of preventive risk factor treatment by applying this strategy. Finally, we showed that even in this heavy smoking population (mean numver of pack-years >40yr), quitting smoking will reduce risk of CVD events. Compared with current smokers, the HR for CVD events for former smokers was 0.65 (95% CI 0.42-0.99). We conclude that using vascular calcifications as predictors of future CVD events in either patients undergoing routine diagnostic chest CT or participants of a low-dose CT lung cancer screening trial is feasible and effective. Both examples constitute an extension of existing practices and try to define new strategies for the early detection of CVD in order to optimize primary preventive efforts of reducing the number of incident fatal and nonfatal CVD events
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.