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JOURNAL ARTICLE
MULTICENTER STUDY
OBSERVATIONAL STUDY
Rationale and design of the coronary artery calcium consortium: A multicenter cohort study.
Journal of Cardiovascular Computed Tomography 2017 January
BACKGROUND: Although coronary artery calcium (CAC) has been investigated for over two decades, there is very limited data on the association of CAC with cause of death. The CAC Consortium is a large ongoing multi-center observational cohort of individuals who underwent non-contrast cardiac-gated CAC testing and systematic, prospective, long-term follow-up for mortality with ascertainment of cause of death.
METHODS: Four participating institutions from three states within the US (California, Minnesota, and Ohio) have contributed individual-level patient data to the CAC Consortium (spanning years 1991-2010). All CAC scans were clinically indicated and physician-referred in patients without a known history of coronary heart disease. Using strict inclusion and exclusion criteria to minimize missing data and to eliminate non-dedicated CAC scans (i.e. concomitant CT angiography), a sharply defined and well-characterized cohort of 66,636 patients was assembled. Mortality status was ascertained using the Social Security Administration Death Master File and a validated algorithm. In addition, death certificates were obtained from the National Death Index and categorized using ICD (International Classification of Diseases) codes into common causes of death.
RESULTS: Mean patient age was 54 ± 11 years and the majority were male (67%). Prevalence of CVD risk factors was similar across sites and 55% had a <5% estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk. Approximately 45% had a Calcium score of 0 and 11% had an Agatston Score ≥400. Over a mean follow-up of 12 ± 4 years, there were 3158 deaths (4.15 per 1000 person-years). The majority of deaths were due to cancer (37%) and CVD (32%). Most CVD deaths were due to CHD (54%) followed by stroke (17%). In general, CAC score distributions were similar across sites, and there were similar cause of death patterns.
CONCLUSIONS: The CAC Consortium is large and highly generalizable data set that is uniquely positioned to expand the understanding of CAC as a predictor of mortality risk across the spectrum of disease states, allowing innovative modeling of the competing risks of cardiovascular and non-cardiovascular death.
METHODS: Four participating institutions from three states within the US (California, Minnesota, and Ohio) have contributed individual-level patient data to the CAC Consortium (spanning years 1991-2010). All CAC scans were clinically indicated and physician-referred in patients without a known history of coronary heart disease. Using strict inclusion and exclusion criteria to minimize missing data and to eliminate non-dedicated CAC scans (i.e. concomitant CT angiography), a sharply defined and well-characterized cohort of 66,636 patients was assembled. Mortality status was ascertained using the Social Security Administration Death Master File and a validated algorithm. In addition, death certificates were obtained from the National Death Index and categorized using ICD (International Classification of Diseases) codes into common causes of death.
RESULTS: Mean patient age was 54 ± 11 years and the majority were male (67%). Prevalence of CVD risk factors was similar across sites and 55% had a <5% estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk. Approximately 45% had a Calcium score of 0 and 11% had an Agatston Score ≥400. Over a mean follow-up of 12 ± 4 years, there were 3158 deaths (4.15 per 1000 person-years). The majority of deaths were due to cancer (37%) and CVD (32%). Most CVD deaths were due to CHD (54%) followed by stroke (17%). In general, CAC score distributions were similar across sites, and there were similar cause of death patterns.
CONCLUSIONS: The CAC Consortium is large and highly generalizable data set that is uniquely positioned to expand the understanding of CAC as a predictor of mortality risk across the spectrum of disease states, allowing innovative modeling of the competing risks of cardiovascular and non-cardiovascular death.
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