One risk assessment tool for cardiovascular disease, type 2 diabetes, and chronic kidney disease.

OBJECTIVE: Individuals at high risk for chronic cardiometabolic disease (cardiovascular disease [CVD], type 2 diabetes, and chronic kidney disease [CKD]) share many risk factors and would benefit from early intervention. We developed a nonlaboratory-based risk-assessment tool for identification of people at high cardiometabolic disease risk. RESEARCH DESIGN AND METHODS: Data of three population-based cohorts from different regions of the Netherlands were merged. Participants were 2,840 men and 3,940 women, white, aged 28-85 years, free from CVD, type 2 diabetes, and CKD diagnosis at baseline. The outcome was developing cardiometabolic disease during 7 years follow-up. RESULTS: Age, BMI, waist circumference, antihypertensive treatment, smoking, family history of myocardial infarction or stroke, and family history of diabetes were significant predictors, whereas former smoking, history of gestational diabetes, and use of lipid-lowering medication were not. The models showed acceptable calibration (Hosmer and Lemeshow statistics, P > 0.05) and discrimination (area under the receiver operating characteristic [ROC] curve 0.82 [95% CI 0.81-0.83] for women and 0.80 [0.78-0.82] for men). Discrimination of individual outcomes was lowest for diabetes (area under the ROC curve 0.70 for men and 0.73 for women) and highest for CVD mortality (0.83 for men and 0.85 for women). CONCLUSIONS: We demonstrate that a single risk stratification tool can identify people at high risk for future CVD, type 2 diabetes, and/or CKD. The present risk-assessment tool can be used for referring the highest risk individuals to health care for further (multivariable) risk assessment and may as such serve as an important part of prevention programs targeting chronic cardiometabolic disease.

Comparative effectiveness and cost-effectiveness of computed tomography screening for coronary artery calcium in asymptomatic individuals.

OBJECTIVES: The aim of this study was to assess the (cost-) effectiveness of screening asymptomatic individuals at intermediate risk of coronary heart disease (CHD) for coronary artery calcium with computed tomography (CT). BACKGROUND: Coronary artery calcium on CT improves prediction of CHD. METHODS: A Markov model was developed on the basis of the Rotterdam Study. Four strategies were evaluated: 1) current practice; 2) current prevention guidelines for cardiovascular disease; 3) CT screening for coronary calcium; and 4) statin therapy for all individuals. Asymptomatic individuals at intermediate risk of CHD were simulated over their remaining lifetime. Quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios were calculated. RESULTS: In men, CT screening was more effective and more costly than the other 3 strategies (CT vs. current practice: +0.13 QALY [95% confidence interval (CI): 0.01 to 0.26], +$4,676 [95% CI: $3,126 to $6,339]; CT vs. statin therapy: +0.04 QALY [95% CI: -0.02 to 0.13], +$1,951 [95% CI: $1,170 to $2,754]; and CT vs. current guidelines: +0.02 QALY [95% CI: -0.04 to 0.09], +$44 [95% CI: -$441 to $486]). The incremental cost-effectiveness ratio of CT calcium screening was $48,800/QALY gained. In women, CT screening was more effective and more costly than current practice (+0.13 QALY [95% CI: 0.02 to 0.28], +$4,663 [95% CI: $3,120 to $6,277]) and statin therapy (+0.03 QALY [95% CI: -0.03 to 0.12], +$2,273 [95% CI: $1,475 to $3,109]). However, implementing current guidelines was more effective compared with CT screening (+0.02 QALY [95% CI: -0.03 to 0.07]), only a little more expensive (+$297 [95% CI: -$8 to $633]), and had a lower cost per additional QALY ($33,072/QALY vs. $35,869/QALY). Sensitivity analysis demonstrated robustness of results in women but considerable uncertainty in men. CONCLUSIONS: Screening for coronary artery calcium with CT in individuals at intermediate risk of CHD is probably cost-effective in men but is unlikely to be cost-effective in women.

Burden of atherosclerosis improves the prediction of coronary heart disease but not cerebrovascular events: the Rotterdam Study.

AIMS: Since atherosclerosis is a systemic process, risk prediction would benefit from targeting multiple components of cardiovascular disease simultaneously. To this end, it is useful to examine the predictive value of non-invasive measures of atherosclerosis in various vascular beds for both coronary heart disease (CHD) and cerebrovascular disease. METHODS AND RESULTS: Between September 2003 and February 2006, 2153 asymptomatic participants (69.6±6.6 years) from the Rotterdam Study underwent a multi-detector computed tomography scan. During a median follow-up of 3.5 years, 58 CHD events (myocardial infarction and CHD death) and 52 cerebrovascular events (TIA and stroke) occurred. Participants were classified into low (<5%), intermediate (5-10%), and high (>10%) 5-year risk categories based on a refitted Framingham risk model. The model was extended by coronary, aortic arch, or carotid calcium and reclassification percentages were calculated. For the outcome CHD, the C-statistic improved from 0.693 for the Framingham refitted model to 0.743, 0.740, and 0.749 by addition of coronary, aortic arch, and carotid calcium, respectively. Reclassification was most substantial in the intermediate risk group where addition of coronary calcium reclassified 56% of persons [net reclassification improvement (NRI): 15%; P<0.01)]. Adding aortic arch calcium led to a reclassification of 32% of persons (NRI: 8%; P=0.01) and adding carotid calcium reclassified 51% (NRI: 9%; P=0.02). In contrast, calcification in any of the three vascular beds did not improve cerebrovascular risk prediction. CONCLUSION: Coronary, aortic arch, and carotid artery calcification significantly improved risk prediction of CHD but not of cerebrovascular events.

Sonographic assessment of abdominal fat distribution in infancy.

There is growing evidence that not only the total amount of fat, but also the distribution of body fat determines risks for metabolic and cardiovascular disease. Developmental studies on factors influencing body fat distribution have been hampered by a lack of appropriate techniques for measuring intraabdominal fat in early life. Sonography, which is an established method for assessing abdominal fat distribution in adults, has not yet been evaluated in infants. To adapt the sonographic measurement of abdominal fat distribution to infants and study its reliability. The Generation R study, a population-based prospective cohort study. We included 212 one- and 227 two-year old Dutch infants in the present analysis. Sixty-two infants underwent replicate measurements to assess reproducibility. We developed a standardized protocol to measure the thickness of (1) subcutaneous and (2) preperitoneal fat in the upper abdomen of infants. To this end we defined infancy specific measurement areas to quantify fat thickness. Reproducibility of fat measurements was good to excellent with intraclass correlation coefficients of 0.93-0.97 for intra-observer agreement and of 0.89-0.95 for inter-observer agreement. We observed a pronounced increase in preperitoneal fat thickness in the second year of life while subcutaneous fat thickness increased only slightly, resulting in an altered body fat distribution. Gender did not significantly influence fat distribution in the first two years of life. Our age specific protocol for the sonographic measurement of central subcutaneous and preperitoneal fat is a reproducible method that can be instrumental for investigating fat distribution in early life.

Apparent and internal validity of a Monte Carlo-Markov model for cardiovascular disease in a cohort follow-up study.

OBJECTIVE: To determine the apparent and internal validity of the Rotterdam Ischemic heart disease & Stroke Computer (RISC) model, a Monte Carlo-Markov model, designed to evaluate the impact of cardiovascular disease (CVD) risk factors and their modification on life expectancy (LE) and cardiovascular disease-free LE (DFLE) in a general population (hereinafter, these will be referred to together as (DF)LE). METHODS: The model is based on data from the Rotterdam Study, a cohort follow-up study of 6871 subjects aged 55 years and older who visited the research center for risk factor assessment at baseline (1990-1993) and completed a follow-up visit 7 years later (original cohort). The transition probabilities and risk factor trends used in the RISC model were based on data from 3501 subjects (the study cohort). To validate the RISC model, the number of simulated CVD events during 7 years' follow-up were compared with the observed number of events in the study cohort and the original cohort, respectively, and simulated (DF)LEs were compared with the (DF)LEs calculated from multistate life tables. RESULTS: Both in the study cohort and in the original cohort, the simulated distribution of CVD events was consistent with the observed number of events (CVD deaths: 7.1% v. 6.6% and 7.4% v. 7.6%, respectively; non-CVD deaths: 11.2% v. 11.5% and 12.9% v. 13.0%, respectively). The distribution of (DF)LEs estimated with the RISC model consistently encompassed the (DF)LEs calculated with multistate life tables. CONCLUSIONS: The simulated events and (DF)LE estimates from the RISC model are consistent with observed data from a cohort follow-up study.

Pharmacoeconomic evaluation of testing for angiotensin-converting enzyme genotype before starting beta-hydroxy-beta-methylglutaryl coenzyme A reductase inhibitor therapy in men.

This study aimed to assess the potential cost-effectiveness of screening men for their angiotensin-converting enzyme (ACE)-genotype before starting statin therapy. We used a combination of decision-analytic and Markov modelling techniques to evaluate the long-term incremental clinical and economic effects associated with genetic testing of men with hypercholesterolemia before starting treatment with statins. The study was performed from a health care payer perspective. We used data from the Rotterdam study, a prospective population-based cohort study in the Netherlands, which was started in 1990 and included 7983 subjects aged 55 years and older. Men treated with cholesterol-lowering drugs at baseline or with a baseline total cholesterol > or = 6.5 mmol/l were included. The ratio of difference in lifelong costs between the screening strategy and the no screening strategy to difference in life expectancy between these strategies was calculated. We also performed a cost-utility analysis. The base case was a 55-year-old man with hypercholesterolemia who was initially untreated. Several univariate sensitivity analyses were performed. All costs were discounted with an annual rate of 5%. Screening men for their ACE-genotype was the dominant strategy for the base case analysis, because the screening strategy saved money (851 Euro), but life expectancy was not changed. Screening was the dominant strategy for all age-groups in our cohort. Even in 80-year-old subjects, with the shortest life-expectancy, it was cheaper to screen than to give lifelong treatment to men with a DD genotype without success. Even if all DD subjects were treated with other (non-statin) cholesterol-lowering drugs, screening remained the cost-effective strategy. The results of the cost-utility analysis were similar. Discounting the effects with 5% per year also had no major impact on the conclusions. If other studies confirm that men with the DD genotype do not benefit from treatment with statins, screening for ACE genotype in men most likely will be a cost-effective strategy before initiating statin therapy.