Cardiovascular (CV) risk-assessment methods such as the Systematic Coronary Risk Evaluation (SCORE) system divide subjects into risk categories based on age, gender, cholesterol, blood pressure, and smoking: low (<5% 10 year CVD mortality risk); intermediate(5-9%): and high (>10%). Drug treatment recommendations are linked to these categories. However, risk stratification by SCORE leaves much room for improvement.
The use of non-invasive measurements of atherosclerosis, such as carotid intima media thickness (CIMT), has been suggested to improve risk assessment based on the consistent findings of increased relative risks with increasing CIMT. Yet, a recent systematic review of the role of CIMT measurements in CVD screening programs concluded that data to support a role for CIMT measurements in risk profiling, i.e., data from studies showing that for an individual a high or low CIMT measurement leads to a shift from one to another risk category and this shift is followed by different treatment consequences, are lacking.
Despite the absence of evidence on added value, increasingly commercial initiatives promote to have your CIMT measured on the premise that a CIMT measurement much better assesses an individual's future CV risk than traditional risk factors do. Solid evidence should become available to refute or support the view before efforts and costs are wasted and false feelings of security in people are created.
To assess whether a CIMT measurement helps to distinguish a high risk from a low risk subject, above and beyond the contribution of traditional risk factors, at acceptable cost.
The general aim is divided into several specific objectives:
1. Does a CIMT measurement help to distinguish a high risk from a low risk subject, on top of the information available from traditional risk factors?
2. Are there subgroups** within the general population, in which a CIMT measurement helps to distinguish a high risk from a low risk subject, on top of the information available from traditional risk factors.
** subgroups are for example, men/women, age groups, subjects with hypertension/hyperlipidemia/obesity; subjects with intermediate risks estimated by Framingham/SCORE prediction models.
When either of the above objectives is confirmative:
3. Is it cost-effective to add CIMT measurement to traditional risk assessment with cardiovascular risk factors?
Design: Individual participant data from cohort studies will be pooled into one cohort for the current study.
Study population: Cohorts based on the general population, as a CIMT measurement for risk profiling focuses specifically on subjects aged 40-75 yrs free from symptomatic CVD and diabetes mellitus. We aim at a total cohort of over 30.000 subjects with over 2000 CV events.
Measurements: Available data include risk factor levels needed to estimate the SCORE risks (age, sex, systolic pressure, smoking, total and HDL cholesterol). Participants need to have been followed for occurrence of CV events with data on type of CV event, fatal or non-fatal, date of event and date of baseline examination and all cause mortality. CIMT at baseline needed to be available.
The USE_IMT cohort data have been collected and harmonized between 2010-2012. The main publications on USE-IMT can be found at pubmed.
Requests for use of the USE-IMT data should be directed to one of the principle investigators.
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