Assessments tools for risk prediction of cardiovascular diseases.

Scientific background: Cardiovascular diseases have an enormous epidemiological and economic importance. For the selection of persons with increased total cardiovascular risk for individual-targeted (e. g. drug-based) prevention interventions different risk prognosis instruments (equations, point scores and table charts) were derived from studies or databases. The transferability of these prognostic instruments on the populations not examined in these data sources as well as their comparability are not clear.

Research questions: The evaluation addresses the questions on the existence of instruments for risk prediction of cardiovascular diseases, their transferability and comparability.

Methods: A systematic literature search was performed in the medical electronic databases in April 2008 beginning from 2004 and was completed with a hand search. Publications on the prognostic instruments for cardiovascular diseases as well as publications addressing external validity and/or comparing prognostic instruments were included in the evaluation.

Results: The systematic lierature search yielded 734 hits. Three systematic reviews, 38 publications with descriptions of prognostic instruments and 29 publications with data on the validity of the prognosis instruments were identified. Most risk prognosis instruments are based on the Framingham cohort of the USA. Only the PROCAM study is completely based on the German reference population. Almost all prognostic instruments use the variables sex, age, smoking, different parameters of the lipid status and of the blood pressure. Different cardiovascular events are considered to be an end parameter in the prognosis instruments. The time span for predicted events in the studies mostly comprises ten years. Data on calibration of the prognosis instruments (a quotient of the predicted by the observed risk) are presented in nearly half of the studies on the validation, however in no study from Germany. Only single studies find the levels of calibration between 0.9 and 1.1. Many studies on the transferability of the prognosis instruments show a value of the discrimination (correct differentiation of persons with different risk levels, best value 1.0) between 0.7 and 0.8, few studies between 0.8 and 0.9 and no study over 0.9. The studies addressing the discrimination of the prognostic instruments on the German population almost always find values between 0.7 and 0.8. The comparison of the validity of different risk prognosis instruments shows a trend for a better calibration and a better discrimination for the prognosis instruments examined on the derivation and/or validation cohorts of one of the compared prognostic instruments. Comparing the prognostic instruments on other cohorts, the newly derived Framingham prognostic instruments show a better discrimination in comparison with previously derived instruments. No studies exists comparing different prognostic instruments on the German population.

Discussion: The geographic variance of the cardiovascular morbidity and mortality supposed to be the most important factor limiting the transferability of the prognostic instruments. An appropriate recalibration is considered to be an approach for the improvement of the transferability.

Conclusions: The identified instruments for the risk prediction of cardiovascular diseases are insufficiently validated on the German population. Their use can lead to false risk estimation for a single person. Therefore, the existing prognostic instruments should be used for the informed decision-making and for the therapy selection in Germany only with critical caution.