Abstract
Persisting high levels of cardiovascular mortality in Russia present a specific case among developed countries. Application of cardiovascular risk prediction models holds great potential for primary prevention in this country. Using a unique set of cohort follow-up data from Moscow and Saint Petersburg, this study aims to test and recalibrate the Systematic Coronary Risk Evaluation (SCORE) methods for predicting CVD mortality risks in the general population. The study is based on pooled epidemiological cohort data covering the period 1975-2001. The algorithms from the SCORE project were used for the calibration of the SCORE equation for the Moscow and St. Petersburg populations (SCORE-MoSP). Age-specific 10-year cumulative cardiovascular mortality rates were estimated according to the original SCORE-High and SCORE-Low equations and compared to the estimates based on the recalibrated SCORE-MoSP model and observed CVD mortality rates. Ten-year risk prediction charts for CVD mortality were derived and compared using conventional SCORE-High and recalibrated SCORE-MoSP methods. The original SCORE-High model tends to substantially under-estimate 10-year cardiovascular mortality risk for females. The SCORE-MoSP model provided better results which were closer to the observed rates. For males, both the SCORE-High and SCORE-MoSP provided similar estimates which tend to under-estimate CVD mortality risk at younger ages. These differences are also reflected in the risk prediction charts. Using non-calibrated scoring models for Russia may lead to substantial under-estimation of cardiovascular mortality risk in some groups of individuals. Although the SCORE-MoSP provide better results for females, more complex scoring methods involving a wider range of risk factors are needed.