AIMS: Cardiovascular disease (CVD) risk prediction models are used in Western European countries, but less so in Eastern European countries where rates of CVD can be two to four times higher. We recalibrated the SCORE prediction model for three Eastern European countries and evaluated the impact of adding seven behavioural and psychosocial risk factors to the model. METHODS AND RESULTS: We developed and validated models using data from the prospective HAPIEE cohort study with 14 598 participants from Russia, Poland, and the Czech Republic (derivation cohort, median follow-up 7.2 years, 338 fatal CVD cases) and Estonian Biobank data with 4632 participants (validation cohort, median follow-up 8.3 years, 91 fatal CVD cases). The first model (recalibrated SCORE) used the same risk factors as in the SCORE model. The second model (HAPIEE SCORE) added education, employment, marital status, depression, body mass index, physical inactivity, and antihypertensive use. Discrimination of the original SCORE model (C-statistic 0.78 in the derivation and 0.83 in the validation cohorts) was improved in recalibrated SCORE (0.82 and 0.85) and HAPIEE SCORE (0.84 and 0.87) models. After dichotomizing risk at the clinically meaningful threshold of 5%, and when comparing the final HAPIEE SCORE model against the original SCORE model, the net reclassification improvement was 0.07 [95% confidence interval (CI) 0.02-0.11] in the derivation cohort and 0.14 (95% CI 0.04-0.25) in the validation cohort. CONCLUSION: Our recalibrated SCORE may be more appropriate than the conventional SCORE for some Eastern European populations. The addition of seven quick, non-invasive, and cheap predictors further improved prediction accuracy.

Centre for Environmental Health Monitoring National Institute of Public Health Šrobárova 48 10042 Prague Czech Republic

Centre for Non Communicable Disease Institute for Global Health University College London 30 Guilford Street London WC1N 1EH UK

Department of Applied Mathematics Computer Science and Statistics Ghent University Krijgslaan 281 S9 9000 Ghent Belgium

Department of Epidemiology and Population Studies Institute of Public Health Jagiellonian University Medical College ul Grzegórzecka 20 31531 Krakow Poland

Department of Epidemiology and Public Health University College London 1 19 Torrington Place London WC1E 7HB UK

Estonian Genome Center Institute of Genomics University of Tartu Riia 23b 51010 Tartu Estonia

Institute of Cell and Molecular Biology University of Tartu Riia 23b 51010 Tartu Estonia

Institute of Mathematics and Statistics University of Tartu Narva mnt 18 51009 Tartu Estonia

Novosibirsk State Medical University Krasny Prospect 52 630091 Novosibirsk Russia

Research Center in Epidemiology and Preventive Medicine University of Insubria Via O Rossi 9 21100 Varese Italy

Research Institute of Internal and Preventive Medicine Branch of the Institute of Cytology and Genetics SB RAS 10 Ac Lavrentieva ave 630090 Novosibirsk Russia

Eur Heart J. 2020 Sep 14;41(35):3334-3335. doi: 10.1093/eurheartj/ehaa685. PubMed

Eur Heart J. 2021 Feb 11;42(6):670. doi: 10.1093/eurheartj/ehaa875. PubMed

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