Abstract P367: Application of Hierarchical Cluster Analysis on Five Risk Factors Scores (RFS) to Estimate Individual Patient Risk in Case Where There is No Official Country Specific RFS: Example From Bosnia and Herzegovina

Abstract

Objective: The accuracy and applicability of various cardiovascular disease (CVD) risk calculators may not be same in different populations. Wecompared 5 RFS for CVD risk on patients from Bosnia and Herzegovina to explore relations between different RFS and estimate use of theircombination. Methods: We utilized demographic, medical history, and lipid profile data gathered from patients seen in primary care clinic in 2013. FiveRFS namely, 10 year Framingham CHD score, QRISK 2, AHA/ACC ASCVD risk score, Framingham ATP III score, and EU SCORE were calculatedusing demographic, history of diabetes and hypertension, taking any hypertension medication, and lipid profile variables. Additionally, we entered these scores as dimensions in hierarchical cluster analysis to group people based on their risk of developing CVD. Results: There were 1277 patients in thisstudy and majority (65%) were women. The mean (SD) age of the sample was 56.2 (11.4) years. Correlation between these scores are presented inTable 1. We obtained 4 clusters with significant different cluster centers. Clusters were ordered from lowest to highest risk; cluster 1 containing patients with lowest and cluster 4 with highest mean RFS. Cluster centers, which represents mean values for all the RFS are given in Table 2. Conclusion: All risk scores performed well in this population. Only EU SCORE correlated less with other RFS. Obtained clusters are more homogenous and were ableto classify patients better. This novel method of using calculated RFCs as dimensions in clustering produced very good estimates of patient’s risk ofdeveloping CVD by combining several RFS, even in a case where originally RFS were created for and from different population.