Risk estimation for the primary prevention of cardiovascular disease: considerations for appropriate risk prediction model selection

Kim Robin van Daalen, Dudan Zhang, Stephen Kaptoge, Ellie Paige, Emanuele Di Angelantonio, Lisa Pennells*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

13 Citations (Scopus)

Abstract

Cardiovascular diseases remain the number one cause of death globally. Cardiovascular disease risk scores are an integral tool in primary prevention, being used to identify individuals at the highest risk and guide the assignment of preventive interventions. Available risk scores differ substantially in terms of the population sample data sources used for their derivation and, consequently, in the absolute risks they assign to individuals. Differences in cardiovascular disease epidemiology between the populations contributing to the development of risk scores, and the target populations in which they are applied, can result in overestimation or underestimation of cardiovascular disease risks for individuals, and poorly informed clinical decisions. Given the wide plethora of cardiovascular disease risk scores available, identification of an appropriate risk score for a target population can be challenging. This Review provides an up-to-date overview of guideline-recommended cardiovascular disease risk scores from global, regional, and national contexts, evaluates their comparative characteristics and qualities, and provides guidance on selection of an appropriate risk score.

Original languageEnglish
Pages (from-to)e1343-e1358
Number of pages16
JournalThe Lancet Global Health
Volume12
Issue number8
DOIs
Publication statusPublished - Aug 2024

Fingerprint

Dive into the research topics of 'Risk estimation for the primary prevention of cardiovascular disease: considerations for appropriate risk prediction model selection'. Together they form a unique fingerprint.

Cite this