Why the study?
Does recalibration of CVD risk algorithms affect the pairwise overlap of individuals classed as high risk?
Does recalibration of CVD risk algorithms affect the pairwise overlap of individuals classed as high risk?
Recalibration of cardiovascular risk prediction models is necessary when adapting them to different populations to ensure consistent identification of high-risk individuals.
Pairwise overlap in individuals classed as high risk according to four different CVD risk algorithms, before and after recalibration. The figure is from a previously published EHJ paper which compared the performance of four risk scores using data from 86 cohort studies involved in the Emerging Risk Factors Collaboration.1 FRS, Framingham Risk Score; SCORE, Systematic Coronary Risk Evaluation (SCORE) risk models; PCE, Pooled Cohort Equations; RRS, Reynolds Risk Score.
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Pennells et al. (2023) studied this question.
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