National variation in ASCVD risk between Pooled Cohort Equations and PREVENT

<h3>Context</h3> In November 2023, the American Heart Association (AHA) released PREVENT, a new set of risk equations to calculate an individual9s risk of atherosclerotic cardiovascular disease (ASCVD). This new model creates an opportunity to examine the differences in risk estimates compared to the previous Pooled Cohort Equations (PCE). This is especially relevant for African Americans, who previously had a race-based equation under PCE and now transition to the race-agnostic PREVENT equations. <h3>Objective</h3> Determine if there are significant changes in population-level ASCVD risk when switching from the Pooled Cohort Equations to the PREVENT ASCVD equation. <h3>Study Design and Analysis</h3> This study utilized data from NHANES 2011-2019 to calculate two ASCVD risk scores for each eligible individual: one using the race-based PCE and the other using the race-agnostic PREVENT equation. Each individual was separated into clinically significant risk categories of &lt;7.5%, 7.5-10%, and &gt;10%. The number of individuals reclassified when switching from the PCE to the PREVENT equations was then calculated using provided weights to create national estimates. <h3>Setting or Dataset</h3> The study used data from the National Health and Nutrition Examination Survey (NHANES). <h3>Population Studied</h3> Participants were individuals in the NHANES dataset, covering the years 2011-2019, who met the criteria for primary prevention. <h3>Intervention/Instrument</h3> No specific intervention was applied. We recalculated ASCVD risk scores with PREVENT and compared them to the previous PCE. <h3>Outcome Measures</h3> The primary outcome was the percentage of individuals reclassified when switching from PCE to PREVENT, stratified by race. The secondary outcome was the average difference in risk scores between the two methods. <h3>Results</h3> 3,885 individuals met the criteria. The average ASCVD risk score for white individuals was 6.23% with PCE and 3.24% with PREVENT. For black individuals, it was 7.61% with PCE and 3.19% with PREVENT. When pooled into risk categories, 0.15% of white individuals were reclassified into a higher risk category and 18.47% into a lower category with PREVENT. For black individuals, 0.49% were reclassified into a higher category, and 23.1% into a lower category. <h3>Conclusions</h3> A significant number of individuals in the US, especially black individuals, will be reclassified to a lower-risk class when switching from PCE to PREVENT. This could impact prescribing and deprescribing medications for primary prevention.

Authors

Publication Details

Journal
The Annals of Family Medicine
Published
2024-11-20
DOI
https://doi.org/10.1370/afm.22.s1.6765
Primary Topic
Systemic Sclerosis and Related Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

National variation in ASCVD risk between Pooled Cohort Equations and PREVENT

Jarett Beaudoin
The Annals of Family Medicine
Systemic Sclerosis and Related Diseases
article

National variation in ASCVD risk between Pooled Cohort Equations and PREVENT

Jarett Beaudoin
article en

Abstract

<h3>Context</h3> In November 2023, the American Heart Association (AHA) released PREVENT, a new set of risk equations to calculate an individual9s risk of atherosclerotic cardiovascular disease (ASCVD). This new model creates an opportunity to examine the differences in risk estimates compared to the previous Pooled Cohort Equations (PCE). This is especially relevant for African Americans, who previously had a race-based equation under PCE and now transition to the race-agnostic PREVENT equations. <h3>Objective</h3> Determine if there are significant changes in population-level ASCVD risk when switching from the Pooled Cohort Equations to the PREVENT ASCVD equation. <h3>Study Design and Analysis</h3> This study utilized data from NHANES 2011-2019 to calculate two ASCVD risk scores for each eligible individual: one using the race-based PCE and the other using the race-agnostic PREVENT equation. Each individual was separated into clinically significant risk categories of &lt;7.5%, 7.5-10%, and &gt;10%. The number of individuals reclassified when switching from the PCE to the PREVENT equations was then calculated using provided weights to create national estimates. <h3>Setting or Dataset</h3> The study used data from the National Health and Nutrition Examination Survey (NHANES). <h3>Population Studied</h3> Participants were individuals in the NHANES dataset, covering the years 2011-2019, who met the criteria for primary prevention. <h3>Intervention/Instrument</h3> No specific intervention was applied. We recalculated ASCVD risk scores with PREVENT and compared them to the previous PCE. <h3>Outcome Measures</h3> The primary outcome was the percentage of individuals reclassified when switching from PCE to PREVENT, stratified by race. The secondary outcome was the average difference in risk scores between the two methods. <h3>Results</h3> 3,885 individuals met the criteria. The average ASCVD risk score for white individuals was 6.23% with PCE and 3.24% with PREVENT. For black individuals, it was 7.61% with PCE and 3.19% with PREVENT. When pooled into risk categories, 0.15% of white individuals were reclassified into a higher risk category and 18.47% into a lower category with PREVENT. For black individuals, 0.49% were reclassified into a higher category, and 23.1% into a lower category. <h3>Conclusions</h3> A significant number of individuals in the US, especially black individuals, will be reclassified to a lower-risk class when switching from PCE to PREVENT. This could impact prescribing and deprescribing medications for primary prevention.

The Annals of Family MedicineVol. 22(Supplement 1)
Openalex Percentile: Top 65%
Systemic Sclerosis and Related Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.