Comparison of short- and long-term atherosclerotic cardiovascular disease risk assessment tools in US young adults
Abstract Body (Do not enter title and authors here): Background: In 2023, the AHA published the PREVENT equations for estimating atherosclerotic cardiovascular disease (ASCVD) risk in adults aged 30-79 years. Research Questions: In young adults aged 20-39 years, does PREVENT improve risk prediction for 10- and 30-year ASCVD compared with existing risk assessment tools recommended in the current US guidelines (i.e., Pooled Cohort Equations [PCEs] and Pencina et al. equations)? Aims: To compare the performance of PREVENT vs. PCEs in predicting 10-year ASCVD, and PREVENT vs. Pencina equations in predicting 30-year ASCVD in young adults. Methods: We analyzed data from two complementary sources: (1) pooled data from two large cohorts: Coronary Artery Risk Development in Young Adults (CARDIA) and Framingham Heart Study (FHS; including the Offspring, Third Generation, Omni 1, and Omni 2 cohorts), and (2) electronic health records from Kaiser Permanente Southern California (KPSC). We included adults aged 20-39 years without a history of ASCVD at baseline. The outcome was incident ASCVD (defined as myocardial infarction, fatal coronary heart disease, fatal and nonfatal stroke) at 10 or 30 years. Model discrimination (Harrell’s C) and mean calibration (estimated as the ratio of predicted to observed event rates) were calculated for the overall population and stratified by sex and race/ethnicity. Results: We included 7,606 young adults (mean age 29 years, 53% female, 30% Black) from the pooled cohorts, and 284,667 (mean age 32 years, 61% female, 8% Black, 46% Hispanic) from KPSC. When predicting 10-year risk, PREVENT improved discrimination in both the pooled cohort (ΔHarrell’s C=0.052; 95% CI: 0.014, 0.095) and KPSC (ΔHarrell’s C=0.039; 95% CI: 0.028, 0.049) compared with the PCEs. PREVENT had good calibration (mean calibration ranged from 0.77 to 1.54), whereas the PCEs overestimated 10-year risk (mean calibration ranged from 1.99 to 4.82). When predicting 30-year risk, discrimination was similar for PREVENT and Pencina equations, but both algorithms underestimated 30-year risk with PREVENT showing worse calibration (mean calibration 0.61). Conclusion: PREVENT improved 10-year ASCVD risk prediction in young adults compared to the PCEs but underestimated 30-year risk.
Zhang, Yiyi
( Columbia University
, Great Neck
, New York
, United States
)
Safford, Monika
( WEILL CORNELL MEDICINE
, New York
, New York
, United States
)
Colantonio, Lisandro
( UNIVERSITY OF ALABAMA AT BIRMINGHAM
, Birmiham
, Alabama
, United States
)
Rana, Jamal
( KAISER PERMANENTE
, Oakland
, California
, United States
)
Bellows, Brandon
( Columbia University
, New York
, New York
, United States
)
Moran, Andrew
( Columbia University Medical Center
, New York
, New York
, United States
)
An, Jaejin
( Kaiser Permanente
, Pasadena
, California
, United States
)
Xia, Mengying
( Columbia University
, Montclair
, New Jersey
, United States
)
Reynolds, Kristi
( KAISER PERMANENTE
, Pasadena
, California
, United States
)
Zhou, Hui
( KAISER PERMANENTE
, Pasadena
, California
, United States
)
Zhou, Mengnan
( KAISER PERMANENTE
, Pasadena
, California
, United States
)
Allen, Norrina
( NORTHWESTERN UNIVERSITY
, Chicago
, Illinois
, United States
)
Gauen, Abigail
( NORTHWESTERN UNIVERSITY
, Chicago
, Illinois
, United States
)
Petito, Lucia
( Northwestern University
, Chicago
, Illinois
, United States
)
Xanthakis, Vanessa
( BU SCHOOL OF MEDICINE
, Boston
, Massachusetts
, United States
)
Author Disclosures:
Yiyi Zhang:DO NOT have relevant financial relationships
| Monika Safford:No Answer
| Lisandro Colantonio:DO have relevant financial relationships
;
Research Funding (PI or named investigator):Amgen:Past (completed)
| Jamal Rana:DO NOT have relevant financial relationships
| Brandon Bellows:DO NOT have relevant financial relationships
| Andrew Moran:No Answer
| Jaejin An:DO NOT have relevant financial relationships
| Mengying Xia:No Answer
| Kristi Reynolds:DO have relevant financial relationships
;
Researcher:Merck Sharp & Dohme LLC:Active (exists now)
| Hui Zhou:DO NOT have relevant financial relationships
| Mengnan Zhou:No Answer
| Norrina Allen:DO NOT have relevant financial relationships
| Abigail Gauen:DO NOT have relevant financial relationships
| Lucia Petito:DO have relevant financial relationships
;
Research Funding (PI or named investigator):Omron Healthcare Co., Ltd.:Active (exists now)
| Vanessa Xanthakis:DO NOT have relevant financial relationships
Cho So Mi, Natarajan Pradeep, Rivera Rachel, Koyama Satoshi, Kim Min Seo, Honigberg Michael, Bhattacharya Romit, Paruchuri Kaavya, Allen Norrina, Hornsby Whitney