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Original Investigation
June 10, 2024

Atherosclerotic Cardiovascular Disease Risk Estimates Using the Predicting Risk of Cardiovascular Disease Events Equations

Author Affiliations
  • 1Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
  • 2Center for Pharmaceutical Policy and Prescribing, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
  • 3Center for Health Equity Research and Promotion, Veterans Affairs (VA) Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
  • 4Associate Editor, JAMA Internal Medicine
  • 5Division of General Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
  • 6Division of General Internal Medicine, Department of Medicine, University of Michigan, Ann Arbor
  • 7Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan
JAMA Intern Med. 2024;184(8):963-970. doi:10.1001/jamainternmed.2024.1302
Key Points

Question  How do estimates of 10-year atherosclerotic cardiovascular disease (ASCVD) risk and recommendations for primary prevention statin therapy differ between the 2023 American Heart Association (AHA) Predicting Risk of Cardiovascular Disease Events (PREVENT) equations and the 2013 AHA/American College of Cardiology pooled cohort equations (PCEs)?

Findings  In this cross-sectional study of 3785 adults aged 40 to 75 years without known ASCVD weighted to be representative of the US population, use of the PREVENT equations was associated with reduced ASCVD risk estimates across age, sex, and racial groups compared with the PCEs. Based on PREVENT equations, 17.3 million adults who were previously recommended primary prevention statin therapy would no longer meet eligibility, including 4.1 million adults currently taking statins.

Meaning  Findings of this study suggest that use of the PREVENT equations could greatly reduce the number of patients eligible for primary prevention statin therapy.

Abstract

Importance  In 2023, the American Heart Association (AHA) developed the Predicting Risk of Cardiovascular Disease Events (PREVENT) equations to estimate 10-year risk of atherosclerotic cardiovascular disease (ASCVD), as an update to the 2013 pooled cohort equations (PCEs). The PREVENT equations were derived from contemporary cohorts and removed race and added variables for kidney function and statin use.

Objective  To compare national estimates of 10-year ASCVD risk using the PCEs and PREVENT equations and how these equations affect recommendations for primary prevention statin therapy.

Design, Setting, and Participants  This cross-sectional study included adults aged 40 to 75 years who participated in the National Health and Nutrition Examination Survey from 2017 to March 2020. Adults were defined as eligible for primary prevention statin use based on the 2019 AHA/American College of Cardiology guideline on the primary prevention of cardiovascular disease. Data were weighted to be nationally representative and were analyzed from December 27, 2023, to January 31, 2024.

Main Outcomes and Measures  The 10-year ASCVD risk and eligibility for primary prevention statin therapy based on PREVENT and PCE calculations.

Results  In the weighted sample of 3785 US adults (mean [SD] age, 55.7 [9.7] years; 52.5% women) without known ASCVD, 20.7% reported current statin use. The mean estimated 10-year ASCVD risk was 8.0% (95% CI, 7.6%-8.4%) using the PCEs and 4.3% (95% CI, 4.1%-4.5%) using the PREVENT equations. Across all age, sex, and racial subgroups, compared with the PCEs, the mean estimated 10-year ASCVD risk was lower using the PREVENT equations, with the largest difference for Black adults (10.9% [95% CI, 10.1%-11.7%] vs 5.1% [95% CI 4.7%-5.4%]) and individuals aged 70 to 75 years (22.8% [95% CI, 21.6%-24.1%] vs 10.2% [95% CI, 9.6%-10.8%]). The use of the PREVENT equations instead of the PCEs could reduce the number of adults meeting criteria for primary prevention statin therapy from 45.4 million (95% CI, 40.3 million-50.4 million) to 28.3 million (95% CI, 25.2 million-31.4 million). In other words, 17.3 million (95% CI, 14.8 million-19.7 million) adults recommended statins based on the PCEs would no longer be recommended statins based on PREVENT equations, including 4.1 million (95% CI, 2.8 million-5.5 million) adults currently taking statins. Based on the PREVENT equations, 44.1% (95% CI, 38.6%-49.5%) of adults eligible for primary prevention statin therapy reported currently taking statins, equating to 15.8 million (95% CI, 13.4 million-18.2 million) individuals eligible for primary prevention statins who reported not taking statins.

Conclusions and Relevance  This cross-sectional study found that use of the PREVENT equations was associated with fewer US adults being eligible for primary prevention statin therapy; however, the majority of adults eligible for receiving such therapy based on PREVENT equations did not report statin use.

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7 Comments for this article
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Questionable recommendations
Alain Efstratiou, MD |
As an interventional cardiologist who would like to continue being employed, I agree with the authors.
Making recommendations about a condition that affects millions after studying less than four thousand individuals is to my mind quite bold. Risk equations are useful but imaging is superior. If a patient would consider getting off statins, I would recommend a coronary calcium score. If the result is zero stopping therapy and repeating the test in ten years is reasonable.
CONFLICT OF INTEREST: None Reported
Enhanced Prediction of the Population at Risk of Athrothrombotic Disease: Back to Framingham
William Feeman, MD | The Bowling Green Study
The PREVENT risk predictors are not much different than those of the Framingham Heart Study (FHS). The problem with risk prediction for the FHS, Pooled Cohort Equations, and the PREVENT studies is that they treat atherothrombotic disease (ATD) risk factors as independent factors, and the FHS has clearly shown that the ATD risk factors are not independent, but rather are part of a milieu, and that risk factor interactions are key to ATD risk. Moreover it is clear that the more severe the risk factors are, the higher the risk. May I suggest that you examine my article of the above title published in EC Carduology, 7.3 (2020):1-19. This was a requested article and I did NOT pay anything to get it published.
CONFLICT OF INTEREST: None Reported
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Immaging in the prediction of the population at risk of atherothrombotic disease
William Feeman, MD | The Bowling Green Study
Dr Efstratiou is quite correct that imaging will detect atherothrombotic disease (ATD), if by that he means coronary artery CAT scanning. But at what cost?? Screening for ATD risk factors early in life with the intention of treating those who are on the fast tract to develop ATD (primordial prevention) is, in my opinion, the optimal way of preventing ATD: treat ATD risk factors to plaque stabilization/regression levels. Screening avoids the cost of imaging and risk factor treatment is the final common pathway in any event.
CONFLICT OF INTEREST: None Reported
The new risk score can't be applied to guidelines that were based on the old risk score
Christopher Cannon, MD | Brigham and Women's Hospital
Although the authors say that their new risk score would change eligibility, a huge issue with that argument is that the ACC/AHA guidelines calling for use of statins beginning at 7.5% are based on the old calculator. In fact in the clinical trials there’s benefit of statins of equal proportion when people are 5% (as assessed in the CTT analysis of low risk patients - attached). and so the 7.5% was an arbitrary cut point, using the old calculator.

If this new PREVENT risk calculator is to be used for statin eligibility, one would need to apply this new
score in the clinical trials and see down to what percent risk on their score that statin benefit is seen and then adjust the guidelines accordingly. That hasn't been done and so their notion that 17 million people are no longer eligible for statins in not evidence based but rather applying a new score to a guideline based on the old score.
CONFLICT OF INTEREST: Dr. Cannon reports in calendar years 2022 to 2024: Research Grants from: Amgen, Better Therapeutics, Boehringer-Ingelheim (BI), Novo Nordisk, and salary support from Colorado Prevention Center (CPC) Clinical Research, which gets research grant support from Amgen, Bayer, Cleerly, Esperion, Lexicon, Silence. Consulting fees from Amryt/Chiesi, Amgen, Ascendia, Biogen, BI, BMS, CSL Behring, Eli Lilly, Janssen, Lexicon, Milestone, Pfizer, Rhoshan I serve on Data and Safety Monitoring Boards for the Areteia, Novo Nordisk, ROMTherapy, Inc. and the Veterans Administration.
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Jump to the limitations section
Geoffrey Ruben, MD, MMM |
I probably am missing it, but I did not see where the authors then validated their PREVENT score. Their second sentence in the Limitations section supports this.

I can easily imagine insurance company pharmacy managers, or the many patients who resist being on statins, using this hypothetical scoring system as a way to reassure themselves there is no need for statins in a large swath of the American population - only to find a few years down the road that the PREVENT score was invalid for a a variety of potential reasons. Whats more, it looks at
first blush that the African American population would bear the brunt of the denial of statin use.
CONFLICT OF INTEREST: None Reported
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At what lipid value to begin Rx
William Feeman, MD | The Bnowling Green Study
I assume that one does not want to put statins in the drinking water and that it is a good idea to treat according to risk of atherothrombotic disease (ATD). I spoke to a number of international authorities a few years ago as to what level of ATD risk would be acceptable. No one wanted to go on record, but suggested that a 15% lifetime risk would be correct. I have a database of about 3300 patients with full lipid profiles--I can get the exact number when I get home--and I have stratified these patients by age and degree of risk factor severity. I have then done reverse Kaplan-Meier curves (time to event) and have shown that when the lipid risk factor is divided into sextiles, then the time to ATD event curves fan out into six distinct risk curves.
This was published in the Journal of Heart 2 (S2):16-35. I can go further if any one wants me to do so. Incidentally, the curves for men and women are virtually superimposable.
CONFLICT OF INTEREST: None Reported
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Refining ASCVD Risk Assessment: PREVENT Equations & the Path to Personalized Care
Yu Haichu, MD | The Affiliated Hospital of Qingdao University
To the Editor,
With great interest, we read the esteemed publication titled"Atherosclerotic Cardiovascular Disease Risk Estimates Using the Predicting Risk of Cardiovascular Disease Events Equations" by Anderson et al.1 This pivotal study marks a significant step forward in refining risk assessment methodologies for ASCVD. By introducing the PREVENT equations, the authors have successfully addressed several limitations of the previous 2013 Pooled Cohort Equations (PCEs), particularly through the removal of race as a variable and the inclusion of kidney function and statin usage. These updates acknowledge the evolving understanding of race as a social construct and the interplay between multiple health
indicators in predicting ASCVD risk.

A strength of this investigation lies in its use of the National Health and Nutrition Examination Survey (NHANES) dataset, ensuring a nationally representative sample and enhancing the generalizability of findings. The observed reduction in estimated 10-year ASCVD risk, particularly among Black adults and older adults aged 70 to 75 years, underscores the importance of refining risk models to better reflect individual patient profiles.

However, while the PREVENT equations show promise, the study's reliance on self-reported statin use and the unavailability of the Optum Data Warehouse to external researchers pose challenges to independent validation and further refinement. Moreover, the 46.9% response rate in the NHANES cycle raises questions about potential selection bias and the representativeness of the sample.

An area that merits further exploration is the impact of these updated risk predictions on actual clinical outcomes and healthcare disparities. The authors' suggestion to augment electronic health records with methods to improve data accuracy and reduce bias is commendable and underscores the need for ongoing research in this direction. Additionally, the proposal to shift from strict treatment thresholds to a model that prioritizes risk communication and shared decision-making aligns with the principles of personalized medicine.

In conclusion, Anderson et al.'s study underscores risk estimation complexities, emphasizing the need for refined prediction tools. The PREVENT equations present a promising, equitable ASCVD risk framework, necessitating thorough validation for real-world application. Further research must explore their practical impact to enhance patient care and mitigate health disparities.


Mengmeng Wang, MD
Haichu Yu, MD
Author Affiliations: Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, China (Mengmeng Wang, Haichu Yu).

Corresponding Author: Haichu Yu, MD, Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, China (haichuyu@163.com).

Conflict of Interest Disclosures: None reported.

1.Anderson TS, Wilson LM, Sussman JB. Atherosclerotic Cardiovascular Disease Risk Estimates Using the Predicting Risk of Cardiovascular Disease Events Equations. JAMA internal medicine. Jun 10 2024.
CONFLICT OF INTEREST: None Reported
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