Rethinking Cardiovascular Risk: Why the PREVENT Calculator Is Changing the Game

If you're a primary care clinician, chances are you order lipid panels more than any other lab. Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death globally, and a staggering 80% of ASCVD-related events are preventable. Prevention is our domain, but how do we best estimate risk and guide shared decision-making?

Enter the PREVENT calculator, the American Heart Association’s (AHA) updated tool for assessing cardiovascular risk in adults aged 30 to 79 without known CVD. This new model replaces the Pooled Cohort Equations (PCEs), which have been in use since 2013. Let’s explore why this shift matters and how PREVENT improves upon its predecessor.

Why Move Away from the PCE?

The PCE was groundbreaking in its time, offering a more holistic view of cardiovascular risk beyond LDL or blood pressure alone. But it had some limitations. Its scope was too narrow, focusing solely on ASCVD and ignoring risks like heart failure. It viewed race as a binary variable: African-American or White/Other, based on limited representation. And it overestimated the risk of disease, particularly in Black patients, due to the disproportionate weight of the race variable.

The 2025 AHA/ACC/SGIM Hypertension Guidelines now recommend using PREVENT over PCE, and future guidelines are expected to follow suit.

What Makes PREVENT Different?

PREVENT was developed using data from over 6–7 million individuals across diverse cohorts from 1992 to 2017 — vastly larger than the PCE’s 24,000-person sample. 

The base model inputs include:

• Age, sex

• Total and HDL cholesterol

• Systolic blood pressure

• Diabetes status

• Smoking status

• eGFR

• Use of antihypertensives or statins

• BMI

The full model adds:

• HbA1c

• Urine albumin/creatinine ratio (uACR)

• Zip code (used to calculate a Social Deprivation Index)

By replacing race with zip code, PREVENT shifts the focus from race-based proxies to neighborhood-level socioeconomic factors — an arguably more ethical and accurate approach.

How Does PREVENT Perform?

In a validation study by Kaiser Permanente Southern California involving nearly 560,000 patients, PREVENT outperformed PCE in predicting 10-year risk, especially in men and non-Hispanic Black adults. The Full model (with HbA1c, uACR, and zip code) was more accurate than the Base model. And PREVENT was more reliable among older adults, including those over the age of 80, where PCE significantly overestimated risk.

Outputs and Clinical Use

PREVENT is so much more than a statin decision aid. The score provides both 10-year and 30-year CVD risk estimates, broken down by subtype: ASCVD, heart failure, coronary heart disease, and stroke. The heart failure score can help inform discussions around blood pressure targets and management, as well as monitoring of cardiovascular, kidney, and metabolic health factors that may increase heart failure risk. When it comes to when to recommend a statin, clinicians should continue to follow the same primary prevention guidelines they usually do. 

Limitations and Considerations

While the PREVENT equation is ideal for adults aged 30–79 who do not have known CVD, it is not meant for everyone. PREVENT should not be used in patients with the following conditions:

• Known CVD

• Evidence of severe subclinical CVD (e.g., left ventricular ejection fraction <40%, coronary artery calcium ≥300)

• Positive genetic testing for a pathogenic variant or an inherited cardiovascular condition

• End-stage kidney disease

• Limited life expectancy (<1 year)

Even in the right patient populations, PREVENT isn’t perfect. Underrepresentation of Black, Hispanic, and Asian populations persists (10% or less for each of these racial/ethnic groups). It doesn’t account for all risk enhancers (e.g., apoB, Lp(a), CRP, adverse pregnancy outcomes, menopause status, or family history). And we don’t yet have guidelines to help us manage high heart failure risk scores from the PREVENT calculator. 

Still, it’s a major step forward in recognizing the cardio-kidney-metabolic spectrum — a more integrated view of cardiovascular health.

Final Takeaways

Based on the literature and ACC/AHA recommendations, we should all switch to the PREVENT score for everyday CV risk assessment. In reality, cardiovascular, metabolic, and kidney health are inseparable; metrics like BMI, A1C, EGFR, and albuminuria are all CV risk factors. And, using a patient’s zip code instead of race is a step toward more equitable and realistic modeling. When deciding when to start a statin, we can continue to use the statin cutoffs we already know. 

For more information, subscribe to Primary Care Reviews and Perspectives and listen to the podcast episode, "PREVENT vs. PCE: A Paradigm Shift in Cardiovascular Prediction."