Online Calculator Allows Young Adults to See How Their 30-Year CV Risk Compares to Peers’

A new online tool based on the PREVENT equations offers detailed population-based estimates of cardiovascular risk out to 30 years in younger adults, with the predictions stratified by age and sex.

The percentiles of risk calculated in the study, published in the November 25, 2025 issue of JACC, can help patients put their cardiovascular health into perspective, say researchers.

“If you were asked to say, ‘Where would you be in 30 years?’ I don’t think any of us would have any very solid way of answering that,” senior author Sadiya S. Khan, MD (Northwestern University Feinberg School of Medicine, Chicago, IL), told TCTMD. “It’s a hard thing to think about. The percentiles help us kind of get a better idea to say: ‘Compared to other people my age, and as a woman compared to another woman my age, where do I rank on my 30-year risk and how is my heart health doing?’”

More research is needed to determine how these data can best be used clinically, she added. Most likely, just as the 75th percentile of coronary calcium scoring is used as a “red flag” for intensifying therapy, a threshold based on cardiovascular risk could be applied in the same way, said Khan.

In an accompanying editorial, Erica S. Spatz, MD (Yale School of Medicine, New Haven, CT), assesses the effectiveness of the new tool. “Theoretically, the PREVENT calculator should ignite earlier risk factor modification to prevent cardiovascular disease later in life,” she writes. “In practice, however, acting on a distant 30-year risk is difficult.”

She lists several components that clinicians need to address in informing younger people’s beliefs about health: susceptibility, severity, benefits, barriers, and self-efficacy. For example, the “optimism bias” that heart disease only happens to the elderly tends to sway them towards underestimating their own risk, which could be higher than their peers’ for a variety of reasons.

“As the field of preventive cardiology moves toward earlier intervention in younger people with elevated long-term risk, next-generation strategies that embrace implementation science and design thinking are needed to encourage adoption of health behaviors that can be sustained for decades,” Spatz says. “Peer comparison, reduction of structural barriers, integration of metrics and feedback on progress, and shifting framing to more positive agency around healthy aging may hold promise but will require iterative testing with patient and clinician feedback.”

Translating Risk

The analysis, led by Vaishnavi Krishnan, BS (Northwestern University Feinberg School of Medicine), included National Health and Nutrition Examination Survey (NHANES) data from 8,686 adults aged 30-59 years without known cardiovascular disease, representing 91 million adults. The mean ages for females and males were 44.8 and 44.2 years, respectively.

Overall, the median 30-year absolute risk of CVD was 13.1%. The researchers then reported percentile values for risks of CVD, atherosclerotic cardiovascular disease, and heart failure stratified by age and sex. Generally, absolute risk was higher for men than for women, with increases seen alongside rising age.

The researchers created an online tool where users can calculate these risk percentiles, with data displayed clearly for those who might not be familiar with the statistical terminology.

This aspect is critical for shared decision-making, commented Martha Gulati, MD (Houston Methodist DeBakey Heart and Vascular Center, TX). “Numeric literacy is very poor in the United States. Like when you give a percentage, if you say you have a 5% chance of developing heart disease in the next 10 years or 30 years, whatever you’re trying to communicate, patients do not understand,” she said.

“This way they can translate that 30-year risk more adequately,” Gulati continued. “It’s all well and good for us to understand it, but ultimately we need our patients to be able to make the changes.”

Do Patients Want This?

Not everyone feels this extended-risk data is accurate or necessary. Jenny Doust, PhD (The University of Queensland, Herston, Australia), who has previously published research showing that adding female-specific risk factors doesn’t enhance the predictability of CV risk calculators, called the study “very dubious.”

First, she told TCTMD, PREVENT is based on modeling studies, which have “fundamental flaws,” namely that they don’t account for the effects of treatment over time and can “overestimate cardiovascular events in the young.”

The original purpose of risk equations was “not to decide who’s at high risk of a cardiovascular event—that might be of interest to people—but to decide who to start treating with [blood pressure- and lipid-lowering] agents,” Doust emphasized.

The hypothesis that treating early lipid deposits in younger patients can prevent CVD long-term is “extremely interesting,” she said, “but at the moment I think it still remains a hypothesis, and we don’t actually have strong data to support it.”

Also, Doust questioned whether patients are even asking for 30-year predictions, citing prior research showing that heart-age tools aren’t good for shared decision-making regarding medical therapy. “You don’t need to estimate risk for deciding who to treat with lifestyle measures,” she said. “When the risk factors are so prevalent in the community, you should advise lifestyle measures for everyone without estimating risk.”

Khan argued that some health-minded patients are asking for more information on their long-term risk profile, and that the results don’t always need to translate to immediate initiation of medication. “These are really helpful tools, especially when we use them earlier and earlier to think about lifestyle changes that can help change this risk too,” she said. “It doesn’t always have to be a medicine.”

It’s optimistic to think that lifestyle improvements are being pushed by clinicians like they should be, according to Khan. “There’s the ‘optimal’ and then there’s the ‘what’s happening,’” she said, adding that this is where the new PREVENT tool can help as a “wake-up call.”

Khan acknowledged that many strategies exist to help improve population health. “The ultimate goal is: how do we optimize each person’s health?” she said. But to get there, tools like this will help “tailor [care] for the person in front of you and personalize it, so that it works for that person.”

Gulati, too, said she has been previously critical of risk scores but advised that the key is not to use them in “isolation.”  What’s important to remember “is that the person in front of us is the person we’re caring for,” she said, adding that she’d like to see more work done on who is actually using these kinds of tools and what clinical effect they might be having.