This story was originally published in the February 2026 issue of the Breakthroughs newsletter.
Recently named to the Time100 Health 2026 list, Sadiya Khan, MD, is establishing herself as a leader in preventive cardiology and calling for younger people to think about their heart health earlier in life.
As the Magerstadt Professor of Cardiovascular Epidemiology, Khan studies the epidemiology of risk for cardiovascular disease (CVD). Using population-based cohorts and large electronic health record data analyses, she performs epidemiologic and mechanistic studies to enhance risk prediction and identify novel therapeutic targets for the prevention and treatment of cardiovascular disease.
Khan and her team have developed a tool to predict risk and prevent cardiovascular disease such as heart failure, stroke, arrhythmia, coronary artery disease and many other conditions. The tool called the American Heart Association Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) is a set of equations that could help healthcare clinicians more accurately identify patients who have higher CVD risk and enhance preventive care efforts. PREVENT can be thought of as an umbrella of equations from which risk calculators have been developed, including a 10-year risk assessment in broad populations, a 30-year risk assessment using percentiles and a “heart age” assessment.
The creation and implementation of these online risk calculators could help individuals and their physicians identify potential risks before problems arise in digestible and actionable ways.
Estimating CVD Risk in Broad Populations
A recent study in Circulation, led by Khan, was commissioned by the American Heart Association, to develop a risk prediction tool that can estimate cardiovascular disease (CVD) risk in adults more accurately than current models. The Pooled Cohort Equations are the current clinical standard for atherosclerotic CVD risk prediction.
“If a healthcare clinician can use models like PREVENT to predict which patients are more likely to develop CVD, including heart failure, then they can emphasize preventive lifestyle measures, such as structured exercise programs, or consider medications such as the GLP-1 receptor agonist medications earlier to potentially improve cardiovascular outcomes in their patient,” Khan said.
In a follow-up study published in Nature Medicine, the investigators utilized data from the Veterans Health Administration data warehouse representing more than 2.5 million U.S. veterans between the ages of 30 and 79 years who did not have a history of CVD or kidney failure. Patients in the cohort identified with the following race and ethnicity groups: Asian/Native Hawaiian/Pacific Islander, Hispanic, non-Hispanic Black and non-Hispanic white or as other/unknown.
Using the PREVENT equations to calculate patients’ 10-year risk of CVD, the investigators found that PREVENT performed well across racial and ethnic groups and estimated CVD risk more accurately than the current standard of care.
“If we can accurately identify patients who would benefit from earlier interventions, lifestyle changes or medication management to help prevent the onset of CVD, then we can improve patient outcomes and reduce healthcare spending costs. Accurate predictive models are an invaluable part of preventive medicine,” Khan said.
Identifying Risk at an Earlier Age
Another study published in the Journal of the American College of Cardiology used the American Heart Association PREVENT equations to calculate percentiles to help younger adults forecast and understand their risk of a heart event over the next 30 years
Khan led the design of the free tool, intended for adults aged 30 to 59. Using common health measures included in the PREVENT equations such as blood pressure, cholesterol, smoking status, diabetes history and kidney function, the tool calculates a person’s 30-year risk percentile of developing heart disease. After a person enters their information, the calculator displays their percentile rank among 100 peers of the same age and sex, along with a simple visual.
For the study, Khan’s team analyzed data from nearly 8,700 U.S. adults aged 30 to 59 who were free of cardiovascular disease when they entered the National Health and Nutrition Examination Survey. Using the PREVENT equations, the Northwestern scientists calculated each person’s risk of developing a heart attack, heart failure or stroke over the next 30 years.
While not a substitute for clinical care, the tool can encourage discussion between patients and clinicians.
“A 30-year time horizon is difficult for most people to grasp,” she said. “Therefore, we hope that being able to compare your long-term risk to others in the same age makes the information more relatable, and therefore, actionable. Presenting risk as percentiles can also be more helpful to motivate patients, because they see how their risk compares with peers, much like standardized tests or growth charts put these measurements in context.”
Calculating a Heart ‘Age’
Khan led the development of yet another way to communicate CVD risk through a person’s “heart age,” using routine health data such as blood pressure, cholesterol levels and whether a person smokes or has diabetes.
The study, published in JAMA Cardiology, outlines how the research team tested the PREVENT equations on more than 14,000 nationally representative US adults, ages 30 to 79, who participated in the National Health and Nutrition Examination Survey between 2011 and 2020. All participants had no prior history of cardiovascular disease.
On average, they found that women had a heart age of 55.4, compared to a chronological age of 51.3. For men, the age gap was wider: an average heart age of 56.7 compared to an average chronological age of 49.7.
“The important thing is that we have very good options available in our toolbox to help slow that aging down if we can identify it. This may be even more important in younger people who don’t often think about their risk for heart disease,” Khan said.
These three studies are the beginning of improving the standard of care in calculating and communicating risk and preventing CVD in younger people. These studies are the foundation from which Khan and her team are working, and the American Heart Association is now leading the integration of the PREVENT equations into the electronic medical record (EMR). The goal is to make it easier for clinicians and patients to begin an individualized conversation about risk.
“While it can sound scary to talk about risk for heart attack, stroke, or heart failure, we have more tools today at our disposal than ever before to lower that risk safely and effectively.”
Khan said the current moment is an exciting time in science and medicine, and she hopes these tools from the American Heart Association can be a conversation starter between physicians and patients.
“If we can demonstrate to a patient that down the road, they are estimated to be at higher risk for developing cardiovascular disease, whether that’s because of their predicted risk, ‘heart age’, or their percentile for risk, then we can act on this to reduce their risk by optimizing prevention strategies such as lifestyle changes or starting a medication, if indicated.”
Melissa Rohman and Ben Schamisso contributed to this story.
