Framingham 10-Year Heart Disease Risk Calculator

What Is the Framingham Risk Score?

The Framingham Risk Score estimates the chance that someone with no history of heart disease will have a first cardiovascular event within the next ten years. It comes out of the Framingham Heart Study, which has followed residents of Framingham, Massachusetts since 1948. That study is the reason anyone says “risk factor” at all: the phrase was coined in a 1961 paper from this cohort.

This page uses the 2008 general CVD (cardiovascular disease) model published by D’Agostino and colleagues in Circulation. That paper gives two things: a simple points table meant for use at the bedside, and the sex-specific Cox regression equations underneath it. The equations are what run here, because the points table sorts every input into a band, so a systolic pressure of 139 mmHg scores identically to 130.

What counts as an event. “Cardiovascular disease” here is wider than a heart attack. It covers coronary death, myocardial infarction (heart attack), coronary insufficiency, angina, ischaemic and haemorrhagic stroke, transient ischaemic attack, peripheral artery disease and heart failure. An older Framingham score from 2001 counts only hard coronary events and is still in wide use, which is why two calculators can both say “Framingham” and disagree by roughly a factor of two. If a number here looks high next to one you have seen elsewhere, check which endpoint the other tool was counting.

What each input does

• Age. The heaviest single term in the model. It was fitted on ages 30 to 74 and published up to 79, which is the range this page accepts. Anything outside that is extrapolation, and the score drifts optimistic in the very old.
• Total cholesterol and HDL (high-density lipoprotein, the “good” cholesterol). They enter as two separate terms rather than as a ratio, and HDL carries a negative coefficient. Going from 40 to 60 mg/dL genuinely subtracts risk here.
• Systolic blood pressure, the upper number in a reading. Treated and untreated pressures use different coefficients, so being medicated at 130 mmHg scores worse than sitting at 130 mmHg without medication. That is not a quirk. The prescription itself tells the model something about what the pressure was before treatment.
• Smoking. Current smoker at the time of the exam. There is no dose term and no category for someone who quit last year.
• Diabetes. A plain yes or no.

Risk categories

The published tables stop at “under 1%” and “over 30%”, and this page stops there too. The equation itself will keep going and hand you a 99% if you feed it a bad enough profile, but the Framingham cohort held too few people at either extreme to support a number, so quoting one would be invented precision.

Worked example. A 55-year-old man, total cholesterol 220 mg/dL, HDL 45 mg/dL, systolic 130 mmHg untreated, non-smoker, no diabetes, comes out at 13.4% over ten years, which is intermediate. Drop his systolic to 120 mmHg and nothing else, and the same man reads 11.6%. A woman with that identical profile reads 7.4%.

Limitations. The cohort was almost entirely white and American. The score overestimates in some populations and underestimates in South Asian ones. It knows nothing about family history, obesity, physical activity, kidney function or inflammatory markers, and it cannot see that you started running last year. Most United States guidelines now use the 2013 pooled cohort equations for actual treatment decisions. Framingham survives because it is the number people recognise, and because it is a clean way to see which of your own inputs is doing the damage. Bring the result to a doctor rather than acting on it.