Why Risk Screening For Heart Disease Is As Good As Crystal Ball Gazing

If weather forecasts were as reliable as cardiovascular risk prediction tools, meteorologists would miss two thirds of all hurricanes, expect rain for 8 out of 10 sunny days, and fail to see the parallels to fortune telling.    

When you are older than 35 and visit your doctor, there is a good chance he will evaluate your risk of suffering a heart attack or stroke over the next 10 years. The motivation behind this risk scoring is to prevent such an event while you still can. After all, these cardiovascular diseases are the number one causes of disability and death. In Europe alone 1.8 Million people die from it every year. In fact, they die prematurely, which means at an age younger than 75. [tweet this].

That's why, at first blush, it sounds reasonable to develop risk prediction scores to help doctors identify the high-risk patient whose asymptomatic state makes him blissfully unaware of being a walking time bomb. Forewarned is forearmed, or something like that the reasoning goes. But what if the forewarning part is as reliable as a six weeks weather forecast and the forearming as effective as the wish for world peace?

As with any medical technology, risk prediction tools should be judged by their ability to improve YOUR health outcome before they are used on YOU. While the latest publication about the UK QRISK score is an upbeat evaluation of its improved performance, it fails to convince me that using these tools actually makes sense [1]. 

Let's look at the data first: 
The QRISK score was developed for the UK population, because the grand dame of risk prediction scores, the Framingham Risk Score (FRS), doesn't do so hot in northern European people. FRS was seen to over-predict the risk in the UK population by up to 50%. In an effort to do better than that, QRISK was developed. It packs a lot more variables into its score than FRS. In its latest version, QRISK includes the risk factors age, smoking status (with a 5-level differentiation), ethnicity, blood pressure, cholesterol, BMI, family history, socioeconomic status, and various disease diagnoses. An algorithm calculates your risk, expressed as a %-chance to suffer a heart attack or stroke over the next 10 years. 

In clinical practice a 20% risk is defined as the critical threshold that separates the high-risk person from those in the low-to-moderate risk categories. 20% is an entirely arbitrary number, selected simply for convenience's sake and economic reasons. Set it too high, and you identify too few at-risk people, set it too low and you have to deal with too many false positives, that is, people who you would treat for elevated risk but who will not suffer an event even if you didn't treat them. The latter is clearly a strain on limited health budgets.

Now, let's see how QRISK at a threshold of 20% risk would work for you, provided you are between 30 and 84 years old, which is the age range to which QRISK is applicable. Let's also assume you are female.  

For every 1000 women, 40 will suffer a first heart attack or stroke over the next 10 years. Of these 40 obviously high-risk, women, QRISK identifies 17 correctly. Which means the remaining 23, or 60% of all those who will suffer a heart attack or stroke, fly below the QRISK radar. But that's not the intriguing part. We get to that by looking at the group of women who are identified as high-risk. 
If the 20% risk score threshold predicts correctly, then about 20 of every 100 women identified as high-risk will suffer a first event over the next 10 years. After all, that's what a 20% risk means: Of a hundred women having the same profile, 20 will eventually suffer a first heart attack or stroke over the next 10 years. Which brings us to the really juicy part: In the population from which QRISK was developed, 16% of the high-risk women actually did suffer that predicted heart attack or stroke. 

You are forgiven if you don't immediately see, why I call this the juicy part. But think about it this way: The QRISK numbers were not plugged from an observational study, which simply observes and follows women for 10 years, without doing anything to or with them. These numbers represent women who were identified to be at high risk by the very health care system, which claims to do the risk scoring to protect them from such events in the first place. So, what happened to actually preventing those events? 16% vs. 20% doesn't sound like a terrific preventive job. 

By the way, for men the figures are very much the same. The reason why I chose women is because there is an inconsistency in the study's published tables which compare the events in two age groups - the 35-74 year old men, and the 30-80 year old men. The number of heart attacks and strokes is given as 54 and 50 for the first and second group respectively. But it can't be that there are less events in the 30-80 year range than in the 35-74 year range. Since there is no such detectable inconsistency in the numbers for women, I chose them as the example.  

Back to the risk score and a summary of its performance. First, the score misses 60% of all cases right off the bat. Second, among the correctly identified future sufferers of heart attacks and strokes, the subsequent treatment only prevents a small minority of events, which amounts to about 4% of all cases happening over the 10-year period.  If our preventive interventions were worth their salt, we should see no, or only a few, cases happening in the high-risk group. Because this is the group, which is supposed to benefit from intensive treatment and intervention. 

This public health strategy of targeting the high-risk part of the population with an intervention is appropriately called the high-risk strategy. As we have seen, it makes public health miss the majority of disease events, which it set out to prevent in the first place. So what is the alternative? It's called the population strategy. And, yes, it means targeting the entire population in an effort to reduce all people's exposure to whatever are the causes of the disease. That entails necessarily a one-size-fits-all approach to health. Which you encounter in the form of those exercise and diet recommendations preached to us from every public health pulpit. 

In theory, this strategy could potentially have a large effect on the health of the entire population, materializing as a substantial reduction in the number of heart attacks and strokes. But when you look at it from YOUR point of view, you have to invest the sizeable effort of changing your eating and exercising habits, while you'll find the benefits hardly perceivable. After all, health is when you don't feel it. A prevented disease is never perceived as such. In public health, this situation, where an individual's large perceived sacrifice yields only an imperceptibly small personal benefit, is called the prevention paradox. It's a more academic way of saying it doesn't work either.
The data are certainly there to prove my case. In my previous post I highlighted how little change in health behaviors has happened over the past 20 years. And the little change, that did happen, went mostly into the wrong direction. 

Which is why we will continue to see most of us dying, ironically, from preventable diseases: heart disease, stroke, diabetes, many cancers. Which is why I'm questioning the current clinical practice of risk scoring. After all, it costs money and time.

It's this question which has lead some researchers to suggest giving everybody above the age of 50 a so-called polypill. A pill which reduces blood pressure and cholesterol, and which delivers a low dose of aspirin. It aims at killing three birds with one stone: hypertension, hypercholesterolemia and thrombotic events, all of which are causally related to heart attack and stroke. But to me, the polypill is preventive medicine's declaration of bankruptcy.

In my next post, I will talk about this, about how preventive medicine may really work, and, most importantly, what it means to you. Practically and presently. Because we already have the tools to help you prevent your heart attack or stroke. And those tools don't go by the name of any known risk score. if you are still keen on scoring your risk, we have a tool on our website for you to do that. It also shows you, how your risk would be if all risk factors were in the green zone, or how your risk will be if you maintain your current status over the next ten years. You can play around with it here, and make a couple of other tests, too. But don't get fooled by numbers. Your greatest risk is to take those risk scores too seriously. 


1. Collins, G.S. and D.G. Altman, Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2. BMJ, 2012. 344.

Collins GS, & Altman DG (2012). Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2. BMJ (Clinical research ed.), 344 PMID: 22723603