CT scans may be better at predicting midlife risk

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A new study shows that CT scans are more effective in estimating the risk of heart disease during middle age compared to genetic testing. Urs Siedentop & Co/Stocksy
  • Assessing an individual’s risk of developing cardiovascular disease is essential for prevention.
  • Traditional risk markers such as blood pressure and cholesterol are not always accurate measures for predicting heart disease at an individual level.
  • Researchers are exploring new risk markers such as the coronary artery calcium score and the polygenic risk score.
  • A new study suggests that adding the coronary artery calcium score, as opposed to the polygenic risk score, to traditional risk markers may help clinicians more accurately assess individual risk of coronary heart disease in middle-aged and older adults. elderly.

On average, someone in the United States dies from cardiovascular disease (CVD) every 34 seconds.

still to World Health Organization (WHO) estimates that more than 75% of early cases of cardiovascular disease are preventable.

To minimize the risk of heart disease, it is important for clinicians to assess an individual’s risk factors, particularly for coronary heart disease (CAD). This is done using risk models that take into account many factors, including age, gender, blood pressure, cholesterol levels, diabetes and smoking.

Earlier this year, 20-year results from the Heinz Nixdorf Recall (HNR) study showed that individual risk prediction is improved by adding coronary artery calcification to the traditional risk score. However, no studies to date have directly compared coronary artery calcium and polygenic risk scores in the same cohort.

To address this knowledge gap, Northwestern University Feinberg School of Medicine researchers analyzed data on two risk scores from two cohorts of middle-aged to older adults from the United States and the Netherlands.

They compared the change in prediction of CHD risk when a coronary artery calcium score, a polygenic risk score, or both were added to a traditional risk factor-based model.

The findings were published in JAMA on May 23.

Risk models help clinicians determine whether treatments such as lipid-lowering therapy or lowering blood pressure are needed based on the level of risk of cardiovascular disease.

But these conventional risk scores do not always provide accurate estimates, and new risk markers for coronary heart disease are being explored.

One such marker is coronary artery calcium (calcium plaque in the walls of the coronary arteries), which is a strong predictor of future coronary heart disease and can be detected using computed tomography (CT).

Furthermore, to look for demonstrated that genetics play an important role in the development of coronary heart disease.

Another approach to determining a person’s risk of developing the disease is the use of polygenic risk scores, which calculate the risk of coronary heart disease based on a person’s genes.

The present study included data from two population-based observational studies involving white individuals aged 45 to 79 years who did not have coronary artery disease at baseline: the Multiethnic Atherosclerosis Study (MESA) and the Rotterdam Study (RS), conducted in the USA and the Netherlands, respectively.

Only individuals of European descent were included in the Northwestern study because of previous evidence suggesting that the polygenic risk score performs better in European populations.

Additionally, participants with missing data or those on lipid-lowering therapy at baseline were excluded, resulting in a final analysis population of 1991 MESA participants and 1217 RS participants.

Lead researcher Dr. Sadiya S. Khan, assistant professor of medicine and preventive medicine at Northwestern University, and her team assessed the risk of coronary heart disease based on traditional risk factors.

They used the 2013 ACC/AHA Pooled Cohort Equations (PCEs) to calculate the 10-year predicted risk of atherosclerotic cardiovascular disease for each participant. This risk prediction model considered factors such as age, sex, smoking, blood pressure, cholesterol levels, diabetes and treatment for hypertension.

They then assessed the risk of coronary heart disease using the coronary artery calcium score and the polygenic risk score for each participant.

In the MESA and RS studies, the occurrence of coronary heart disease events, including myocardial infarction, angina, resuscitated cardiac arrest, and death from coronary heart disease, was monitored using personal exams approximately every 18 months and annual follow-up telephone conversations.

Finally, Dr. Khan and colleagues conducted statistical analyzes to examine the association between CHD risk predictors (ECPs, coronary artery calcium score, and polygenic risk score) and the actual occurrence of CHD.

The median age was 61 years in MESA and 67 years in RS.

Results showed that both coronary artery calcium score and polygenic risk score were significantly associated with a 10-year risk of coronary heart disease: 2.60 times greater risk per standard deviation (SD) for coronary artery calcium score coronary artery and 1.43 times greater risk per increase in SD for polygenic risk score.

The researchers used a statistical measure called the C-statistic to assess the ability of the coronary artery calcium score and the polygenic risk score to predict the risk of coronary heart disease. The C statistic for the coronary artery calcium score was 0.76, indicating moderate predictive power, and for the polygenic risk score, it was 0.69, indicating slightly lower predictive power.

When the coronary artery calcium score was added to the traditional risk factors, there was a significant improvement in risk prediction (an increase in C statistic of 0.09).

However, when the polygenic risk score was added, the improvement was smaller (an increase in C statistic of 0.02). When both scores were added together, there was a greater improvement (an increase in C statistic of 0.10).

The researchers obtained similar results when they repeated the analyzes with age-stratified subgroups and long-term follow-up data from the MESA study (median 16.0 years).

doctor Joseph F. Polak, MPH, a professor of radiology at Tufts University School of Medicine who is involved in the MESA study, said he was not surprised by these results. He explained to medical news today:

“This is probably an example of what we commonly call vascular age. Basically, a person is as old as his arteries. In this case, a direct measurement of the ‘age’ of the artery trumps genetics”.

doctor Raimund Erbel, emeritus professor of medicine and cardiology at Essen University Hospital and University of Duisburg-Essen, and principal investigator of the Heinz Nixdorf Recall Study, also agreed with the conclusions of this study and described CT as “a wonderful tool for individual cardiovascular[r] risk prediction” in their comments to MNT.

When asked to comment on the implications of these findings, Dr. Erica Spatz, associate professor of cardiology and epidemiology at Yale University, said MNT that “this study validates our current approach to assessing cardiovascular risk, in which a calcium score can significantly increase or decrease a person’s cardiovascular risk, especially when that risk is greater than 7.5%.”

The Doctor. Spatz explained that “Calcium scores can enhance shared decision-making discussions about how aggressive to be with prevention, including decisions about statins and other lipid-lowering agents, LDL targets, and overall lifestyle goals.”

“Polygenic risk scores are the new kid on the block for risk stratification; they provide additional information about a person’s cardiovascular risk, but we are still trying to figure out their place in clinical practice,” added Dr. Spatz.

Dr. Karol E. Watson, PhD, professor of medicine and cardiology at the David Geffen School of Medicine at the University of California, Los Angeles, cautioned that the findings “are not definitive” as the study is limited to “a specific population” and “scores”. specific polygenic risk”.

“What this study says is that in white participants enrolled in 2 observational studies, identifying coronary artery calcium predicted future cardiac events better than ours currently available polygenic risk scores. This does not mean that the CAC [coronary artery calcium] predicts better than genetics. it just means[s] that the CAC predicted incident events better than the specific polygenic risk scores they used in these white populations”.

– Dr. Karol E. Watson, PhD, Professor of Medicine and Cardiology, UCLA


However, Dr. Bots noted that there will always be some low-risk individuals who may experience a cardiovascular event, while some high-risk individuals, such as those with high coronary calcium levels, may not.

CT scans may be better at predicting midlife risk

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