MESA Study: Track Your Plaque-Lite?

The long-awaited data analyses from the Multi-Ethnic Study of Atherosclerosis (MESA) are finally making it to press.

The MESA Study is an enormously ambitious and important study of 6800 people, 45 to 84 years old, that includes white, black, Hispanic, and Chinese participants from six communities around the U.S. (Forsyth County, NC; Northern Manhattan and the Bronx, NY; Baltimore and Baltimore County, Md; St Paul, Minn; Chicago, Ill; and Los Angeles County, California.) Participants had no history of heart disease at enrollment. All underwent a heart scan (either EBT or multi-detector heart scans) at the start. It is therefore the largest prospective study involving heart scans ever performed. It is, not unexpectedly, yielding some fascinating observations relevant to the Track Your Plaque program. The MESA study is, incidentally, funded by the non-commercial, publicly-funded National Heart, Lung, and Blood Institute and is therefore presumably free of commercial bias.

Among the most recent publications is Risk factors for the progression of coronary artery calcification in asymptomatic subjects: Results from the Multi-Ethnic Study of Atherosclerosis (MESA) In this analysis of 5700 of the MESA participants, a repeat heart scan was obtained an average of 2.4 years after the first. Conventional risk factors for heart disease were obtained at the start (see below for details under Measurement of Covariates.)

After analyzing the data and risk factors assessed, such as age, sex, race, blood pressure, body mass index (BMI), presence of diabetes, blood sugar, and family history of heart disease, two questions were asked:

1) What risk factors predict heart scan scores?

2) What risk factors predict progression (i.e., increase) in heart scan scores?

(The second question is particularly relevant to us and the Track Your Plaque experience.)

The MESA analysis showed that essentially all the risk factors assessed correlated with both the initial heart scan score, as well as the rate of progression. No surprises here.

But the most eye-opening finding was that the conventional risk factors assessed explained only 12% of the variation and progression in heart scan scores (coefficient of determination, or R squared, = 0.12.) In other words:

--Conventional risk factors like LDL cholesterol, diabetes, and excess weight explain only a tiny fraction of why someone develops coronary atherosclerotic plaque as represented by a heart scan score.

--The great majority of risk for a high heart scan score remains unexplained by conventional risk factors.

--The great majority of risk for progressive increase in heart scan scores also remains unexplained by conventional risk factors.

In light of the MESA analysis, it's no surprise that strategies like reducing LDL cholesterol with statin drugs fails to prevent most heart attacks. It's no surprise that conventional prevention programs that talk about "knowing your numbers," eating a "balanced" or low-fat diet, etc., fail miserably to prevent the vast majority of heart attacks and heart procedures .

MESA confirms what we've been saying these past few years: If you want control over coronary heart disease, you won't find it in Lipitor, a low-fat diet, and other limited conventional notions of risk. Correction of conventional risk factors like cholesterol and blood pressure are, in a word, a failure . I wouldn't even call the conventional approach Track Your Plaque-Lite. They don't even come close.

If conventional risk factors can explain only 12% of the reason behind heart disease, we've got to look elsewhere to understand why you and I develop this process.

Measurement of Covariates
Information on demographics, smoking, medical conditions, and family history was collected by questionnaire at the initial examination. Height and weight were also measured at the baseline examination, and blood was drawn for measurements, including lipids, inflammation, fasting glucose, fibrinogen, and creatinine. Resting blood pressure was measured 3 times in the seated position, and the average of the last 2 measurements was used in the analysis. Medication use was determined by questionnaire. Additionally, the participant was asked to bring to the clinic containers for all medications used during the 2 weeks before the visit. The interviewer then recorded the name of each medication, the prescribed dose, and frequency of administration from the containers.