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CME

Epidemiology of Cardiometabolic Disease (Slides with Transcript)

  • Authors: Steven M. Haffner, MD
  • THIS ACTIVITY HAS EXPIRED FOR CREDIT
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Target Audience and Goal Statement

This activity is intended for cardiologists and internists.

Upon completion of this activity, participants should be able to:

  • Review the most recent evidence-based medicine concerning cardiometabolic disease;
  • Explain the epidemiology and risk factors in CVD;
  • Evaluate emerging clinical data on the treatment of atherosclerosis, hypertension, and diabetes;
  • Discuss how atherosclerosis, hypertension, and diabetes interact in CVD through a debate format.


Disclosures

In accordance with the Accreditation Council for Continuing Medical Education’s Standards for Commercial Support, all CME providers are required to disclose to the activity audience the relevant financial relationships of the planners, teachers, and authors involved in the development of CME content. An individual has a relevant financial relationship if he or she has a financial relationship in any amount occurring in the last 12 months with a commercial interest whose products or services are discussed in the CME activity content over which the individual has control. Relationship information appears below.

Unlabeled and Investigational Usage

The audience is advised that this continuing medical education activity may contain references to unlabeled uses of FDA-approved products or to products not approved by the FDA for use in the United States. The faculty members have been made aware of their obligation to disclose such usage.


Author(s)

  • Steven M. Haffner, MD

    Professor, Internal Medicine, Department of Medicine/Clinical Epidemiology, University of Texas Health Science Center, San Antonio, TX

    Disclosures

    Disclosure: Dr. Haffner: Speakers' Bureau: GlaxoSmithKline, Pfizer, Novartis, Merck & Co., AstraZeneca. Consultant: GlaxoSmithKline, Pfizer, Novartis, Merck & Co., AstraZeneca.

Staff Disclosure:

Vindico Medical Education: No relevant financial relationships to disclose.


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    Vindico Medical Education designates this educational activity for a maximum of 2.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

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CME

Epidemiology of Cardiometabolic Disease (Slides with Transcript)

Authors: Steven M. Haffner, MDFaculty and Disclosures
THIS ACTIVITY HAS EXPIRED FOR CREDIT

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Epidemiology of Cardiometabolic Disease

  • Steven M. Haffner, MD: Thank you very much, Dr. Smith.

  • Slide 1.

    Slide 1.

    (Enlarge Slide)
  • I am going to talk a little bit about clustering of risk factors and the metabolic syndrome. The metabolic syndrome has been welcomed by some and critiqued by others. One of the critiques of the metabolic syndrome is that there are so many definitions, and these were five from the initial two versions of the World Health Organization (WHO), the National Cholesterol Education Program (NCEP) has the most effect, the American Association of Clinical Endocrinologists (AACE) people rightfully ignore, the International Diabetes Federation (IDF) has been modified so now it looks very much like the NCEP definitions with the exception that there is a required waist circumference, and I will show you the American Heart Association (AHA), which is a likely modified NCEP definition, but now there is good agreement.

  • Slide 2.

    Slide 2.

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  • One of the problems is that the metabolic syndrome is an operational definition but there is a broader concept and the broader concept of sort of cardiometabolic risk includes visceral fat, insulin resistance, atherogenic dyslipidemia—and this goes forth to other lipoproteins, other than low-density lipoprotein (LDL). There are data on VLDL and HDL, heterogeneity as well—hypertension, glucose intolerance, fibrinolysis, and inflammation. It may not be as familiar to cardiologists but women with polycystic ovarian syndrome certainly have aspects of it, non-alcoholic fatty liver disease, and you know there are other things that are not listed like sleep apnea that share many of these characteristics.

  • Slide 3.

    Slide 3.

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  • In contrast, when the NCEP developed the metabolic syndrome definition, it was meant to be an operation definition. As a consequence, it only includes things that are commonly measured by physicians or inexpensive, it included waist. It uses simple dichotomous cutpoints rather than global risk and that is both good and bad. It is simple, and it does not include age, gender, smoking, and LDL cholesterol, and thus it is obvious it was never meant on its own to calculate absolute risk vs. global risk, it was meant as a supplement.

  • Slide 4.

    Slide 4.

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  • The metabolic syndromes one way of looking at clustering, certainly Bill Kannel with the Framingham data back to 1979 talked about clustering of high total cholesterols, diabetes, obesity and hypertension. We have been interested in this area from a slightly different way, we have been interested in the concept of an atherogenic pre-diabetic state and these are data from the San Antonio Heart Study. Prior to the onset of diabetes, people are fatter, have an unfavorable body fat dispersion, have high triglycerides, low HDLs, high blood pressure, high glucose, and insulin concentrations that are twice as high. This came out in 1990, so it was 10 years before the metabolic syndrome definitions. What is of interest is this was identical to the components of the metabolic syndrome that would develop later, so the metabolic syndrome is not a new concept, there are precursors many, many years in advance.

  • Slide 5.

    Slide 5.

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  • Another thing that is important to understand is that most of what has been written about the pre-diabetic syndrome is focused on insulin resistance. It is going to be important; you are going to hear more about this later when Steve Kahn talks. Pre-diabetics are not only insulin resistant, they have decreased insulin secretion as well. These again are data from the San Antonio Heart Study, a paper in Circulation in 1990. Over half of them have both insulin resistance and low insulin secretion. In fact, 16% of them based on median splits in and non-diabetics appeared to have an isolated insulin secretory deficit so both are potential candidates if you were thinking about intervening.

  • Slide 6.

    Slide 6.

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  • All of you know the AHA Heart Lung and Blood definition published in Circulation in 2005. What are the differences from the NCEP? One is the fasting glucose is 100 rather than 110 mg/dL. The second difference is that there is a footnote here that talks about Asian subjects having lower waist circumferences, so I think it is a little more like IDF. If you are taking drug that counts as having a low HDL, high triglyceride, or blood pressure, that was always the intention of the NCEP. It was basically an oversight when it was put together. Finally, unlike the IDF definition, it is any 3 out of 5 rather than requiring a waist circumference with 2 other disorders.

  • Slide 7.

    Slide 7.

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  • I mentioned there was controversy about this. What are the criticisms? Well, one criticism is you lose a lot of information when you have dichotomous variables. This is one paper—there are many in this area now—it is from Peter Wilson in the Framingham study in Circulation in 2005. He used cutpoints of 0, 1 to 2, it has to be below the threshold for the metabolic syndrome, 3 or more, and for CVD in both men and women. You see a nice stepwise increase in risk. You see the same for type 2 diabetes. Even if you have only 1 or 2 risk factors or components, you are at higher risk. Note that the metabolic syndrome is a stronger risk factor for diabetes than it is for cardiovascular disease. And everybody sees that loss of information with two cutpoints.

  • Slide 8.

    Slide 8.

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  • The next two slides are going to deal with a different issue. How greater a risk factor for cardiovascular disease is the metabolic syndrome? What implications are there for intensification of risk factor management in non-diabetic subjects with the metabolic syndrome? This is probably the first major paper I think that came out after NCEP and it is a paper by Lakka based on data on Kuopio, Finland. It is Scandinavia, and non-diabetics looking at cardiovascular mortality over 10 years. The green line people without the metabolic syndrome, these are men. Purple line with the metabolic syndrome, the hazard ratio is very high, it is 3.6, sort of like the Framingham data for diabetes in women. If this was really true, this would suggest that this is like a CHD risk equivalent.

  • Slide 9.

    Slide 9.

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  • What about North American data? These are some data by Kelly Hunt who worked with our group who is now in South Carolina. People who do not have diabetes in metabolic syndrome have the lowest risk, not a surprise, people with just the metabolic syndrome who do not have diabetes. Here, the hazard ratio for cardiovascular mortality is more modest, it is 2.1 in women, it is 2.0 in men. It is not different between men and women unlike the situation in diabetes. This is more like a major risk factor, hypertension or cigarette smoking and less like a CHD risk equivalent. I am going to talk about why this might have occurred.

  • Slide 10.

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  • This is a paper by Charlie Alexander, and this is looking at National Health and Nutrition Examination Survey (NHANES) data, prevalence national data, although it has limitations because it is cross-sectional. Here we are looking at all the different components of the metabolic syndrome and whether they predict CHD. They used to be in red, but then they are now in pink. I do not know if there is any gender identity issues by the person who made up the slide, but anyway, low HDL is a significant predictor of CHD, high blood pressure is a significant predictor and diabetes is, and impaired fasting glucose, triglycerides, and waist circumference are not independent predictors. What this suggests is that some risk factors are more important than others, low HDL and high blood pressure, and this is a very important critique. Note also that once you add in all these components as in most papers, the metabolic syndrome is not an important predictor and the ADA really harped on it in its critique.

    Let's go back for a minute. One of the reasons just as important is if you look at what characterizes people in North America most with the metabolic syndrome is they are obese and, here, waist circumference is not an important independent predictor of CHD. Maybe very important over a long-term basis but not over a couple of years; whereas if you look at people in Scandinavia, they tend to have very high rates of hypertension, and high blood pressure is always an important risk factor for CHD, which means that even if you have the same definition of the metabolic syndrome, if you have a different set of components, your risk of heart disease may be different and this is something that needs to be taken account.

  • Slide 11.

    Slide 11.

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  • These are some data from the San Antonia Heart Study, now looking at the metabolic syndrome in IGT predicting the incidence of diabetes over 7 years. The first thing is if you have normal glucose tolerance, and you have the metabolic syndrome, the relative risk is 4. It sounds like a pretty important risk factor. Unlike diabetologists, cardiologists are attuned to absolute risk, however, and their absolute risk is still, it's 12% over 7 years. You are not going to use a drug to prevent diabetes in people with the metabolic syndrome who have normal glucose tolerance, period. If you were going to do something, you would do behavior. What about people who have impaired glucose tolerance? So here if you do not have the metabolic syndrome, your risk is 25% over 7 years, 3%, 4% per year. You are going to do something and what you do is behavior and that will cut the risk in half and it will be 12% then. You probably will not use a drug for something that is 1.5% per year. But what if people have the metabolic syndrome and IGT? Their risk doubles again, so they have a 55% chance of developing diabetes in 7 years. Even if you did a behavioral program, and you cut it in half, you would reduced it to 25% to 30%. One of the principles that comes out of data like this DREAM study and other studies is if you were going to even consider a drug, you would only do it in high risk IGTs, so IGT plus the metabolic syndrome, IGT plus IFG, a multivariate predicting model.

  • Slide 12.

    Slide 12.

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  • Components of the metabolic syndrome differently predict the incidence of diabetes but this time they are different predictors. Here it is a high fasting glucose as far and away the most important, then obesity although high blood pressure and low HDLs tend to be somewhat important but less important.

  • Slide 13.

    Slide 13.

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  • What about studies to prevent diabetes? The first study that came out in Circulation was with pravastatin in the West of Scotland study, paper by Freedman showed a 30% reduction risk; very, very exciting. Another reason to use statins, as if we needed other reasons.

  • Slide 14.

    Slide 14.

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  • Unfortunately, the next few studies that came out—ASCOT with atorvastatin, HPS with simvastatin, and even a bigger study, the LIPID study with pravastatin—have shown no effect. So statins, it is wonderful with AR for CHD do not prevent or delay type 2 diabetes.

  • Slide 15.

    Slide 15.

    (Enlarge Slide)
  • What about post-hoc analysis for ACEs and ARBs? This does not show every study so with apologies to studies that are your favorites that I have ignored, sorry about that. There are data with captopril; there are data with ramipril. We will hear about that more, lisinopril versus chlorathalidone, ramipril in the Diabetes Reduction Assessment with Ramipril and Rosiglitazone Medication (DREAM) trial. I am going to show again next time that 's opposite direction, I think they actually added this, this was supposed to be post-hoc, ARB, losartan versus atenolol, candesartan, valsartan versus amlodipine. These data are all in the range of 15% to 30%. How good is that?

  • Slide 16.

    Slide 16.

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  • If you start to look at intention-to-treat analysis, diabetes prevention with behavior shows generally a 45% to 60% reduction. It is very impressive. What about drugs? Well, metformin and Diabetes Prevention Program (DPP) showed 31%. That is the current recommendation from ADA in diabetes care in 2006. Troglitazone showed 75% in that study, the Troglitazone In Prevention Of Diabetes (TRIPOD) study showed 55%, DREAM showed 62%. That was diabetes prevention as opposed to the treatment, so TZDs are more effective than metformin and acarbose, but that is just for diabetes, it is a different issue. What about ramipril again? Here, there was a 9% reduction, not statistically significant. It is not well understood why it is different.

  • Slide 17.

    Slide 17.

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  • This is a little bit about diabetes and it is now looking at some United Kingdom Prospective Diabetes Study (UKPDS) data. You are going to hear more about this from Steve Kahn. This is a background to the ADOPT data you are going to say is unlike something like LDL cholesterol. Hemoglobin A1Cs get worse with time, they do not remain stable. Based on these data and other data, we think it is more related to a decline in beta cell function than it is to insulin resistance. It fits in that it is a defect in insulin depletion at the beginning of diabetes.

  • Slide 18.

    Slide 18.

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  • I am going to wrap up at this point. What are the disadvantages and advantages of the metabolic syndrome? The disadvantage is you lose a lot of data by using dichotomous endpoints. The components of the metabolic syndrome differ in their ability to predict diabetes in metabolic syndrome. What about the advantage? It is operational and, therefore, if something is left out, it can be changed. You could use ALTs now in a definition of a metabolic syndrome; it is clinically useful for insulin concentrations if it becomes standardized. Few people use a multivariate metabolic, a multivariate predicting model. It encourages providers to look for other risk factors and, most important, it encourages behavioral therapy as opposed to just treating every risk factor on its own. It is actually a pretty good predictor of diabetes, as opposed to CVD. Why is that? It turns out that in diabetes, age is not an important predictor once you have impaired glucose tolerance. The problem with the metabolic syndrome predicting heart disease is age and gender in smoking.

  • Slide 19.

    Slide 19.

    (Enlarge Slide)
  • This is my last slide. How should we handle this? Certainly behavioral therapy, weight loss, and increased physical activity, you should treat existing risk factors. Should you intensify management above and beyond global risk? Perhaps, but certainly they do not all need to be CHD risk equivalent. This is controversial insulin sensitizing non-diabetics. I do not think you should do it for the metabolic syndrome alone. There are no clinical trials. You could do an oral glucose tolerance test. If you have diabetes, then obviously you can use whatever you want. If you have IGT, there are clinical trials available, although no clinical trial to date has shown a reduction in cardiovascular disease. If they have normal glucose tolerance, I think clearly you would not use an insulin sensitizer to prevent diabetes. I would like to thank you all for listening.

    Dr. Smith: Thank you, Steve. That was excellent. Let's move on to our next speaker. You have thrown down the gauntlet, Steve. I think you mentioned 3 factors, hypertension, HDL, and diabetes, and our next three speakers are going to address those. Dick Nesto is next and he is going to talk about the dyslipidemia.

  • Slide 20.

    Slide 20.

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