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"Medical Journeys" is a set of clinical resources reviewed by physicians, meant for the medical team as well as the patients they serve. Each episode of this journey through a disease state contains both a physician guide and a downloadable/printable patient resource. "Medical Journeys" chart a path each step of the way for physicians and patients and provide continual resources and support, as the caregiver team navigates the course of a disease.

After screening and diagnosis of hypercholesterolemia comes the difficult part -- making decisions about how to proceed.

The goal is primary prevention of atherosclerotic cardiovascular disease (ASCVD) before myocardial infarction, stroke, angina, or death occur due to plaque buildup.

Risk Prediction Tools

Individuals at higher risk of those conditions due to various factors have lower thresholds for initiating treatment. Risk prediction tools can put the whole picture together to guide management decisions in hypercholesterolemia.

While the Framingham Heart Study led in creating risk-prediction equations, the American Heart Association/American College of Cardiology (AHA/ACC) developed what has become known as the based on data from five population-based cohorts of patients that mirror the U.S. population.

This estimation tool has emerged as the dominant risk predictor in clinical use. It factors in age, sex, race or ethnicity, smoking status, systolic and diastolic blood pressure, current antihypertensive treatment, lipid levels, and type 2 diabetes to estimate a percentage risk of ASCVD in the next 10 years as well as a lifetime ASCVD risk.

However, there are limitations to the pooled cohort equations, which don't account for lipoprotein(a), inflammatory diseases, history of pre-eclampsia, family history of early onset cardiovascular disease, or socioeconomic status, among other known risk factors, as Brian Palmisano, MD, PhD, and Joshua Knowles, MD, PhD, both of Stanford University in California, wrote in .

"Furthermore," they said, "the pooled cohort equations are only validated for middle-aged patients over the intermediate term (10 years), are not well validated in many race/ethnicities, and fail to identify those at risk of ASCVD early in life, prior to onset of risk factors ('primordial prevention')."

A handful of , like the , have also been developed to address these limitations. One recent study showed that use of the PREVENT equations -- which combine measures of cardiovascular, kidney, and metabolic health to estimate risk for myocardial infarction, stroke, and heart failure without considering race -- would reclassify 53% of U.S. adults to lower ASCVD risk categories and cut the number of candidates for statin therapy, at the cost of potentially leading to more instances of myocardial infarction and stroke. Professional societies have not yet endorsed use of risk calculators other than the pooled cohort equations.

Some studies have also supported incorporating genetics in a polygenic risk score (PRS), particularly to predict coronary heart disease. A using a genome-wide PRS suggested better prediction of incident coronary heart disease than the pooled cohort equations. However, "the most logical use of the PRS is not to see whether they outperform other risk prediction models, but rather to see whether they can refine risk prediction when used in conjunction with traditional models," as Palmisano and Knowles wrote in . Studies have shown the greatest statin and PCSK9 treatment benefit in people with the highest genetic risk category.

However promising these genetic risk scores, however, clinical use has been limited and their performance is less than ideal in populations other than the largely European ones these scores were based on.

Risk Enhancers

While statins used to be recommended uniformly for people with diabetes or inflammatory conditions like rheumatoid arthritis or HIV, these conditions now weigh on treatment decisions in the context of the presence of other risk enhancers.

Along with clinical factors, the AHA/ACC guidelines note that the high-sensitivity C-reactive protein (hs-CRP) marker of inflammation can be a risk enhancing factor to consider along with elevated lipoprotein (a), or Lp(a), and apolipoprotein B (apoB). However, that's only "if measured." A relative indication for measurement would be high triglycerides (≥200 mg/dL) in the case of apoB.

"Nevertheless, apoB measurement carries extra expense, and its measurement in some laboratories may not be reliable," the guidelines note.

U.S. guidelines support once-in-a-lifetime measurement of Lp(a) in most individuals with increased risk of ASCVD, because levels are determined genetically and don't change much. A relative indication for primary prevention measurement of Lp(a) is family history of premature ASCVD, although the guidelines note it has been proven as useful in risk prediction only for women. Notably, a recent analysis of the Women's Health Study showed that a combination of Lp(a), hsCRP, and low-density lipoprotein (LDL) cholesterol independently predicted cardiovascular disease over 30 years in women who were initially healthy.

Coronary artery calcium (CAC) has support in , but the considers the evidence insufficient to support these noninvasive scans for cardiovascular risk assessment in asymptomatic primary prevention populations. The AHA/ACC guidelines suggest CAC scoring as helpful when risk is uncertain or if statin therapy is problematic. A score of zero lowers risk, while higher scores more strongly support treatment.

Other risk enhancing factors include metabolic syndrome, chronic kidney disease, chronic inflammatory conditions, history of premature menopause, high-risk race or ethnicity (e.g., South Asian), and low ankle brachial index.

Lifestyle Impact

Identifying patients at greatest risk affords the opportunity to make changes to potentially prevent or mitigate the consequences of hypercholesterolemia for cardiovascular health. Even regarding genetic risk, an of the Malmö Diet and Cancer Study, Atherosclerosis Risk in Communities study, and Women's Health Genome Study showed that favorable lifestyle factors could offset the impact of genetic risk on coronary heart disease, and the greatest absolute reduction in 10-year coronary event rate was sustained by those at the highest genetic risk for coronary disease.

Food also makes a difference in controlling cholesterol levels, particularly saturated fat and trans fat content. The biggest source of saturated fat is animal product foods, like red meat, processed meats, and high-fat dairy products like butter and cheese. Commercial and processed baked goods and fried foods are top culprits for trans fats.

While small effects, soluble fiber binds to cholesterol in the digestive system, plant sterols and stanols also keep the body from absorbing cholesterol, and polyunsaturated fats directly lower LDL.

But rather than just avoiding specific foods, the American Heart Association recommends following a dietary pattern -- like the DASH diet or Mediterranean diet -- that emphasizes vegetables, fruits, whole grains, legumes like beans, and healthy sources of protein, like low-fat dairy products, low-fat poultry, fish, seafood, and nuts.

Exercise doesn't directly impact cholesterol levels, but tobacco use does. Nicotine and lowers high-density lipoprotein cholesterol levels, which is another reason to quit. Overweight and obesity have been linked to higher LDL cholesterol as well.

Read previous installments in this series:

Part 1: Hypercholesterolemia: A Complex System

Part 2: Consequences of Hypercholesterolemia

Part 3: Genetics of Hypercholesterolemia

Part 4: Case Study: High Lipoprotein(a) Levels in Younger Patients Are Not So Clear Cut

Part 5: The Shifting Epidemiology of Hypercholesterolemia

Part 6: Diagnosing Hypercholesterolemia

Up next: Non-Familial Hypercholesterolemia Management