Lipid analysis in an aging population

Due to an aging U.S. population, the incidence of cardiovascular disease is rapidly increasing, with an expected rise in coronary heart disease prevalence by 43% (increase by 5 million) and an associated cost of $70 million by the year 2030 [1]. The Pooled Cohort Equations, which estimate 10-year atherosclerotic cardiovascular disease (ASCVD) risk and are fundamental to current statin, aspirin, and blood pressure prevention guidelines, are validated for patients up to 75 years old and weighted heavily by age. Among modifiable risk factors, cholesterol reduction with statins and adjunctive therapies is a major point of intervention for cardiovascular prevention in the elderly. Accurate low density lipoprotein cholesterol (LDL-C) calculation is important for this population, as discriminate cholesterol reduction has the potential to provide substantial absolute benefit in a select subset of patients [1]. The Friedewald equation [2], serving as the global standard for LDL-C calculation for several decades, was initially validated in the fasting state. The 2016 European Atherosclerosis joint consensus statement, however, has shifted to recommend non-fasting lipid testing given its convenience and accuracy at a population level [3]. Non-fasting lipid assessment also helps avoid hypoglycemic events with fasting, to which elderly patients may be more prone. Acknowledgement of the Friedewald equation’s limitations at low LDL-C, high triglycerides (TG), and the non-fasting state has prompted significant efforts to improve upon the equation. The Friedewald equation is prone to error in the non-fasting state and diseases such as diabetes due to alteration in the ratio of TG to very low density lipoprotein cholesterol (VLDL-C) [4]. The comparatively low fixed factor set by the Friedewald equation tends to overestimate VLDL-C in these contexts, leading to underestimation in LDL-C and therefore potential for undertreatment. Metabolic syndrome, which increases in prevalence with age and is associated with severe hypertriglyceridemia, has a similar effect on Friedewald estimation via displacement of TG to non-VLDL particles. Friedewald and colleagues recognized in their seminal publication that at lower LDL-C levels, small error in VLDL-C estimation might promote significant error in LDL-C estimation [2]; this was originally tolerated given Editorial