Prognostic Value of Fasting vs. Nonfasting LDL-C Levels on Long-Term Mortality: Insight From NHANES-III

Editor’s Note: Commentary based on Doran B, Guo Y, Xu J, et al. Prognostic Value of Fasting Versus Nonfasting Low-Density Lipoprotein Cholesterol Levels on Long-Term Mortality: Insight From the National Health and Nutrition Examination Survey III (NHANES-III). Circulation 2014;130:546-53.

Background

Professional guidelines on lipid management recommend fasting before obtaining a lipid panel.1-3 However, requiring fasting may be burdensome for patients and delay adequate treatment. Therefore, Doran et al. sought to determine if there is a difference in the prognostic value of fasting versus nonfasting low-density lipoprotein cholesterol (LDL-C) in predicting all-cause and cardiovascular mortality.

Methods

The National Health and Nutrition Examination Survey III (NHANES-III) is a nationally representative cohort of individuals living in the U.S. Patients aged 18 years and older included in this database from 1988-1994 with available lipid data (n = 16,161) were classified as fasting if they had fasted for ≥8 hours. One-to-one propensity score matching yielded 4,299 pairs of fasting and nonfasting participants with similar baseline characteristics. LDL-C levels were estimated using the Friedewald formula and examined as a categorical variable: <100, ≥100–130, and ≥130 mg/dL. The primary outcome was all-cause mortality, and the secondary outcome was cardiovascular mortality, with a mean follow-up of 14 years. Prognosis according to LDL-C and fasting status, and their interaction, was examined using receiver operating curves and Cox proportional hazards regression. 

Results

The C statistic for all-cause mortality in the group of individuals who fasted prior to LDL-C estimation was 0.59 (95% CI 0.57-0.61) and was similar in those who were nonfasting (0.58; 95% CI 0.56-0.60). Testing for interaction between LDL-C categories and fasting status was not significant (Pinteraction=0.11). Results using the secondary outcome of cardiovascular mortality were similar.

Conclusion

The authors concluded that fasting and nonfasting LDL-C have similar prognostic value; therefore, professional societies should reevaluate recommendations for fasting lipids.

Commentary/Perspective

The issue of whether to obtain fasting or nonfasting lipids is directly relevant to daily worldwide clinical practice. As the authors note, nonfasting predominantly impacts triglycerides, and well-done studies have shown that nonfasting triglycerides are more strongly related to risk than fasting triglycerides.4-6 From a practical standpoint, requiring fasting lipid panels might be excessively burdensome and preclude timely evaluation and management of cardiovascular risk associated with dyslipidemia. In our own clinical practices, the authors of this review do not routinely ask our patients to take off additional time from work or time away from other activities to return for a dedicated lab visit in the fasting state. The current study reinforces our view, one apparently shared by other experts.7

So why do we not routinely mandate fasting lipid profiles in our clinics? The primary reason is that we do not use Friedewald-estimated LDL-C in isolation, we also examine the rest of the standard lipid profile, paying particular attention to non-high-density lipoprotein cholesterol (non-HDL-C) and total cholesterol (TC)/HDL-C. We sometimes obtain other tests as well, such as apolipoprotein B (apoB). The European Society of Cardiology (ESC)/European Atherosclerotic Society (EAS) and Canadian guidelines endorse these additional parameters.2,3 While the 2013 American College of Cardiology (ACC)/American Heart Association (AHA) guideline1 does not, it is more limited in scope by design, focused on therapeutics, and it will be in the purview of the next ACC/AHA guideline to comprehensively address lipid testing.

Predictably, the 2013 ACC/AHA guideline carried forward the historical approach: fasting estimation of LDL-C by the Friedewald formula. This formula, probably the most widely used and deeply ingrained in laboratory medicine, was developed using fasting samples. Triglycerides are especially impacted by nonfasting and the fundamental basis of the Friedewald formula is estimating VLDL-C from triglycerides by a fixed conversion factor. Such estimation is highly inaccurate at low LDL-C and higher triglyceride levels.8 As a partial solution, we introduced a more accurate method for LDL-C estimation, which uses an adjustable rather than fixed factor to convert triglycerides to VLDL-C, and which is not necessarily dependent on fasting status.9 The method has been validated.10

If the concern is risk prediction in a U.S. patient being considered for preventive therapies, particularly a statin, the 2013 ACC/AHA guideline9 advises that LDL-C as a single risk factor marks high risk when ≥190 mg/dl (a level suggesting a genetic dyslipidemia, like familial hypercholesterolemia). However, at LDL-C levels more commonly encountered in clinical practice, LDL-C is a weaker marker of risk, and the ACC/AHA guideline advises combining lipids (total cholesterol and HDL-C, not LDL-C) with other traditional risk factors to estimate 10-year risk. The Pooled Cohort Equations for risk estimation are mapped to myocardial infarction and stroke, not only fatal outcomes (for good reason).11 If the 10-year risk is ≥7.5% in a 40-75-year-old patient without clinical atherosclerotic cardiovascular disease or diabetes, and LDL-C is 70-189 mg/dl, then the patient falls into the 4th guideline “statin benefit group,” carrying a Class I LOE A recommendation for statin therapy, only to be prescribed after shared decision making between the clinician and patient.1 If a statin is prescribed, then the guidelines advise repeating lipids to assess for the expected % LDL-C lowering from statin therapy (30 to <50% with moderate-intensity therapy; ≥50% with high-intensity). It is rather obvious that calculating the percent reduction could be skewed by differences in fasting status and performance characteristics of the Friedewald formula from baseline to follow-up. Again, we have introduced a partial solution,9 but we also favor a broader view that extends beyond LDL-C.

References:

  1. Stone NJ, Robinson JG, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2014;63(25 Pt B):2889-2934.
  2. Catapano AL, Reiner Z, De Backer G, et al. ESC/EAS Guidelines for the management of dyslipidaemias The Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS). Atherosclerosis 2011;217:3-46.
  3. Anderson TJ, Gregoire J, Hegele RA, et al. 2012 update of the Canadian Cardiovascular Society guidelines for the diagnosis and treatment of dyslipidemia for the prevention of cardiovascular disease in the adult. Can J Cardiol 2013;29:151-167.
  4. Bansal S, Buring JE, Rifai N, Mora S, Sacks FM, Ridker PM. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. JAMA 2007;298:309-316.
  5. Nordestgaard BG, Benn M, Schnohr P, Tybjaerg-Hansen A. Nonfasting triglycerides and risk of myocardial infarction, ischemic heart disease, and death in men and women. JAMA 2007;298:299-308.
  6. Langsted A, Freiberg JJ, Tybjaerg-Hansen A, Schnohr P, Jensen GB, Nordestgaard BG. Nonfasting cholesterol and triglycerides and association with risk of myocardial infarction and total mortality: the Copenhagen City Heart Study with 31 years of follow-up. J Intern Med 2011;270:65-75.
  7. Gaziano JM. Should we fast before we measure our lipids? Arch Int Med 2012;172:1705-1706.
  8. Martin SS, Blaha MJ, Elshazly MB, et al. Friedewald-estimated versus directly measured low-density lipoprotein cholesterol and treatment implications. J Am Coll Cardiol 2013;62:732-739.
  9. Martin SS, Blaha MJ, Elshazly MB, et al. Comparison of a novel method vs the Friedewald equation for estimating low-density lipoprotein cholesterol levels from the standard lipid profile. JAMA 2013;310:2061-2068.
  10. Meeusen JW, Lueke AJ, Jaffe AS, Saenger AK. Validation of a Proposed Novel Equation for Estimating LDL Cholesterol. Clin Chem 2014 [Epub ahead of print]
  11. Czarny MJ, Martin SS, Kohli P, Metkus T, Blumenthal RS. Nonfatal outcomes in the primary prevention of atherosclerotic cardiovascular disease: is all-cause mortality really all that matters? Circ Cardiovasc Qual Outcomes 2014;7:481-485.

Clinical Topics: Diabetes and Cardiometabolic Disease, Dyslipidemia, Prevention, Lipid Metabolism, Nonstatins, Novel Agents, Primary Hyperlipidemia, Statins, Diet

Keywords: American Heart Association, Apolipoproteins B, Attention, Canada, Cardiovascular Diseases, Cholesterol, Cholesterol, LDL, Decision Making, Diabetes Mellitus, Dyslipidemias, Fasting, Fatal Outcome, Follow-Up Studies, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Hyperlipoproteinemia Type II, Lipids, Lipoproteins, HDL, Lipoproteins, LDL, Myocardial Infarction, Nutrition Surveys, Prognosis, Propensity Score, Risk, Risk Factors, Stroke, Triglycerides, United States


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