Higher cholesterol variability associated with increased incidence of CV outcomes

08/01/2018

In a large population-based cohort study, cholesterol variability was an independent predictor for the development of MI and stroke, as well as for all-cause mortality, in the general population.

Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: a nationwide population-based study
Literature - Kim MK, Han K, Kim H-S, et al. - Eur Heart J 2017;38:3560–3566

Background

Existing data from small studies suggest that a high visit-to-visit variability in cholesterol levels is an independent predictor of MACE in high-risk CAD patients [1,2]. However, the prognostic significance of cholesterol variability in the general population is unknown.

In this large population-based study of 3,656,648 individuals, the prognostic significance of increased total cholesterol (TC) variability on all-cause mortality, MI, and stroke was evaluated. For this purpose, Koreans aged ≥20 years without previous MI or stroke enrolled in the National Health Insurance System [3,4], with at least 3 TC measurements between January 1, 2002 and December 31, 2007, were followed-up for a median of 8.3 years. TC variability was calculated based on 3 indices:

  • coefficient of variation (CV)
  • standard deviation (SD)
  • variability independent of the mean (VIM = 100 x SD/Meanbeta, with beta being the regression coefficient)

The study endpoints were newly-diagnosed MI, ischemic stroke, or death.

Main results

  • Participants were divided into quartiles according to their TC variability. The mean TC levels were ~190 mg/dL in all groups, with increasing CV values in ascending quartiles (Q1: 4.25±1.36%; Q2: 7.48±0.77%; Q3: 10.38±0.97%; Q4: 16.78±4.65%).
  • The incidence rate of all-cause mortality increased stepwise with higher CV quartiles of TC variability.
  • The association between TC variability and all-cause mortality remained significant after adjustment for baseline characteristics (HR for Q2: 1.03; 95% CI: 1.00-1.05; HR for Q3: 1.08; 95% CI: 1.06-1.10; HR for Q4: 1.26; 95% CI: 1.24-1.28, as compared with Q1).
  • Similar to the outcome of all-cause mortality, an incrementally higher risk of MI and stroke was observed with higher CV quartiles compared with the lowest quartile group in all models adjusting for baseline characteristics.
  • Individuals in the CV of TC variability Q4 group had an approximately 8% higher risk of MI and 11% higher risk of stroke compared with the CV Q1 group.
  • The results were consistent when the TC variability was determined using SD and VIM, and TC variability measured by SD or VIM was an independent predictor of all-cause mortality, MI, and stroke even after full multivariable adjustment.
  • When the variability index was used as a continuous variable, a 5% increase in CV was associated with a significantly increased risk of outcomes after full multivariable adjustment (HR for all-cause mortality: 1.09; 95% CI: 1.08–1.09; HR for MI: 1.03; 95% CI: 1.02–1.04; HR for stroke: 1.03; 95% CI: 1.03-1.04).

Conclusion

In a large population-based cohort study, TC variability was an independent predictor for the development of MI and stroke, as well as for all-cause mortality in the general population. These data suggest that reducing TC variability may be of benefit in the primary prevention of CVD.

Editorial comment

In his editorial article, Bangalore [5] notes that intra-individual variability in hemodynamic factors, such as blood pressure, is a sign of life. He raises a number of open questions related to the association between cholesterol variability and clinical outcomes as studied by Kim et al. He first questions whether the association is causal or merely a bystander-effect, and does this in the context of Hill’s 9 criteria for causation [6]. Although many of the criteria are satisfied, Bangalore concludes that the causality of the relationship is far from perfect. He then discusses practical difficulties, like the lack of measures and cut-offs for cholesterol variability. He concludes: ‘Moreover, the clinical implications are not known. At present, increased variability may represent potential medication noncompliance and, if not, perhaps consideration should be given to use a high-intensity statin given data showing reduced cholesterol variability. However, it is not known if reducing cholesterol variability will indeed impact prognosis. Before any of these are incorporated into clinical practice, more studies are needed to test whether this is ‘causal’ or merely an epidemiological association.’

References

1. Bangalore S, Breazna A, DeMicco DA, et al. Visit-to-visit low density lipoprotein cholesterol variability and risk of cardiovascular outcomes: insights from the TNT trial. J Am Coll Cardiol 2015;65:1539–1548.

2. Boey E, Gay GM, Poh KK, et al. Visit-to-visit variability in LDL- and HDL-cholesterol is associated with adverse events after ST-segment elevation myocardial infarction: a 5-year follow-up study. Atherosclerosis 2016;244:86–92.

3. Yang HK, Han K, Kwon HS, et al. Obesity, metabolic health, and mortality in adults: a nationwide population based study in Korea. Sci Rep 2016;6:30329.

4. Lee J, Lee JS, Park SH, et al. Cohort profile: the National Health Insurance Service-National Sample Cohort (NHIS-NSC), South Korea. Int J Epidemiol 2017;46:e15.

5. Bangalore S. Cholesterol variability: a marker for increased risk or a risk factor? Eur Heart J 2017;38: 3567–3568.

6. Hill AB. The environment and disease: association or causation? Proc R Soc Med 1965;58:295–300.

Find this article online at Eur Heart J

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