A New Equation for Calculation of Low-Density Lipoprotein Cholesterol in Patients With Normolipidemia and/or Hypertriglyceridemia | Cardiology | JAMA Cardiology | JAMA Network
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1.
Wilson  PWF, Polonsky  TS, Miedema  MD, Khera  A, Kosinski  AS, Kuvin  JT.  Systematic review for the 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol.   Circulation. 2019;139(25):e1144-e1161. doi:10.1161/CIR.0000000000000626PubMedGoogle ScholarCrossref
2.
Friedewald  WT, Levy  RI, Fredrickson  DS.  Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.   Clin Chem. 1972;18(6):499-502. doi:10.1093/clinchem/18.6.499PubMedGoogle ScholarCrossref
3.
Miller  WG, Myers  GL, Sakurabayashi  I,  et al.  Seven direct methods for measuring HDL and LDL cholesterol compared with ultracentrifugation reference measurement procedures.   Clin Chem. 2010;56(6):977-986. doi:10.1373/clinchem.2009.142810 PubMedGoogle ScholarCrossref
4.
Langlois  MR, Chapman  MJ, Cobbaert  C,  et al; European Atherosclerosis Society (EAS) and the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Joint Consensus Initiative.  Quantifying atherogenic lipoproteins: current and future challenges in the era of personalized medicine and very low concentrations of LDL cholesterol: a consensus statement from EAS and EFLM.   Clin Chem. 2018;64(7):1006-1033. doi:10.1373/clinchem.2018.287037 PubMedGoogle ScholarCrossref
5.
Oliveira  MJA, van Deventer  HE, Bachmann  LM,  et al.  Evaluation of four different equations for calculating LDL-C with eight different direct HDL-C assays.   Clin Chim Acta. 2013;423:135-140. doi:10.1016/j.cca.2013.04.009 PubMedGoogle ScholarCrossref
6.
van Deventer  HE, Miller  WG, Myers  GL,  et al.  Non-HDL cholesterol shows improved accuracy for cardiovascular risk score classification compared to direct or calculated LDL cholesterol in a dyslipidemic population.   Clin Chem. 2011;57(3):490-501. doi:10.1373/clinchem.2010.154773 PubMedGoogle ScholarCrossref
7.
Vujovic  A, Kotur-Stevuljevic  J, Spasic  S,  et al.  Evaluation of different formulas for LDL-C calculation.   Lipids Health Dis. 2010;9(1):27. doi:10.1186/1476-511X-9-27 PubMedGoogle ScholarCrossref
8.
de Cordova  CMM, de Cordova  MM.  A new accurate, simple formula for LDL-cholesterol estimation based on directly measured blood lipids from a large cohort.   Ann Clin Biochem. 2013;50(pt 1):13-19. doi:10.1258/acb.2012.011259 PubMedGoogle ScholarCrossref
9.
Dansethakul  P, Thapanathamchai  L, Saichanma  S, Worachartcheewan  A, Pidetcha  P.  Determining a new formula for calculating low-density lipoprotein cholesterol: data mining approach.   EXCLI J. 2015;14:478-483. doi:10.17179/excli2015-162PubMedGoogle Scholar
10.
Rasouli  M, Mokhtari  H.  Calculation of LDL-cholesterol vs. direct homogenous assay.   J Clin Lab Anal. 2017;31(3):e22057. doi:10.1002/jcla.22057 PubMedGoogle Scholar
11.
Gazi  IF, Elisaf  M.  LDL-cholesterol calculation formulas in patients with or without the metabolic syndrome.   Int J Cardiol. 2007;119(3):414-415. doi:10.1016/j.ijcard.2006.07.139 PubMedGoogle ScholarCrossref
12.
Vohnout  B, Vachulová  A, Blazícek  P, Dukát  A, Fodor  G, Lietava  J.  Evaluation of alternative calculation methods for determining LDL cholesterol.   Vnitr Lek. 2008;54(10):961-964.PubMedGoogle Scholar
13.
Anandaraja  S, Narang  R, Godeswar  R, Laksmy  R, Talwar  KK.  Low-density lipoprotein cholesterol estimation by a new formula in Indian population.   Int J Cardiol. 2005;102(1):117-120. doi:10.1016/j.ijcard.2004.05.009 PubMedGoogle ScholarCrossref
14.
Puavilai  W, Laorugpongse  D, Deerochanawong  C, Muthapongthavorn  N, Srilert  P.  The accuracy in using modified Friedewald equation to calculate LDL from non-fast triglyceride: a pilot study.   J Med Assoc Thai. 2009;92(2):182-187.PubMedGoogle Scholar
15.
Saiedullah  M, Rahman  MR, Rahman  M, Khan  MAH, Begum  S.  A simple modification of Friedewald's formula to calculate low-density lipoprotein cholesterol up to serum triglyceride concentration of 1000 mg/dL.   Bang J Med Biochem. 2009;(2):62-65.Google Scholar
16.
Hattori  Y, Suzuki  M, Tsushima  M,  et al.  Development of approximate formula for LDL-chol, LDL-apo B and LDL-chol/LDL-apo B as indices of hyperapobetalipoproteinemia and small dense LDL.   Atherosclerosis. 1998;138(2):289-299. doi:10.1016/S0021-9150(98)00034-3 PubMedGoogle ScholarCrossref
17.
Rao  A, Parker  AH, el-Sheroni  NA, Babelly  MM.  Calculation of low-density lipoprotein cholesterol with use of triglyceride/cholesterol ratios in lipoproteins compared with other calculation methods.   Clin Chem. 1988;34(12):2532-2534. doi:10.1093/clinchem/34.12.2532PubMedGoogle ScholarCrossref
18.
Ahmadi  S-A, Boroumand  M-A, Gohari-Moghaddam  K, Tajik  P, Dibaj  S-M.  The impact of low serum triglyceride on LDL-cholesterol estimation.   Arch Iran Med. 2008;11(3):318-321.PubMedGoogle Scholar
19.
Chen  Y, Zhang  X, Pan  B,  et al.  A modified formula for calculating low-density lipoprotein cholesterol values.   Lipids Health Dis. 2010;9(1):52. doi:10.1186/1476-511X-9-52 PubMedGoogle ScholarCrossref
20.
DeLong  DM, DeLong  ER, Wood  PD, Lippel  K, Rifkind  BM.  A comparison of methods for the estimation of plasma low- and very low-density lipoprotein cholesterol: the Lipid Research Clinics Prevalence Study.   JAMA. 1986;256(17):2372-2377. doi:10.1001/jama.1986.03380170088024 PubMedGoogle ScholarCrossref
21.
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(19):2061-2068. doi:10.1001/jama.2013.280532 PubMedGoogle ScholarCrossref
22.
Martin  SS, Giugliano  RP, Murphy  SA,  et al.  Comparison of low-density lipoprotein cholesterol assessment by Martin/Hopkins estimation, Friedewald estimation, and preparative ultracentrifugation: insights from the FOURIER trial.   JAMA Cardiol. 2018;3(8):749-753. doi:10.1001/jamacardio.2018.1533 PubMedGoogle ScholarCrossref
23.
Chung  BH, Wilkinson  T, Geer  JC, Segrest  JP.  Preparative and quantitative isolation of plasma lipoproteins: rapid, single discontinuous density gradient ultracentrifugation in a vertical rotor.   J Lipid Res. 1980;21(3):284-291.PubMedGoogle Scholar
24.
Chaudhary  R, Garg  J, Shah  N, Sumner  A.  PCSK9 inhibitors: a new era of lipid lowering therapy.   World J Cardiol. 2017;9(2):76-91. doi:10.4330/wjc.v9.i2.76 PubMedGoogle ScholarCrossref
25.
Everett  BM, Smith  RJ, Hiatt  WR.  Reducing LDL with PCSK9 inhibitors—the clinical benefit of lipid drugs.   N Engl J Med. 2015;373(17):1588-1591. doi:10.1056/NEJMp1508120 PubMedGoogle ScholarCrossref
26.
Grundy  SM, Stone  NJ, Bailey  AL,  et al.  2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the management of blood cholesterol: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.   Circulation. 2019;139(25):e1046-e1081. doi:10.1161/CIR.0000000000000624PubMedGoogle Scholar
27.
Mudd  JO, Borlaug  BA, Johnston  PV,  et al.  Beyond low-density lipoprotein cholesterol: defining the role of low-density lipoprotein heterogeneity in coronary artery disease.   J Am Coll Cardiol. 2007;50(18):1735-1741. doi:10.1016/j.jacc.2007.07.045 PubMedGoogle ScholarCrossref
28.
Hopkins  PN, Brinton  EA, Nanjee  MN.  Hyperlipoproteinemia type 3: the forgotten phenotype.   Curr Atheroscler Rep. 2014;16(9):440. doi:10.1007/s11883-014-0440-2 PubMedGoogle ScholarCrossref
29.
Chung  BH, Segrest  JP, Ray  MJ,  et al.  Single vertical spin density gradient ultracentrifugation.   Methods Enzymol. 1986;128:181-209. doi:10.1016/0076-6879(86)28068-4 PubMedGoogle ScholarCrossref
30.
Chowaniec  Z, Skoczyńska  A.  Plasma lipid transfer proteins: the role of PLTP and CETP in atherogenesis.   Adv Clin Exp Med. 2018;27(3):429-436. doi:10.17219/acem/67968 PubMedGoogle ScholarCrossref
31.
Shen  BW, Scanu  AM, Kézdy  FJ.  Structure of human serum lipoproteins inferred from compositional analysis.   Proc Natl Acad Sci U S A. 1977;74(3):837-841. doi:10.1073/pnas.74.3.837 PubMedGoogle ScholarCrossref
32.
Goff  DC  Jr, Lloyd-Jones  DM, Bennett  G,  et al.  2013 ACC/AHA guideline on the assessment of cardiovascular risk: 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):2935-2959. doi:10.1016/j.jacc.2013.11.005 PubMedGoogle ScholarCrossref
33.
Nordestgaard  BG.  Triglyceride-rich lipoproteins and atherosclerotic cardiovascular disease: new insights from epidemiology, genetics, and biology.   Circ Res. 2016;118(4):547-563. doi:10.1161/CIRCRESAHA.115.306249 PubMedGoogle ScholarCrossref
34.
Varbo  A, Benn  M, Nordestgaard  BG.  Remnant cholesterol as a cause of ischemic heart disease: evidence, definition, measurement, atherogenicity, high risk patients, and present and future treatment.   Pharmacol Ther. 2014;141(3):358-367. doi:10.1016/j.pharmthera.2013.11.008 PubMedGoogle ScholarCrossref
35.
Cantey  EP, Wilkins  JT.  Discordance between lipoprotein particle number and cholesterol content: an update.   Curr Opin Endocrinol Diabetes Obes. 2018;25(2):130-136. doi:10.1097/MED.0000000000000389 PubMedGoogle ScholarCrossref
Original Investigation
February 26, 2020

A New Equation for Calculation of Low-Density Lipoprotein Cholesterol in Patients With Normolipidemia and/or Hypertriglyceridemia

Author Affiliations
  • 1Clinical Center, Department of Laboratory Medicine, National Institutes of Health, Bethesda, Maryland
  • 2Prism Health Dx Inc, Austin, Texas
  • 3Pacific Biomarker, Seattle, Washington
  • 4Department of Science and Technology, Laboratory Corporation of America Holdings, Burlington, North Carolina
  • 5NMR Diagnostics, Laboratory Corporation of America Holdings, Burlington, North Carolina
  • 6Cardiovascular Laboratory Medicine, Mayo Clinic, Rochester, Minnesota
  • 7Division of Clinical Core Laboratory Services, Mayo Clinic, Rochester, Minnesota
  • 8Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
JAMA Cardiol. 2020;5(5):540-548. doi:10.1001/jamacardio.2020.0013
Key Points

Question  Is it possible to provide a more accurate estimate of low-density lipoprotein cholesterol in patients with hypertriglyceridemia and/or a low level of low-density lipoprotein cholesterol?

Findings  In this decision analytical model, a new low-density lipoprotein cholesterol equation was derived that can be used to more accurately estimate the low-density lipoprotein cholesterol level in patients with plasma triglyceride levels up to 800 mg/dL and is at least equivalent or more accurate than other equations for patients with normolipidemia and a low level of low-density lipoprotein cholesterol.

Meaning  The new low-density lipoprotein cholesterol equation can be readily implemented by clinical laboratories without incurring any additional costs compared with a standard lipid panel and may improve the use of calculated low-density lipoprotein cholesterol in cardiovascular disease risk management.

Abstract

Importance  Low-density lipoprotein cholesterol (LDL-C), a key cardiovascular disease marker, is often estimated by the Friedewald or Martin equation, but calculating LDL-C is less accurate in patients with a low LDL-C level or hypertriglyceridemia (triglyceride [TG] levels ≥400 mg/dL).

Objective  To design a more accurate LDL-C equation for patients with a low LDL-C level and/or hypertriglyceridemia.

Design, Setting, and Participants  Data on LDL-C levels and other lipid measures from 8656 patients seen at the National Institutes of Health Clinical Center between January 1, 1976, and June 2, 1999, were analyzed by the β-quantification reference method (18 715 LDL-C test results) and were randomly divided into equally sized training and validation data sets. Using TG and non–high-density lipoprotein cholesterol as independent variables, multiple least squares regression was used to develop an equation for very low-density lipoprotein cholesterol, which was then used in a second equation for LDL-C. Equations were tested against the internal validation data set and multiple external data sets of either β-quantification LDL-C results (n = 28 891) or direct LDL-C test results (n = 252 888). Statistical analysis was performed from August 7, 2018, to July 18, 2019.

Main Outcomes and Measures  Concordance between calculated and measured LDL-C levels by β-quantification, as assessed by various measures of test accuracy (correlation coefficient [R2], root mean square error [RMSE], mean absolute difference [MAD]), and percentage of patients misclassified at LDL-C treatment thresholds of 70, 100, and 190 mg/dL.

Results  Compared with β-quantification, the new equation was more accurate than other LDL-C equations (slope, 0.964; RMSE = 15.2 mg/dL; R2 = 0.9648; vs Friedewald equation: slope, 1.056; RMSE = 32 mg/dL; R2 = 0.8808; vs Martin equation: slope, 0.945; RMSE = 25.7 mg/dL; R2 = 0.9022), particularly for patients with hypertriglyceridemia (MAD = 24.9 mg/dL; vs Friedewald equation: MAD = 56.4 mg/dL; vs Martin equation: MAD = 44.8 mg/dL). The new equation calculates the LDL-C level in patients with TG levels up to 800 mg/dL as accurately as the Friedewald equation does for TG levels less than 400 mg/dL and was associated with 35% fewer misclassifications when patients with hypertriglyceridemia (TG levels, 400-800 mg/dL) were categorized into different LDL-C treatment groups.

Conclusions and Relevance  The new equation can be readily implemented by clinical laboratories with no additional costs compared with the standard lipid panel. It will allow for more accurate calculation of LDL-C level in patients with low LDL-C levels and/or hypertriglyceridemia (TG levels, ≤800 mg/dL) and thus should improve the use of LDL-C level in cardiovascular disease risk management.

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