- Email: [email protected]
Reliability of low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B measurement
Journal of Clinical Lipidology (2011) 5, 264–272
Review Article
Reliability of low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B measurement John H. Contois, PhD*, G. Russell Warnick, MS, MBA, Allan D. Sniderman, MD Maine Standards Company, 765 Roosevelt Trail, Windham, ME 04062, USA (Dr. Contois); Health Diagnostics Laboratory, Richmond, VA, USA (G. R. Warnick); and Mike Rosenbloom Laboratory for Cardiovascular Research, McGill University Health Centre, Montreal, Quebec, Canada (Dr. Sniderman) KEYWORDS: Apolipoprotein B; Cardiovascular disease; HDL cholesterol; LDL cholesterol; Non-HDL cholesterol
Abstract: There is little understanding of the reliability of laboratory measurements among clinicians. Low-density lipoprotein cholesterol (LDL-C) measurement is the cornerstone of cardiovascular risk assessment and prevention, but it is fraught with error. Therefore, we have reviewed issues related to accuracy and precision for the measurement of LDL-C and the related markers non-high-density lipoprotein cholesterol (non-HDL-C) and apolipoprotein B. Despite the widespread belief that LDL-C is standardized and reproducible, available data suggest that results can vary significantly as the result of methods from different manufacturers. Similar problems with direct HDL-C assays raise concerns about the reliability of non-HDL-C measurement. The root cause of method-specific bias relates to the ambiguity in the definition of both LDL and HDL, and the heterogeneity of LDL and HDL particle size and composition. Apolipoprotein B appears to provide a more reliable alternative, but assays for it have not been as rigorously tested as direct LDL-C and HDL-C assays. Ó 2011 National Lipid Association. All rights reserved.
Introduction The trapping of apolipoprotein B (apoB) lipoprotein particles within the arterial wall is the fundamental cause of atherosclerosis, and lowering the apoB lipoprotein particle number in plasma is the most potent therapy to reduce the risk of cardiovascular events. Low-density lipoprotein cholesterol (LDL-C) has been the conventional marker in clinical practice of the apoB lipoproteins. Recently, two alternatives, apoB and non-high density lipoprotein
* Corresponding author. E-mail address: [email protected] Submitted March 7, 2011; revised May 3, 2011. Accepted for publication May 17, 2011.
cholesterol (non-HDL-C), have been proposed to be more accurate biological markers of the atherogenic risk posed by apoB lipoproteins. Attention has focused on the epidemiological and clinical trial results supporting these claims, but little attention has been paid to the analytical and preanalytical errors involved in laboratory quantification of LDL-C versus non-HDL C and apoB. Clinicians assume that laboratory results are precise and accurate, particularly those such as LDL-C, which have become integral to modern cardiovascular care. We understand that errors occur, but we know little of their frequency and magnitude. The purpose of this article, therefore, is, first, to outline the elements of error in laboratory measurement and second, to examine the impact of those errors on the performance of calculated and directly measured LDL-C and non-HDL-C.
1933-2874/$ - see front matter Ó 2011 National Lipid Association. All rights reserved. doi:10.1016/j.jacl.2011.05.004
Contois et al
Reliability of LDL-C and non-HDL-C measurement
Errors in laboratory measurement Laboratory errors can be divided into those that are preanalytical, such as those attributable to errors in obtaining and preserving the sample, or those attributable to physiological or pathological factors, and those that are truly analytical, those that relate to the actual measurement system, that is, instrument, reagent, and calibration. These analytical and preanalytical factors need to be taken into account in assessing the clinical utility and validity of one analyte versus another. Components of preanalytical variability include biological factors (age and gender), behavioral factors (diet, obesity, cigarette smoking, alcohol intake, and exercise), clinical factors (medication and disease-related), and sample collection (fasting status, anticoagulants and preservatives, hemoconcentration, and specimen storage).1 Analytical laboratory error can be divided into two components: imprecision and inaccuracy: Total analytical error 5 Error caused by imprecision 1 error caused by inaccuracy Precision refers to the reproducibility of a particular method, that is, how closely repeated measurements will agree with one another. Obviously, if the differences between replicates are large, a substantially larger or smaller number might have been reported, and there can be no confidence in any particular result. The error caused by imprecision is summarized by the coefficient of variation (CV), which is the standard deviation of repeated results divided by the average concentration. For example, a CV of 5% at a mean concentration of 100 mg/dL indicates that two thirds of the time the reported result will be between 95 and 105 mg/dL. Similarly, the 95% confidence interval, estimated as the mean 6 2 ! CV (or more correctly 1.96 ! CV) for a single measurement, is a result between 90 and 110 mg/dL. Inaccuracy, or bias, refers to a systematic difference in results between a method and the ‘‘true’’ value. Often, the true value is obtained by measurement with a reference method, a method recognized as the ‘‘gold standard.’’ Bias is the difference on average between the method used and the reference method. Examples of these errors include differences in results caused by the use of new lots of calibrators or reagents, instrument-to-instrument differences, and differences introduced by recalibrating an assay. An important component of calibration bias is error in standardization and/or traceability to a recognized reference material and/or reference method. Thus, if there is a bias of 110% between the clinical method and the reference method, all the clinical results will be 10% greater than the true value. In this case, a reported result of 105 mg/ dL would actually correspond to a true value of 95 mg/dL and, if the target were 100 mg/dL, the therapeutic dose of the statin would not need to be increased. It is important to appreciate that these two categories of errors, imprecision and inaccuracy, are independent of each
265 other and that correcting one will not correct the other. Thus, a measurement can be precise, but not accurate, and improving precision does not improve accuracy. Nevertheless, precision is a prerequisite for accuracy in measuring an individual specimen. However, a method that is precise and accurate, on average, can be inaccurate in an individual specimen because of the presence of interfering substances in the specimen. In reviewing the laboratory accuracy of the direct LDL-C methods, and the three assays used to calculate LDL-C, we will discuss the methodologies, standardization, and errors associated with each.
Errors in LDL-C LDL-C is the mass of cholesterol within LDL particles and is, currently, the cornerstone of coronary heart disease risk assessment. The NCEP Laboratory Standardization Panel and the Working Group on Lipoprotein Measurement (WGL) have described physiological, clinical, and other preanalytical factors that contribute to variability in lipid and lipoprotein levels and have established guidelines for measurement of total cholesterol, triglycerides, HDL-C, and LDL-C.2–5 The National Cholesterol Education Program (NCEP) goal for LDL-C analytical performance is a result within 12% of the true value3; or, in other words, the total measurement error (bias plus imprecision) should be within 12% of the true value. NCEP Performance goals are summarized in Table 1. In clinical practice, LDL-C is either estimated by the Friedewald formula or directly measured. The former is a calculation determined by plasma triglycerides, total cholesterol, and HDL-C and, therefore, necessarily includes the accumulated errors in all three measurements. Calculated LDL-C does not add additional expense beyond the three core measurements, but it requires a fasting sample. By contrast, direct measurement of LDL-C avoids the need for fasting samples but does add extra expense. In earlier years research laboratories used the beta-quantification method, which is technically demanding and requires specialized ultracentrifugation equipment. We will briefly review the performance of both. We will also address the dilemma in defining LDL-C and in designating a reference method to which both calculated and direct measures of LDL-C are being compared.
Standardization of lipids An assay is standardized if the results from that particular test method are traceable and agree within specified limits to a reference method and/or reference material. The standardization process should identify bias, that is, any systematic difference in the test method either higher or lower than the reference method, and adjust the calibrators (standards) to correct the bias. Standards are generally provided by the assay manufacturer. For lipids (total cholesterol, LDL-C, HDL-C, and triglycerides), manufacturers
266
Journal of Clinical Lipidology, Vol 5, No 4, August 2011
Table 1
Performance goals for lipid and lipoprotein testing as defined by the NCEP Working Group on Lipoprotein Measurement2–4
Total cholesterol Triglycerides LDL cholesterol HDL cholesterol
Total error, %
Precision, %
Bias, %
#9 #15 #12 #13
#3 #5 #4 CV #4 ($42 mg/dL) SD # 1.7 mg/dL (,42 mg/dL)
#3 #5 #4 #5
CV, coefficient of variation; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NCEP, National Cholesterol Education Program.
standardize their assays by ‘‘split-sample’’ comparison with a Cholesterol Reference Method Laboratory Network (CRMLN) laboratory using fresh patient samples. The CRMLN laboratories are, in turn, traceable to the Centers for Disease Control and Prevention (CDC) reference methods. For manufacturers to certify their product, performance must be within established limits for accuracy and precision. This program was intended to transfer accuracy to the clinical laboratory. Because calibrators are made with additives and stabilizers that make the matrix different from patient samples, the analytical system (instrument and reagents) may introduce a bias compared with fresh sera. In other words, the relationship between the analyte concentration in the sample and the instrument response (eg, intensity of transmitted light) differs because of the matrix. The split-sample comparison with fresh patient sera allows the manufacturer to assign a value to the calibrators that optimizes the agreement of the patient samples with the CRMLN laboratory. However, the program has limitations, and the protocol does not appear to provide for rigorous testing with abnormal specimens. LDL has been defined by electrophoretic mobility, as beta-migrating lipoproteins, or as the lipoprotein particles in the density range 1.019–1.063 kg/L after ultracentrifugation. Physical characteristics used to separate lipoproteins are summarized in Table 2. However, risk-based cut points for LDL cholesterol defined by NCEP are determined by epidemiological studies, almost all of which used either beta-quantification (BQ) or calculated LDL-C by use of the Friedewald equation, which was derived from BQ. This ambiguity in defining LDL is a critical limitation in LDL standardization efforts. Table 2
For LDL-C, BQ is the reference method on which standardization of LDL-C is based, whether by calculation with the Friedewald equation or by direct measurement. BQ requires ultracentrifugation of serum or plasma at d 5 1.006 kg/L to separate the supernatant, which contains very low-density lipoprotein (VLDL) and chylomicron particles, from the infranate, which contains LDL and HDL particles. LDL particles are then precipitated from the infranate, leaving HDL. LDL-C is then calculated as infranate cholesterol minus HDL cholesterol.3 Thus, BQ includes the cholesterol in intermediate-density lipoproteins (IDL; 1.006–1.019 kg/L) and the cholesterol in lipoprotein(a) [Lp(a)] as well as the cholesterol in the classical LDL fraction, d 1.019-1.063 kg/L. Moreover, VLDL remnants can be found in both the VLDL range (,1.006 kg/L) and in the intermediate-density range (1.006–1.019 kg/L), which is measured as LDL with BQ. Similarly, the precipitation step in the BQ, which uses the polyanion heparin and the divalent cation manganese, appears to measure different HDL-C subfractions than reagents that use alternate polyanions and cations. Apo E-rich HDL particles, for example, tend to be larger and less dense than other HDL particles and fractionate primarily with the HDL supernate via the use of heparin/ manganese, but precipitate with LDL via the use of dextran sulfate and perhaps other polyanion/divalent cation reagents.6 The large apo E-rich particles generally circulate at relatively low concentrations but can be elevated in CETPinhibited or CETP-deficient patients, an increasingly likely scenario if CETP inhibitors in development become available. Finally, the BQ methodology is technically demanding and difficult to reproduce with alternate methods, and questions have been raised about lipid oxidation, exchange
Major classes of lipoproteins
Lipoprotein
Electrophoretic mobility
Major apolipoproteins
Particle diameter, nm
Density, g/L
Chylomicrons VLDL IDL LDL Lp(a) HDL
Origin Pre-b Pre-b or b b Pre-b or b a
B-48, CII, CIII, E B-100, CII, CIII, E B-100, E B-100 Apo(a), B-100 AI, AII, CII, CIII, E
80–1200 30–80 23–35 18–25 2 5–12
,0.95 0.95–1.006 1.006–1.019 1.019–1.063 1.045–1.080 1.063–1.21
HDL, high-desnity lipoprotein; IDL, intermediate-density lipoprotein; LDL, low-density lipoprotein; Lp(a), lipoprotein A; VLDL, very low-density lipoprotein.
Contois et al
Reliability of LDL-C and non-HDL-C measurement
of lipids and proteins, and dissociation of proteins during ultracentrifugation.
The Friedewald equation The Friedewald formula7 calculates LDL-C using measured values for total cholesterol (shown as TC), HDL-C, and triglycerides (shown as TG) as follows: LDL-C5 ðTCÞ 2 ðHDL-CÞ 2 ðVLDL-CÞ where: VLDL-C (mg/dL) 5 TG (mg/dL)/5 From an analytical perspective, the inaccuracy of the Friedewald equation is the sum of the inaccuracies and imprecision of total cholesterol, HDL-C, and triglyceride measurements. Total cholesterol measurement is well standardized and very precise. However, there are important limitations in measurement of both HDL-C and triglycerides. The measurement of HDL-C is particularly challenging because clinically important differences in concentrations are small, and even small analytical error can contribute to misclassification. The accuracy of HDL-C is based on comparison with the CDC BQ method, a combined ultracentrifugation and chemical precipitation method, as discussed previously in this article.5 Like LDL-C, the CDC methods provide a link to the epidemiological database from which NCEP cut points were derived. An alternate designated comparison method that does not require ultracentrifugation has also been developed to help standardize HDL cholesterol measurement through the Cholesterol Reference Method Laboratory Network.8 In the clinical laboratory, precipitation methods have been largely replaced with homogeneous (direct) assays that require no pretreatment or special handling. Unfortunately, as with direct LDL-C assays, there appears to be significant method-specific bias with these newer assays and poor agreement with reference methods.9 The WGL recommended the chemical method used by the CDC to measure triglycerides as the basis for accuracy 4 because this method provides a link to the epidemiological database for cardiovascular disease risk. This method was relatively specific for triglycerides, although some diglycerides and monoglycerides were also measured, whereas phospholipids and free glycerol were removed during the extraction procedure. To establish traceability to the CDC reference method, therefore, the triglyceride measurement should not include free glycerol. However, the CDC now uses an isotope dilution-mass spectrometry assay for total glycerides as their reference method, 10 which presumably includes glycerol and mono- and diglycerides. Most clinical laboratories do not correct for free glycerol. The contribution of free glycerol to triglycerides in most patient samples is small and not likely to have an impact on clinical decision making with respect to effect on calculated LDL-C, but free glycerol concentration may be increased in patients as the result of strenuous exercise, liver disease, diabetes, hemodialysis, parenteral nutrition, intravenous medications
267 containing glycerol, and stress.4 The WGL recommended that laboratories offer glycerol blanked triglyceride assays, even if it performed only when requested, or for specimens with elevated triglycerides, and also that glycerol blanking be mandatory in laboratories that specialize in the assessment of lipid status, have large populations of hyperlipidemic subjects, or participate in clinical or basic research.4 These recommendations were largely ignored. Now that the CDC reference method includes free glycerol, this source of bias is eliminated and methods that measure total glycerides (triglycerides and free glycerol) will better agree with the CDC reference method. The question remaining is whether LDL-C calculated with total glycerides is better in assessing CHD risk. It is important to remember that the Friedewald formula was developed for research, not clinical purposes, but LDL-C could not have been introduced into clinical care without it. In this case, necessity was the mother of adaptation. Very quickly, it was realized that the calculation is not valid for specimens having triglycerides .400 mg/dL, for patients with type III hyperlipoproteinemia or chylomicronemia, or nonfasting specimens.7 Moreover, in diabetic patients, the Friedewald formula appeared to underestimate LDL-C by 8%–10%, and agreement within 10% of BQ was seen in only 68% of diabetic patients.11 Another report also showed poor correlation between the Friedewald equation and ultracentrifugation, with only 49% and 73% of results agreeing within 10% for diabetics and nondiabetics, respectively.12 Branchi et al13 also reported discordance between calculated LDL and ultracentrifugation, but the differences were similar in both diabetic and nondiabetic groups. The authors show that the differences between methods were related to differences in triglyceride concentrations, with greater discordance with triglycerides .200 mg/dL, an observation reported by others, as well.14,15 Scharnagl et al16 found that the Friedewald equation was also inaccurate at lower LDL-C concentrations, with a bias of 218.5%, 214.5%, 27.3%, and 23.8% reported at LDL-C concentrations of 61, 93, 135, and 180 mg/dL, respectively, compared with BQ. The authors of a recent study reported poor agreement between results calculated with the Friedewald equation and a direct LDL-C assay from Siemens.17 Despite a good correlation between these methods, more than 25% of results differed by more than 30 mg/dL,17 leading the authors to conclude that the two methods do not consistently provide similar clinical information.
Direct LDL-C assays The Laboratory Standardization Panel encouraged the development of direct methods for LDL-C because of concerns about the imprecision of a calculated LDL-C. ‘‘Direct’’ refers to homogeneous methods, that is, assays that do not require a preliminary separation step, such as ultracentrifugation, or manual manipulation of the sample.
268
Journal of Clinical Lipidology, Vol 5, No 4, August 2011
The primary sample tube can be sampled directly on most automated chemistry analyzers for direct measurement of LDL-C. The demand for homogeneous assays is understandable for clinical laboratories where cost pressures have driven automation. Given the impracticality of electrophoresis and ultracentrifugation in the clinical laboratory, alternate methods for separating LDL were sought. Analogous to HDL precipitation methods, heparin, polyvinyl sulfate, dextran sulfate, and proprietary polymers were used to precipitate LDL particles and allow the calculation of LDL-C as the difference between total cholesterol and supernatant cholesterol.18 However, these methods proved to be nonspecific and offered no clear advantage over the Friedewald equation.19 Second-generation methods involved immunoseparation, whereby apo AI and apo E bound to polystyrene beads were used to bind VLDL and HDL, and a centrifugal device allowed the LDL, collected in the filtrate, to be directly measured. The assay was relatively robust, although some VLDL remained with the LDL fraction in hypertriglyceridemic specimens resulting in a 5%–12.5% positive bias.19 Also, no IDL and only about 75% of the Lp(a) cholesterol was retained with the LDL fraction.
Table 3
A magnetic separation procedure was also developed to automate the separation step, but again, the assay did not provide the necessary specificity.19 The third-generation assays were truly homogeneous. There are at least six direct LDL-C methods in the marketplace, each based on different proprietary principles (Table 3). Surprisingly, all have been certified through the CDC’s CRMLN, indicating reasonable agreement with the reference method, although positive validation studies are intermixed with frequent reports of disagreement with other direct methods, with the BQ method, or with the Friedewald equation.20–28 Miller et al20 compared four direct methods to the CDC BQ reference method. Total error, calculated from bias and total variability using 100 subjects, including 60 with various hyperlipidemias, was 12.6%, 16.5%, 38.3%, and 41.6% for the four assays, respectively. None of the four methods met the NCEP performance goal of total error ,12%, whereas total error with two of the methods were greater than 3-fold the NCEP performance goal.20 Fei et al compared the Kyowa and Daiichi direct LDL-C assays.21 Both methods measured only a fraction of IDL cholesterol (Kyowa: 52%; Daiichi: 31%), and both
Direct LDL- cholesterol assays
1. Sekisui Medical (formerly Daiichi) liquid selective detergent method: CM, VLDL, HDL 1 CE 1 CO 1 surfactant 1 / cholestenone 1 fatty acids 1 H2O2 H2O2 1 catalase / H2O 1 O2 (no color development) LDL-C 1 surfactant 2 1 CE 1 CO 1 peroxidase 1 DSBmT / color development 2. Kyowa Medex selective solubilization method: CM, VLDL, HDL 1 sugar compounds (a-cyclodextrin/dextran) 1 surfactants / complexes (blocks enzymes) LDL-C 1 surfactant 1 CE 1 CO / cholestenone 1 H2O2 H2O2 1 4AAP 1 peroxidase 1 HDAOS / color development 3. Wako enzyme selective protection method: LDL 1 ‘‘Compound Y’’ (modified PEG) / protects LDL from enzymes CM, VLDL, and HDL 1 CE 1 CO / H2O2 1 catalase (no color development) LDL 1 ‘‘deprotecting reagent’’ 1 CE 1 CO / cholestenone 1 H2O2 H2O2 1 4AAP 1 peroxidase 1 HDAOS / color development 4. Denka Seiken elimination method: Non-LDL 1 surfactant combination 1 1 CE 1 CO / cholestenone 1 H2O2 H2O2 1 catalase / H2O (no color development) LDL-C 1 surfactant combination 2 1 CE 1 CO 1 sodium azide (to inhibit catalase) / cholestenone 1 H2O2 H2O2 1 4AAP 1 peroxidase 1 HDAOS / color development 5. Sysmex (formerly International Reagent Co) calixarene complex method: LDL 1 calixarene / LDL-calixarene soluble complex CM, VLDL, and HDL 1 CE1 1 CD 1 hydrazine / cholestenone hydrazone (CE from Chromobacterium viscosum cannot react with calixarene complexes) LDL-C-calixarene complex 1 CE2 1 CD 1 hydrazine 1 NAD 1 deoxycholate / cholestenone hydrazone 1 NADH 6. Serotec and UMA phosphate complex inhibition method: LDL-C 1 detergent 1 phosphate compound 1 CE / free cholesterol Free cholesterol 1 CO / cholestenone 1 H2O2 H2O2 1 4AAP 1 peroxidase 1 HDAOS / color development 4AAP, 4-aminoantipyrine; CD, cholesterol dehydrogenase; CE, cholesterol esterase; CM, chylomicrons; CO, cholesterol oxidase; DSBmT, N,N-bis-(4-sulfobutyl)-m-toluidine; FDAOS, N-ethyl-N-(2-hydroxy-3-sulfopropyl)-3,5-dimethoxy-4-fluoraniline; HDAOS, N-(2-hydroxy-3-sulfopropyl)-3, 5-dimethoxyaniline; HDL, high-density lipoprotein; LDL, low-density lipoprotein. Adapted with permission from M. A. Kramer, IV. Lipid Standardization Results of Japanese Manufacturers by US Cholesterol Reference Method Laboratory Network Certification Protocols and Reagent Specificity and Performance. In: Kramer M. A., ed. Focus on Cholesterol Research, Nova Science Publishers, Inc.; 2006:75-146.
Contois et al
Reliability of LDL-C and non-HDL-C measurement
methods measured a proportion of apoE-rich HDL as LDL (Kyowa: 18%; Daiichi: 8%). The Daiichi method also measured the abnormal lipoprotein Lp-X, isolated from cholestatic serum, as LDL-C,21 an observation also reported by Iwasaki with the Daiichi assay but not with the Denka Seiken assay.22 Usui and colleagues23 also compared the measurement of lipoprotein fractions using the Kyowa and Daiichi assays. The Kyowa assay measured 17% of VLDL-C, 72% of IDL-C, 88%–92% of LDL-C, 63% of small, dense LDL-C (density 1.050–1.063), and 71%–87% of Lp(a) cholesterol. Inaccuracy was also evident in the Daiichi assay, which measured 24% of the VLDL-C, 69% of the IDL-C, and 80%–91% of Lp(a) cholesterol, and only 45% of small, dense LDL-C.23 Bayer et al24 concluded that bias with many of the direct LDL-C methods was associated with the VLDL-C/ triglyceride ratio, indicating that cholesterol enrichment of VLDL was an important source of bias. Similarly, a comparison of Roche and Wako assays in individuals with a variety of lipoprotein disorders showed that, although accurate results were possible with sera from individuals with type IIa, type IIb, or type IV hyperlipoproteinemia, there was a 30% positive bias in individuals with type III hyperlipoproteinemia.25 To agree with the BQ or Friedewald equation, these methods must specifically measure the same LDL subfractions included in the density range of 1.006–1.063 kg/L. As discussed previously in this article, the direct methods do not appear to measure the same LDL subfractions, and success in standardization to the reference method is likely to be the result of compensatory errors in the measurement of different fractions29; for example, a method may not recognize certain smaller LDL particles but measure some smaller VLDL particles. With essentially normolipidemic specimens that are typically used for standardization, these differences tend to be offset and hence minimize the error, but comparison of hyperlipidemic specimens shows much greater variability. Miller et al9 recently reported a landmark study that compared direct methods for measuring LDL-C and HDL-C with the BQ reference method procedure by using fresh samples from both ‘‘normal’’ and ‘‘diseased’’ subjects. These data showed a lack of agreement with the reference methods, especially with specimens from patients with dyslipidemias and cardiovascular disease, so-called ‘‘diseased’’ specimens. In fact, only five of the eight direct LDL-C methods met the NCEP performance goals with specimens from nondiseased individuals, and all methods failed to meet NCEP performance goals with those from diseased individuals (Fig. 1 and Table 4). An important advantage of the direct LDL-C methods is the use of nonfasting samples. However, a postprandial decrease in LDL-C appears to be physiologic. In a study of 22 healthy individuals given a high fat meal, LDL-C measured by BQ decreased by 7.6% and 8.5% at 3 and 6 hours after the meal, respectively.30 The decrease in LDL-C coincided with an increase in triglyceride-rich lipoprotein cholesterol (d , 1.006 g/L), suggesting that CETP activity
269 may be responsible for a redistribution of cholesterol postprandially.30 A lack of change in postprandial LDL-C measured with direct methods may indicate a compensation error due to inclusion of increased remnant particles. Mora et al31 compared fasting and nonfasting direct LDL-C measurement (Roche Diagnostics/Hitachi 911) in the prospective Women’s Health Study and found that only fasting LDL-C significantly predicted future cardiovascular disease events with a hazard ratio (95% confidence interval) per 1-SD increment of 1.21 (1.13–1.29) compared with 1.00 (0.87–1.15) for nonfasting LDL-C. Although fasting direct LDL-C and calculated LDL-C were highly correlated (r 5 0.98), fasting and nonfasting direct LDL-C were 5.6 mg/dL and 11.5 mg/dL lower on average, respectively, than the Friedewald LDL-C.32 The hazard ratios for fasting LDL-C were similar, regardless of whether LDL-C was calculated or directly measured: 1.23 (1.15–1.32) for directly measured LDL-C and 1.22 (1.14–1.30) for fasting Friedewald LDL-C.32 Another presumed advantage of direct LDL methods is greater accuracy associated with a single measurement rather than the accumulated imprecision associated with the three measurements required for the calculation. An important component of this variability is biological rather
Figure 1 Box-and-whisker plot of the differences in percentage between the direct and Reference Method Procedure results for LDL-C and HDL-C for each direct method. D, diseased; N, nondiseased; De, Denka; Ky, Kyowa; Ro, Roche; Sr, Serotek; Sk, Sekisui; Sy, Sysmex; Um, UMA; Wa, Wako. Reprinted with permission from Miller et al.9
270
Journal of Clinical Lipidology, Vol 5, No 4, August 2011
Table 4
Total error with direct LDL-C and direct HDL-C methods Nondisease
LDL-C assay Denka Kyowa Roche Sekisui Serotek Sysmex UMA Wako HDL-C assay Denka Kyowa Roche Sekisui Serotek Sysmex UMA Wako
Disease
Total CV, %
Mean bias, %
Max TE, %
Total CV, %
Mean bias, %
Max TE,* %
6.2 3.3 3.8 4.2 3.2 4.2 2.6 2.8
0.2 21.1 26.8 20.7 26.2 26.0 20.1 1.1
13.5 27.5 213.3 28.8 211.9 213.3 5.3 6.8
10.5 9.6 10.0 6.0 9.0 10.8 13.8 6.0
21.5 20.8 26.3 21.7 211.8 27.8 20.4 4.1
22.3 20.4 223.3 213.5 226.6 225.9 31.9 18.2
2.9 3.7 4.3 3.4 4.8 3.1 6.0 2.6
4.0 2.5 22.4 21.7 24.8 25.4 0.7 4.8
10.4 10.4 210.4 28.2 213.4 210.9 13.6 10.5
8.4 8.1 8.1 6.1 9.0 6.7 16.4 6.4
0.4 2.1 23.1 25.2 23.0 28.6 21.9 8.8
18.8 20.0 217.5 216.0 218.9 219.8 36.3 24.0
Reprinted with permission from Miller et al.9 CV, coefficient of variance; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TE, total error. *Greater of positive or negative limit.
than analytical, especially for triglycerides. Cooper et al33 reported average biological variation for cholesterol, LDL-C, HDL-C, and triglycerides of 6.0%, 9.5%, 7.4%, and 22.6%, respectively. In one study, four serial measurements 1 week apart in 35 subjects showed biological variability of 4.7%, 6.4%, and 19.6% and total variability of 5.4%, 6.9%, and 20.1%, for total cholesterol, HDL-C, and triglycerides, respectively.34 Despite the large variability in triglycerides, calculated LDL-C and directly measured LDL-C (immunoseparation technique) exhibited similar variation, 7.3% and 6.8%, respectively.34 A favorable reimbursement policy has helped with the large-scale adoption of direct LDL-C methods. Despite ongoing concerns about the reliability of direct LDL-C methods, CMS allows a physician to order up to six direct LDL-C measurements per patient per year, at $13.66 per test. A standard lipid profile, on the other hand, is allowed only once a year and is reimbursed for $19.19.
Errors in non-HDL cholesterol Non-HDL-C is a calculation that adds no additional expense beyond the lipid panel and is advocated as an additional tool to assess risk in patients with elevated triglycerides. The conventional wisdom is that non-HDL-C is better than LDL-C in assessing risk in these individuals because it includes the cholesterol in all potentially atherogenic lipoproteins. However, it is more likely that nonHDL-C is better than LDL-C because it better estimates the LDL particle number.35
In terms of analytical error, non-HDL-C involves two measurements: total cholesterol and HDL-C. Total cholesterol is relatively well standardized, and assays are precise. However, direct HDL-C assays are problematic, and bias and imprecision associated with HDL-C measurement will impact the reliability of non-HDL-C calculation. According to Miller et al,9 six of eight direct HDL-C assays failed to meet NCEP total error goals in the healthy control group, whereas all eight assays failed to meet performance goals in the group with cardiovascular disease and/or lipoprotein disorders (Table 4). Total variability ranged from 2.6% to 16.4% and total error ranged from 28.2% to 36.3%. Mean bias ranged from 28.6% to 8.8% between assays and the reference method.9 This bias is applicable to non-HDL-C, as well, although the large imprecision is mitigated somewhat by the typically lower HDL-C concentration relative to the total cholesterol concentration from which it is subtracted. Nevertheless, bias and imprecision associated with HDL-C is likely to impact the clinical accuracy of non-HDL-C calculation.
Errors in apo B po B appears to be a better predictor of coronary heart disease than LDL-C and non-HDL-C, 36–41 and one could argue that standardization initiatives for apo B have proceeded more quickly and more successfully for apo B than for LDL-C. The WHO/IFCC collaboration has resulted in the development of secondary reference material to ensure traceability of manufacturer calibrators to an
Contois et al
Reliability of LDL-C and non-HDL-C measurement
approved standard.42 Marcovina et al43 confirmed that accuracy and between-laboratory comparability can be achieved with such uniform calibration. The bias and imprecision for 22 immunonephelometric and immunoturbidimetric assays ranged from 25.3% to 3.6% and 0.9% to 3.2%, respectively.43 More data are needed to rigorously assess method-specific bias with apo B assays, especially in subjects with various lipoprotein disorders. However, because apoB is a well-characterized protein, it appears to provide an alternative to the measurement of heterogeneous LDL and HDL particles and the methodspecific bias inherent with direct LDL-C and HDL-C assays.
Summary Unlike cholesterol, a molecule with a defined chemical structure, LDL and HDL are heterogeneous classes of particles that vary in size and composition, making development of specific assays difficult. Assays or separation techniques determined by different principles may measure different subsets of LDL or HDL, compounding the challenge of standardization. The limitations and errors of the Friedewald calculation, although well-documented, are not well-appreciated by clinicians. Direct LDL-C and direct HDL-C assays have not been adequately standardized, as evidenced by the bias between methods and with reference methods. Without adequate standardization of assays, we cannot rely on a universal cutpoint to assess risk. A separate issue is imprecision. According to the WGL,3 a single LDL-C measurement was clearly insufficient to categorize risk. Ideally, the patient should have LDL-C measured multiple times during an 8-week period at (at least) 1-week intervals, which clearly is impossibile because of insurance reimbursement policies and its huge inconvenience for the patient and clinician. Although largely ignored, it is recommended that, because of analytical and biological variability, at least two serial samples be measured before clinical decision making, although even duplicate testing leaves room for misclassification of patient’s risk: ‘‘Based on the prevailing distributions of LDLcholesterol, with two serial measurements and considering a cutpoint of 130 mg/dL, a patient’s LDL-cholesterol can be confidently assumed to be above or below the cutpoint when the mean value is .145 mg/dL or ,115 mg/dL, respectively.sufficient to categorize 71% of the general population as being above or below the 130 mg/dL cutpoint..’’3
Error is not avoided because it is ignored. Thus, the almost universal practice of measuring one sample unquestionably makes care simpler, but with the consequence that important decisions are inevitably based on less than acceptably accurate information. This is especially true for LDL-C measurement.
271
References 1. Rifai N, Dufour DR, Cooper GR. Preanalytical variation in lipid, lipoprotein, and apolipoprotein testing. In: Rifai N, Warnick GR, Dominiczak MH, editors. Handbook of Lipoprotein Testing. 2nd ed. Washington, DC: AACC Press, 2000. 2. National Cholesterol Education Program. Recommendations for improving cholesterol measurement. A report from the Laboratory Standardization Panel of the National Cholesterol Education Program. NIH Publication No. 9022964, Bethesda, Maryland, February, 1990. 3. Bachorik PS, Ross JW, for the NCEP Working Group on Lipoprotein Measurement. National Cholesterol Education Program recommendations for measurement of low-density lipoprotein cholesterol: executive summary. Clin Chem. 1995;41:1414–1420. 4. Stein EA, Myers GL, for the NCEP Working Group on Lipoprotein Measurement. National Cholesterol Education Program recommendations for triglyceride measurement: executive summary. Clin Chem. 1995;41:1421–1426. 5. Warnick GR, Wood PD, for the NCEP Working Group on Lipoprotein Measurement. National Cholesterol Education Program recommendations for measurement of high-density lipoprotein cholesterol: executive summary. Clin Chem. 1995;41:1427–1433. 6. Gibson JC, Rubinstein A, Brown WW. Precipitation of apo E-containing lipoproteins by precipitation reagents for apolipoprotein B. Clin Chem. 1984;30:1784–1788. 7. Friedewald WT, Levy RI, Fredrickson DS. Estimation of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499–502. 8. Kimberly M, Leary E, Cole T, Waymack P. Selection, validation, standardization, and performance of a designated comparison method for HDL cholesterol for use in the cholesterol reference method laboratory network. Clin Chem. 1999;45:1803–1812. 9. 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;56:977–986. 10. Centers for Disease Control and Prevention. Laboratory quality assurance and standardization programs. Available at: http://www.cdc.gov/ labstandards/lsp_methods.html. Assessed December 21, 2010. 11. Hirany S, Li D, Jialal I. A more valid measurement of low-density lipoprotein cholesterol in diabetic patients. Am J Med. 1997;102:48–53. 12. Rubies-Pratt J, Reverter JL, Senti M, et al. Calculated low-density lipoprotein cholesterol should not be used for management of lipoprotein abnormalities in patients with diabetes mellitus. Diabetes Care. 1993; 16:1081–1086. 13. Branchi A, Rovellinni A, Torri A, Sommariva D. Accuracy of calculated serum low-density lipoprotein cholesterol for the assessment of coronary heart disease risk in NIDDM patients. Diabetes Care. 1998;21:1397–1402. 14. McNamara JR, Cohn JS, Wilson PWF, Schaefer EJ. Calculated values for low-density lipoprotein cholesterol in the assessment of lipid abnormalities and coronary disease risk. Clin Chem. 1990;36:36–42. 15. Warnick R, Knopp RH, Fitzpatrick V, Branson L. Estimating lowdensity lipoprotein cholesterol by the Friedewald equation is adequate for classifying patients on the basis of nationally recommended cutpoints. Clin Chem. 1990;36:15–19. 16. Scharnagl H, Nauck M, Wieland H, Marz W. The Friedewald formula underestimates LDL cholesterol at low concentrations. Clin Chem Lab Med. 2001;39:426–431. 17. Baruch L, Agarwal S, Gupta B, et al. Is directly measured low-density lipoprotein clinically equivalent to calculated low-density lipoprotein? J Clin Lipidol. 2010;4:259–264. 18. Demacker PN, Hijmans AG, Brenninkmeijer BJ, Jansen AP, van’t Laar A. Five methods for determining low-density lipoprotein cholesterol compared. Clin Chem. 1984;30:1797–1800. 19. Nauck M, Warnick GR, Rifai N. Methods for measurement of LDL-cholesterol: a critical assessment of direct measurement by homogeneous assays versus calculation. Clin Chem. 2002;48:236–254.
272 20. Miller WG, Waymack PP, Anderson FP, Ethridge SF, Jayne EC. Performance of four homogeneous direct methods for LDL-cholesterol. Clin Chem. 2002;48:489–498. 21. Fei H, Maeda S, Kirii H, Fujigaki S, Maekawa N, Fujii H, et al. Evaluation of two different homogeneous assays for LDL-cholesterol in lipoprotein-X-positive serum. Clin Chem. 2000;46:1351–1356. 22. Iwasaki Y, Matsuyama H, Nakashima N. Improved specificity of a new homogeneous assay for LDL-cholesterol in serum with abnormal lipoproteins. Clin Chem. 2006;52:886–888. 23. Usui S, Kakuuchi H, Okamoto M, Mizukami Y, Okazaki M. Differential reactivity of two homogeneous LDL-cholesterol methods to LDL and VLDL subfractions, as demonstrated by ultracentrifugation and HPLC. Clin Chem. 2002;48:1946–1954. 24. Bayer P, Veinberg F, Couderc R, et al. Multicenter evaluation of four homogeneous LDL-cholesterol assays. Ann Biol Clin. 2005;63:27–41. 25. Esteban-Salan M, Guimon-Bardesi A, Maria de la Viuda-Unzueta J, et al. Analytical and clinical evaluation of two homogeneous assays for LDL-cholesterol in hyperlipidemic patients. Clin Chem. 2000;46: 1121–1131. 26. Lindsey CC, Graham MR, Johnston TP, Kiroff CG, Freshley A. A clinical comparison of calculated versus direct measurement of lowdensity lipoprotein cholesterol level. Pharmacotherapy. 2004;24: 167–172. 27. Rifai N, Iannotti E, DeAngelis K, Law T. Analytical and clinical performance of a homogeneous enzymatic LDL-cholesterol assay compared with the ultracentrifugation-dextran sulfate-Mg21 method. Clin Chem. 1998;44:1242–1250. 28. Nauck M, Graziani MS, Bruton D, et al. Analytical and clinical performance of a detergent-based homogeneous LDL cholesterol assay: a multicenter evaluation. Clin Chem. 2000;46:506–514. 29. Warnick GR. Editor’s notes. The Fats of Life Newsletter, Fall, 2003. 30. Cohn JS, McNamara JR, Cohn SD, Ordovas JM, Schaefer EJ. Postprandial plasma lipoprotein changes in human subjects of different ages. J Lipid Res. 1988;29:469–479. 31. Mora S, Rifai N, Buring JE, Ridker PM. Fasting compared with nonfasting lipids and apolipoproteins for predicting incident cardiovascular events. Circulation. 2008;118:993–1001. 32. Mora S, Rifai N, Buring JE, Ridker PM. Comparison of LDL cholesterol concentrations by Friedewald calculation and direct measurement in relation to cardiovascular events in 27 331 women. Clin Chem. 2009;55:888–894.
Journal of Clinical Lipidology, Vol 5, No 4, August 2011 33. Cooper GR, Smith SJ, Myers GL, Sampson EJ, Magid E. Estimating and minimizing effects of biologic sources of variation by relative range when measuring the mean of serum lipids and lipoproteins. Clin Chem. 1994;40:227–232. 34. Schectman G, Patsches M, Sasse EA. Variability in cholesterol measurements: comparison of calculated and direct LDL cholesterol determinations. Clin Chem. 1996;42:732–737. 35. Sniderman A, McQueen M, Contois J, Williams K, Furberg CD. Why is non-high density lipoprotein cholesterol a better marker of the risk of vascular disease than low-density lipoprotein cholesterol? J Clin Lipidol. 2010;4:152–155. 36. Sniderman AD, Williams K, Contois JH, et al. A meta-analysis of LDL-C, nonHDL-C, and apoB as markers of cardiovascular risk. Circ Cardiovasc Qual Outcomes. 2011;4:337–345. 37. Yusuf S, Hawken S, Ounpuu S, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364:937–952. 38. Barter PJ, Ballantyne CM, Carmena R, et al. Apo B versus cholesterol in estimating cardiovascular risk and in guiding therapy: report of the thirty-person/ten-country panel. J Intern Med. 2006;259:247–258. 39. Brunzell JD, Davidson M, Furberg CD, Goldberg RB, Howard BV, Stein JH, Witztum JL. Lipoprotein management in patients with cardiometabolic risk: consensus conference report from the American Diabetes Association and the American College of Cardiology Foundation. J Am Coll Cardiol. 2008;51:1512–1524. 40. Contois JH, McConnell JP, Sethi AA, et al. Apolipoprotein B and cardiovascular disease risk: position statement from the AACC Lipoproteins and Vascular Diseases Division Working Group on Best Practices. Clin Chem. 2009;55:407–419. 41. Walldius G, Jungner I, Holme I, et al. High apolipoprotein B, low apolipoprotein A-I, and improvement in the prediction of fatal myocardial infarction (AMORIS study): a prospective study. Lancet. 2001;358:2026–2033. 42. Marcovina SM, Albers JJ, dati F, Ledue TB, Ritchie RF. International Federation of Clinical Chemistry standardization project for measurements of apolipoproteins A-I and B. Clin Chem. 1991;37:1676–1682. 43. Marcovina SM, Albers JJ, Kennedy H, Mei JM, Henderson LO, Hannon WH. International Federation of Clinical Chemistry standardization project for measurement of apolipoproteins A-I and B. IV. Comparability of apolipoprotein B values by use of international reference material. Clin Chem. 1994;40:586–592.
Review Article
Reliability of low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B measurement John H. Contois, PhD*, G. Russell Warnick, MS, MBA, Allan D. Sniderman, MD Maine Standards Company, 765 Roosevelt Trail, Windham, ME 04062, USA (Dr. Contois); Health Diagnostics Laboratory, Richmond, VA, USA (G. R. Warnick); and Mike Rosenbloom Laboratory for Cardiovascular Research, McGill University Health Centre, Montreal, Quebec, Canada (Dr. Sniderman) KEYWORDS: Apolipoprotein B; Cardiovascular disease; HDL cholesterol; LDL cholesterol; Non-HDL cholesterol
Abstract: There is little understanding of the reliability of laboratory measurements among clinicians. Low-density lipoprotein cholesterol (LDL-C) measurement is the cornerstone of cardiovascular risk assessment and prevention, but it is fraught with error. Therefore, we have reviewed issues related to accuracy and precision for the measurement of LDL-C and the related markers non-high-density lipoprotein cholesterol (non-HDL-C) and apolipoprotein B. Despite the widespread belief that LDL-C is standardized and reproducible, available data suggest that results can vary significantly as the result of methods from different manufacturers. Similar problems with direct HDL-C assays raise concerns about the reliability of non-HDL-C measurement. The root cause of method-specific bias relates to the ambiguity in the definition of both LDL and HDL, and the heterogeneity of LDL and HDL particle size and composition. Apolipoprotein B appears to provide a more reliable alternative, but assays for it have not been as rigorously tested as direct LDL-C and HDL-C assays. Ó 2011 National Lipid Association. All rights reserved.
Introduction The trapping of apolipoprotein B (apoB) lipoprotein particles within the arterial wall is the fundamental cause of atherosclerosis, and lowering the apoB lipoprotein particle number in plasma is the most potent therapy to reduce the risk of cardiovascular events. Low-density lipoprotein cholesterol (LDL-C) has been the conventional marker in clinical practice of the apoB lipoproteins. Recently, two alternatives, apoB and non-high density lipoprotein
* Corresponding author. E-mail address: [email protected] Submitted March 7, 2011; revised May 3, 2011. Accepted for publication May 17, 2011.
cholesterol (non-HDL-C), have been proposed to be more accurate biological markers of the atherogenic risk posed by apoB lipoproteins. Attention has focused on the epidemiological and clinical trial results supporting these claims, but little attention has been paid to the analytical and preanalytical errors involved in laboratory quantification of LDL-C versus non-HDL C and apoB. Clinicians assume that laboratory results are precise and accurate, particularly those such as LDL-C, which have become integral to modern cardiovascular care. We understand that errors occur, but we know little of their frequency and magnitude. The purpose of this article, therefore, is, first, to outline the elements of error in laboratory measurement and second, to examine the impact of those errors on the performance of calculated and directly measured LDL-C and non-HDL-C.
1933-2874/$ - see front matter Ó 2011 National Lipid Association. All rights reserved. doi:10.1016/j.jacl.2011.05.004
Contois et al
Reliability of LDL-C and non-HDL-C measurement
Errors in laboratory measurement Laboratory errors can be divided into those that are preanalytical, such as those attributable to errors in obtaining and preserving the sample, or those attributable to physiological or pathological factors, and those that are truly analytical, those that relate to the actual measurement system, that is, instrument, reagent, and calibration. These analytical and preanalytical factors need to be taken into account in assessing the clinical utility and validity of one analyte versus another. Components of preanalytical variability include biological factors (age and gender), behavioral factors (diet, obesity, cigarette smoking, alcohol intake, and exercise), clinical factors (medication and disease-related), and sample collection (fasting status, anticoagulants and preservatives, hemoconcentration, and specimen storage).1 Analytical laboratory error can be divided into two components: imprecision and inaccuracy: Total analytical error 5 Error caused by imprecision 1 error caused by inaccuracy Precision refers to the reproducibility of a particular method, that is, how closely repeated measurements will agree with one another. Obviously, if the differences between replicates are large, a substantially larger or smaller number might have been reported, and there can be no confidence in any particular result. The error caused by imprecision is summarized by the coefficient of variation (CV), which is the standard deviation of repeated results divided by the average concentration. For example, a CV of 5% at a mean concentration of 100 mg/dL indicates that two thirds of the time the reported result will be between 95 and 105 mg/dL. Similarly, the 95% confidence interval, estimated as the mean 6 2 ! CV (or more correctly 1.96 ! CV) for a single measurement, is a result between 90 and 110 mg/dL. Inaccuracy, or bias, refers to a systematic difference in results between a method and the ‘‘true’’ value. Often, the true value is obtained by measurement with a reference method, a method recognized as the ‘‘gold standard.’’ Bias is the difference on average between the method used and the reference method. Examples of these errors include differences in results caused by the use of new lots of calibrators or reagents, instrument-to-instrument differences, and differences introduced by recalibrating an assay. An important component of calibration bias is error in standardization and/or traceability to a recognized reference material and/or reference method. Thus, if there is a bias of 110% between the clinical method and the reference method, all the clinical results will be 10% greater than the true value. In this case, a reported result of 105 mg/ dL would actually correspond to a true value of 95 mg/dL and, if the target were 100 mg/dL, the therapeutic dose of the statin would not need to be increased. It is important to appreciate that these two categories of errors, imprecision and inaccuracy, are independent of each
265 other and that correcting one will not correct the other. Thus, a measurement can be precise, but not accurate, and improving precision does not improve accuracy. Nevertheless, precision is a prerequisite for accuracy in measuring an individual specimen. However, a method that is precise and accurate, on average, can be inaccurate in an individual specimen because of the presence of interfering substances in the specimen. In reviewing the laboratory accuracy of the direct LDL-C methods, and the three assays used to calculate LDL-C, we will discuss the methodologies, standardization, and errors associated with each.
Errors in LDL-C LDL-C is the mass of cholesterol within LDL particles and is, currently, the cornerstone of coronary heart disease risk assessment. The NCEP Laboratory Standardization Panel and the Working Group on Lipoprotein Measurement (WGL) have described physiological, clinical, and other preanalytical factors that contribute to variability in lipid and lipoprotein levels and have established guidelines for measurement of total cholesterol, triglycerides, HDL-C, and LDL-C.2–5 The National Cholesterol Education Program (NCEP) goal for LDL-C analytical performance is a result within 12% of the true value3; or, in other words, the total measurement error (bias plus imprecision) should be within 12% of the true value. NCEP Performance goals are summarized in Table 1. In clinical practice, LDL-C is either estimated by the Friedewald formula or directly measured. The former is a calculation determined by plasma triglycerides, total cholesterol, and HDL-C and, therefore, necessarily includes the accumulated errors in all three measurements. Calculated LDL-C does not add additional expense beyond the three core measurements, but it requires a fasting sample. By contrast, direct measurement of LDL-C avoids the need for fasting samples but does add extra expense. In earlier years research laboratories used the beta-quantification method, which is technically demanding and requires specialized ultracentrifugation equipment. We will briefly review the performance of both. We will also address the dilemma in defining LDL-C and in designating a reference method to which both calculated and direct measures of LDL-C are being compared.
Standardization of lipids An assay is standardized if the results from that particular test method are traceable and agree within specified limits to a reference method and/or reference material. The standardization process should identify bias, that is, any systematic difference in the test method either higher or lower than the reference method, and adjust the calibrators (standards) to correct the bias. Standards are generally provided by the assay manufacturer. For lipids (total cholesterol, LDL-C, HDL-C, and triglycerides), manufacturers
266
Journal of Clinical Lipidology, Vol 5, No 4, August 2011
Table 1
Performance goals for lipid and lipoprotein testing as defined by the NCEP Working Group on Lipoprotein Measurement2–4
Total cholesterol Triglycerides LDL cholesterol HDL cholesterol
Total error, %
Precision, %
Bias, %
#9 #15 #12 #13
#3 #5 #4 CV #4 ($42 mg/dL) SD # 1.7 mg/dL (,42 mg/dL)
#3 #5 #4 #5
CV, coefficient of variation; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NCEP, National Cholesterol Education Program.
standardize their assays by ‘‘split-sample’’ comparison with a Cholesterol Reference Method Laboratory Network (CRMLN) laboratory using fresh patient samples. The CRMLN laboratories are, in turn, traceable to the Centers for Disease Control and Prevention (CDC) reference methods. For manufacturers to certify their product, performance must be within established limits for accuracy and precision. This program was intended to transfer accuracy to the clinical laboratory. Because calibrators are made with additives and stabilizers that make the matrix different from patient samples, the analytical system (instrument and reagents) may introduce a bias compared with fresh sera. In other words, the relationship between the analyte concentration in the sample and the instrument response (eg, intensity of transmitted light) differs because of the matrix. The split-sample comparison with fresh patient sera allows the manufacturer to assign a value to the calibrators that optimizes the agreement of the patient samples with the CRMLN laboratory. However, the program has limitations, and the protocol does not appear to provide for rigorous testing with abnormal specimens. LDL has been defined by electrophoretic mobility, as beta-migrating lipoproteins, or as the lipoprotein particles in the density range 1.019–1.063 kg/L after ultracentrifugation. Physical characteristics used to separate lipoproteins are summarized in Table 2. However, risk-based cut points for LDL cholesterol defined by NCEP are determined by epidemiological studies, almost all of which used either beta-quantification (BQ) or calculated LDL-C by use of the Friedewald equation, which was derived from BQ. This ambiguity in defining LDL is a critical limitation in LDL standardization efforts. Table 2
For LDL-C, BQ is the reference method on which standardization of LDL-C is based, whether by calculation with the Friedewald equation or by direct measurement. BQ requires ultracentrifugation of serum or plasma at d 5 1.006 kg/L to separate the supernatant, which contains very low-density lipoprotein (VLDL) and chylomicron particles, from the infranate, which contains LDL and HDL particles. LDL particles are then precipitated from the infranate, leaving HDL. LDL-C is then calculated as infranate cholesterol minus HDL cholesterol.3 Thus, BQ includes the cholesterol in intermediate-density lipoproteins (IDL; 1.006–1.019 kg/L) and the cholesterol in lipoprotein(a) [Lp(a)] as well as the cholesterol in the classical LDL fraction, d 1.019-1.063 kg/L. Moreover, VLDL remnants can be found in both the VLDL range (,1.006 kg/L) and in the intermediate-density range (1.006–1.019 kg/L), which is measured as LDL with BQ. Similarly, the precipitation step in the BQ, which uses the polyanion heparin and the divalent cation manganese, appears to measure different HDL-C subfractions than reagents that use alternate polyanions and cations. Apo E-rich HDL particles, for example, tend to be larger and less dense than other HDL particles and fractionate primarily with the HDL supernate via the use of heparin/ manganese, but precipitate with LDL via the use of dextran sulfate and perhaps other polyanion/divalent cation reagents.6 The large apo E-rich particles generally circulate at relatively low concentrations but can be elevated in CETPinhibited or CETP-deficient patients, an increasingly likely scenario if CETP inhibitors in development become available. Finally, the BQ methodology is technically demanding and difficult to reproduce with alternate methods, and questions have been raised about lipid oxidation, exchange
Major classes of lipoproteins
Lipoprotein
Electrophoretic mobility
Major apolipoproteins
Particle diameter, nm
Density, g/L
Chylomicrons VLDL IDL LDL Lp(a) HDL
Origin Pre-b Pre-b or b b Pre-b or b a
B-48, CII, CIII, E B-100, CII, CIII, E B-100, E B-100 Apo(a), B-100 AI, AII, CII, CIII, E
80–1200 30–80 23–35 18–25 2 5–12
,0.95 0.95–1.006 1.006–1.019 1.019–1.063 1.045–1.080 1.063–1.21
HDL, high-desnity lipoprotein; IDL, intermediate-density lipoprotein; LDL, low-density lipoprotein; Lp(a), lipoprotein A; VLDL, very low-density lipoprotein.
Contois et al
Reliability of LDL-C and non-HDL-C measurement
of lipids and proteins, and dissociation of proteins during ultracentrifugation.
The Friedewald equation The Friedewald formula7 calculates LDL-C using measured values for total cholesterol (shown as TC), HDL-C, and triglycerides (shown as TG) as follows: LDL-C5 ðTCÞ 2 ðHDL-CÞ 2 ðVLDL-CÞ where: VLDL-C (mg/dL) 5 TG (mg/dL)/5 From an analytical perspective, the inaccuracy of the Friedewald equation is the sum of the inaccuracies and imprecision of total cholesterol, HDL-C, and triglyceride measurements. Total cholesterol measurement is well standardized and very precise. However, there are important limitations in measurement of both HDL-C and triglycerides. The measurement of HDL-C is particularly challenging because clinically important differences in concentrations are small, and even small analytical error can contribute to misclassification. The accuracy of HDL-C is based on comparison with the CDC BQ method, a combined ultracentrifugation and chemical precipitation method, as discussed previously in this article.5 Like LDL-C, the CDC methods provide a link to the epidemiological database from which NCEP cut points were derived. An alternate designated comparison method that does not require ultracentrifugation has also been developed to help standardize HDL cholesterol measurement through the Cholesterol Reference Method Laboratory Network.8 In the clinical laboratory, precipitation methods have been largely replaced with homogeneous (direct) assays that require no pretreatment or special handling. Unfortunately, as with direct LDL-C assays, there appears to be significant method-specific bias with these newer assays and poor agreement with reference methods.9 The WGL recommended the chemical method used by the CDC to measure triglycerides as the basis for accuracy 4 because this method provides a link to the epidemiological database for cardiovascular disease risk. This method was relatively specific for triglycerides, although some diglycerides and monoglycerides were also measured, whereas phospholipids and free glycerol were removed during the extraction procedure. To establish traceability to the CDC reference method, therefore, the triglyceride measurement should not include free glycerol. However, the CDC now uses an isotope dilution-mass spectrometry assay for total glycerides as their reference method, 10 which presumably includes glycerol and mono- and diglycerides. Most clinical laboratories do not correct for free glycerol. The contribution of free glycerol to triglycerides in most patient samples is small and not likely to have an impact on clinical decision making with respect to effect on calculated LDL-C, but free glycerol concentration may be increased in patients as the result of strenuous exercise, liver disease, diabetes, hemodialysis, parenteral nutrition, intravenous medications
267 containing glycerol, and stress.4 The WGL recommended that laboratories offer glycerol blanked triglyceride assays, even if it performed only when requested, or for specimens with elevated triglycerides, and also that glycerol blanking be mandatory in laboratories that specialize in the assessment of lipid status, have large populations of hyperlipidemic subjects, or participate in clinical or basic research.4 These recommendations were largely ignored. Now that the CDC reference method includes free glycerol, this source of bias is eliminated and methods that measure total glycerides (triglycerides and free glycerol) will better agree with the CDC reference method. The question remaining is whether LDL-C calculated with total glycerides is better in assessing CHD risk. It is important to remember that the Friedewald formula was developed for research, not clinical purposes, but LDL-C could not have been introduced into clinical care without it. In this case, necessity was the mother of adaptation. Very quickly, it was realized that the calculation is not valid for specimens having triglycerides .400 mg/dL, for patients with type III hyperlipoproteinemia or chylomicronemia, or nonfasting specimens.7 Moreover, in diabetic patients, the Friedewald formula appeared to underestimate LDL-C by 8%–10%, and agreement within 10% of BQ was seen in only 68% of diabetic patients.11 Another report also showed poor correlation between the Friedewald equation and ultracentrifugation, with only 49% and 73% of results agreeing within 10% for diabetics and nondiabetics, respectively.12 Branchi et al13 also reported discordance between calculated LDL and ultracentrifugation, but the differences were similar in both diabetic and nondiabetic groups. The authors show that the differences between methods were related to differences in triglyceride concentrations, with greater discordance with triglycerides .200 mg/dL, an observation reported by others, as well.14,15 Scharnagl et al16 found that the Friedewald equation was also inaccurate at lower LDL-C concentrations, with a bias of 218.5%, 214.5%, 27.3%, and 23.8% reported at LDL-C concentrations of 61, 93, 135, and 180 mg/dL, respectively, compared with BQ. The authors of a recent study reported poor agreement between results calculated with the Friedewald equation and a direct LDL-C assay from Siemens.17 Despite a good correlation between these methods, more than 25% of results differed by more than 30 mg/dL,17 leading the authors to conclude that the two methods do not consistently provide similar clinical information.
Direct LDL-C assays The Laboratory Standardization Panel encouraged the development of direct methods for LDL-C because of concerns about the imprecision of a calculated LDL-C. ‘‘Direct’’ refers to homogeneous methods, that is, assays that do not require a preliminary separation step, such as ultracentrifugation, or manual manipulation of the sample.
268
Journal of Clinical Lipidology, Vol 5, No 4, August 2011
The primary sample tube can be sampled directly on most automated chemistry analyzers for direct measurement of LDL-C. The demand for homogeneous assays is understandable for clinical laboratories where cost pressures have driven automation. Given the impracticality of electrophoresis and ultracentrifugation in the clinical laboratory, alternate methods for separating LDL were sought. Analogous to HDL precipitation methods, heparin, polyvinyl sulfate, dextran sulfate, and proprietary polymers were used to precipitate LDL particles and allow the calculation of LDL-C as the difference between total cholesterol and supernatant cholesterol.18 However, these methods proved to be nonspecific and offered no clear advantage over the Friedewald equation.19 Second-generation methods involved immunoseparation, whereby apo AI and apo E bound to polystyrene beads were used to bind VLDL and HDL, and a centrifugal device allowed the LDL, collected in the filtrate, to be directly measured. The assay was relatively robust, although some VLDL remained with the LDL fraction in hypertriglyceridemic specimens resulting in a 5%–12.5% positive bias.19 Also, no IDL and only about 75% of the Lp(a) cholesterol was retained with the LDL fraction.
Table 3
A magnetic separation procedure was also developed to automate the separation step, but again, the assay did not provide the necessary specificity.19 The third-generation assays were truly homogeneous. There are at least six direct LDL-C methods in the marketplace, each based on different proprietary principles (Table 3). Surprisingly, all have been certified through the CDC’s CRMLN, indicating reasonable agreement with the reference method, although positive validation studies are intermixed with frequent reports of disagreement with other direct methods, with the BQ method, or with the Friedewald equation.20–28 Miller et al20 compared four direct methods to the CDC BQ reference method. Total error, calculated from bias and total variability using 100 subjects, including 60 with various hyperlipidemias, was 12.6%, 16.5%, 38.3%, and 41.6% for the four assays, respectively. None of the four methods met the NCEP performance goal of total error ,12%, whereas total error with two of the methods were greater than 3-fold the NCEP performance goal.20 Fei et al compared the Kyowa and Daiichi direct LDL-C assays.21 Both methods measured only a fraction of IDL cholesterol (Kyowa: 52%; Daiichi: 31%), and both
Direct LDL- cholesterol assays
1. Sekisui Medical (formerly Daiichi) liquid selective detergent method: CM, VLDL, HDL 1 CE 1 CO 1 surfactant 1 / cholestenone 1 fatty acids 1 H2O2 H2O2 1 catalase / H2O 1 O2 (no color development) LDL-C 1 surfactant 2 1 CE 1 CO 1 peroxidase 1 DSBmT / color development 2. Kyowa Medex selective solubilization method: CM, VLDL, HDL 1 sugar compounds (a-cyclodextrin/dextran) 1 surfactants / complexes (blocks enzymes) LDL-C 1 surfactant 1 CE 1 CO / cholestenone 1 H2O2 H2O2 1 4AAP 1 peroxidase 1 HDAOS / color development 3. Wako enzyme selective protection method: LDL 1 ‘‘Compound Y’’ (modified PEG) / protects LDL from enzymes CM, VLDL, and HDL 1 CE 1 CO / H2O2 1 catalase (no color development) LDL 1 ‘‘deprotecting reagent’’ 1 CE 1 CO / cholestenone 1 H2O2 H2O2 1 4AAP 1 peroxidase 1 HDAOS / color development 4. Denka Seiken elimination method: Non-LDL 1 surfactant combination 1 1 CE 1 CO / cholestenone 1 H2O2 H2O2 1 catalase / H2O (no color development) LDL-C 1 surfactant combination 2 1 CE 1 CO 1 sodium azide (to inhibit catalase) / cholestenone 1 H2O2 H2O2 1 4AAP 1 peroxidase 1 HDAOS / color development 5. Sysmex (formerly International Reagent Co) calixarene complex method: LDL 1 calixarene / LDL-calixarene soluble complex CM, VLDL, and HDL 1 CE1 1 CD 1 hydrazine / cholestenone hydrazone (CE from Chromobacterium viscosum cannot react with calixarene complexes) LDL-C-calixarene complex 1 CE2 1 CD 1 hydrazine 1 NAD 1 deoxycholate / cholestenone hydrazone 1 NADH 6. Serotec and UMA phosphate complex inhibition method: LDL-C 1 detergent 1 phosphate compound 1 CE / free cholesterol Free cholesterol 1 CO / cholestenone 1 H2O2 H2O2 1 4AAP 1 peroxidase 1 HDAOS / color development 4AAP, 4-aminoantipyrine; CD, cholesterol dehydrogenase; CE, cholesterol esterase; CM, chylomicrons; CO, cholesterol oxidase; DSBmT, N,N-bis-(4-sulfobutyl)-m-toluidine; FDAOS, N-ethyl-N-(2-hydroxy-3-sulfopropyl)-3,5-dimethoxy-4-fluoraniline; HDAOS, N-(2-hydroxy-3-sulfopropyl)-3, 5-dimethoxyaniline; HDL, high-density lipoprotein; LDL, low-density lipoprotein. Adapted with permission from M. A. Kramer, IV. Lipid Standardization Results of Japanese Manufacturers by US Cholesterol Reference Method Laboratory Network Certification Protocols and Reagent Specificity and Performance. In: Kramer M. A., ed. Focus on Cholesterol Research, Nova Science Publishers, Inc.; 2006:75-146.
Contois et al
Reliability of LDL-C and non-HDL-C measurement
methods measured a proportion of apoE-rich HDL as LDL (Kyowa: 18%; Daiichi: 8%). The Daiichi method also measured the abnormal lipoprotein Lp-X, isolated from cholestatic serum, as LDL-C,21 an observation also reported by Iwasaki with the Daiichi assay but not with the Denka Seiken assay.22 Usui and colleagues23 also compared the measurement of lipoprotein fractions using the Kyowa and Daiichi assays. The Kyowa assay measured 17% of VLDL-C, 72% of IDL-C, 88%–92% of LDL-C, 63% of small, dense LDL-C (density 1.050–1.063), and 71%–87% of Lp(a) cholesterol. Inaccuracy was also evident in the Daiichi assay, which measured 24% of the VLDL-C, 69% of the IDL-C, and 80%–91% of Lp(a) cholesterol, and only 45% of small, dense LDL-C.23 Bayer et al24 concluded that bias with many of the direct LDL-C methods was associated with the VLDL-C/ triglyceride ratio, indicating that cholesterol enrichment of VLDL was an important source of bias. Similarly, a comparison of Roche and Wako assays in individuals with a variety of lipoprotein disorders showed that, although accurate results were possible with sera from individuals with type IIa, type IIb, or type IV hyperlipoproteinemia, there was a 30% positive bias in individuals with type III hyperlipoproteinemia.25 To agree with the BQ or Friedewald equation, these methods must specifically measure the same LDL subfractions included in the density range of 1.006–1.063 kg/L. As discussed previously in this article, the direct methods do not appear to measure the same LDL subfractions, and success in standardization to the reference method is likely to be the result of compensatory errors in the measurement of different fractions29; for example, a method may not recognize certain smaller LDL particles but measure some smaller VLDL particles. With essentially normolipidemic specimens that are typically used for standardization, these differences tend to be offset and hence minimize the error, but comparison of hyperlipidemic specimens shows much greater variability. Miller et al9 recently reported a landmark study that compared direct methods for measuring LDL-C and HDL-C with the BQ reference method procedure by using fresh samples from both ‘‘normal’’ and ‘‘diseased’’ subjects. These data showed a lack of agreement with the reference methods, especially with specimens from patients with dyslipidemias and cardiovascular disease, so-called ‘‘diseased’’ specimens. In fact, only five of the eight direct LDL-C methods met the NCEP performance goals with specimens from nondiseased individuals, and all methods failed to meet NCEP performance goals with those from diseased individuals (Fig. 1 and Table 4). An important advantage of the direct LDL-C methods is the use of nonfasting samples. However, a postprandial decrease in LDL-C appears to be physiologic. In a study of 22 healthy individuals given a high fat meal, LDL-C measured by BQ decreased by 7.6% and 8.5% at 3 and 6 hours after the meal, respectively.30 The decrease in LDL-C coincided with an increase in triglyceride-rich lipoprotein cholesterol (d , 1.006 g/L), suggesting that CETP activity
269 may be responsible for a redistribution of cholesterol postprandially.30 A lack of change in postprandial LDL-C measured with direct methods may indicate a compensation error due to inclusion of increased remnant particles. Mora et al31 compared fasting and nonfasting direct LDL-C measurement (Roche Diagnostics/Hitachi 911) in the prospective Women’s Health Study and found that only fasting LDL-C significantly predicted future cardiovascular disease events with a hazard ratio (95% confidence interval) per 1-SD increment of 1.21 (1.13–1.29) compared with 1.00 (0.87–1.15) for nonfasting LDL-C. Although fasting direct LDL-C and calculated LDL-C were highly correlated (r 5 0.98), fasting and nonfasting direct LDL-C were 5.6 mg/dL and 11.5 mg/dL lower on average, respectively, than the Friedewald LDL-C.32 The hazard ratios for fasting LDL-C were similar, regardless of whether LDL-C was calculated or directly measured: 1.23 (1.15–1.32) for directly measured LDL-C and 1.22 (1.14–1.30) for fasting Friedewald LDL-C.32 Another presumed advantage of direct LDL methods is greater accuracy associated with a single measurement rather than the accumulated imprecision associated with the three measurements required for the calculation. An important component of this variability is biological rather
Figure 1 Box-and-whisker plot of the differences in percentage between the direct and Reference Method Procedure results for LDL-C and HDL-C for each direct method. D, diseased; N, nondiseased; De, Denka; Ky, Kyowa; Ro, Roche; Sr, Serotek; Sk, Sekisui; Sy, Sysmex; Um, UMA; Wa, Wako. Reprinted with permission from Miller et al.9
270
Journal of Clinical Lipidology, Vol 5, No 4, August 2011
Table 4
Total error with direct LDL-C and direct HDL-C methods Nondisease
LDL-C assay Denka Kyowa Roche Sekisui Serotek Sysmex UMA Wako HDL-C assay Denka Kyowa Roche Sekisui Serotek Sysmex UMA Wako
Disease
Total CV, %
Mean bias, %
Max TE, %
Total CV, %
Mean bias, %
Max TE,* %
6.2 3.3 3.8 4.2 3.2 4.2 2.6 2.8
0.2 21.1 26.8 20.7 26.2 26.0 20.1 1.1
13.5 27.5 213.3 28.8 211.9 213.3 5.3 6.8
10.5 9.6 10.0 6.0 9.0 10.8 13.8 6.0
21.5 20.8 26.3 21.7 211.8 27.8 20.4 4.1
22.3 20.4 223.3 213.5 226.6 225.9 31.9 18.2
2.9 3.7 4.3 3.4 4.8 3.1 6.0 2.6
4.0 2.5 22.4 21.7 24.8 25.4 0.7 4.8
10.4 10.4 210.4 28.2 213.4 210.9 13.6 10.5
8.4 8.1 8.1 6.1 9.0 6.7 16.4 6.4
0.4 2.1 23.1 25.2 23.0 28.6 21.9 8.8
18.8 20.0 217.5 216.0 218.9 219.8 36.3 24.0
Reprinted with permission from Miller et al.9 CV, coefficient of variance; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TE, total error. *Greater of positive or negative limit.
than analytical, especially for triglycerides. Cooper et al33 reported average biological variation for cholesterol, LDL-C, HDL-C, and triglycerides of 6.0%, 9.5%, 7.4%, and 22.6%, respectively. In one study, four serial measurements 1 week apart in 35 subjects showed biological variability of 4.7%, 6.4%, and 19.6% and total variability of 5.4%, 6.9%, and 20.1%, for total cholesterol, HDL-C, and triglycerides, respectively.34 Despite the large variability in triglycerides, calculated LDL-C and directly measured LDL-C (immunoseparation technique) exhibited similar variation, 7.3% and 6.8%, respectively.34 A favorable reimbursement policy has helped with the large-scale adoption of direct LDL-C methods. Despite ongoing concerns about the reliability of direct LDL-C methods, CMS allows a physician to order up to six direct LDL-C measurements per patient per year, at $13.66 per test. A standard lipid profile, on the other hand, is allowed only once a year and is reimbursed for $19.19.
Errors in non-HDL cholesterol Non-HDL-C is a calculation that adds no additional expense beyond the lipid panel and is advocated as an additional tool to assess risk in patients with elevated triglycerides. The conventional wisdom is that non-HDL-C is better than LDL-C in assessing risk in these individuals because it includes the cholesterol in all potentially atherogenic lipoproteins. However, it is more likely that nonHDL-C is better than LDL-C because it better estimates the LDL particle number.35
In terms of analytical error, non-HDL-C involves two measurements: total cholesterol and HDL-C. Total cholesterol is relatively well standardized, and assays are precise. However, direct HDL-C assays are problematic, and bias and imprecision associated with HDL-C measurement will impact the reliability of non-HDL-C calculation. According to Miller et al,9 six of eight direct HDL-C assays failed to meet NCEP total error goals in the healthy control group, whereas all eight assays failed to meet performance goals in the group with cardiovascular disease and/or lipoprotein disorders (Table 4). Total variability ranged from 2.6% to 16.4% and total error ranged from 28.2% to 36.3%. Mean bias ranged from 28.6% to 8.8% between assays and the reference method.9 This bias is applicable to non-HDL-C, as well, although the large imprecision is mitigated somewhat by the typically lower HDL-C concentration relative to the total cholesterol concentration from which it is subtracted. Nevertheless, bias and imprecision associated with HDL-C is likely to impact the clinical accuracy of non-HDL-C calculation.
Errors in apo B po B appears to be a better predictor of coronary heart disease than LDL-C and non-HDL-C, 36–41 and one could argue that standardization initiatives for apo B have proceeded more quickly and more successfully for apo B than for LDL-C. The WHO/IFCC collaboration has resulted in the development of secondary reference material to ensure traceability of manufacturer calibrators to an
Contois et al
Reliability of LDL-C and non-HDL-C measurement
approved standard.42 Marcovina et al43 confirmed that accuracy and between-laboratory comparability can be achieved with such uniform calibration. The bias and imprecision for 22 immunonephelometric and immunoturbidimetric assays ranged from 25.3% to 3.6% and 0.9% to 3.2%, respectively.43 More data are needed to rigorously assess method-specific bias with apo B assays, especially in subjects with various lipoprotein disorders. However, because apoB is a well-characterized protein, it appears to provide an alternative to the measurement of heterogeneous LDL and HDL particles and the methodspecific bias inherent with direct LDL-C and HDL-C assays.
Summary Unlike cholesterol, a molecule with a defined chemical structure, LDL and HDL are heterogeneous classes of particles that vary in size and composition, making development of specific assays difficult. Assays or separation techniques determined by different principles may measure different subsets of LDL or HDL, compounding the challenge of standardization. The limitations and errors of the Friedewald calculation, although well-documented, are not well-appreciated by clinicians. Direct LDL-C and direct HDL-C assays have not been adequately standardized, as evidenced by the bias between methods and with reference methods. Without adequate standardization of assays, we cannot rely on a universal cutpoint to assess risk. A separate issue is imprecision. According to the WGL,3 a single LDL-C measurement was clearly insufficient to categorize risk. Ideally, the patient should have LDL-C measured multiple times during an 8-week period at (at least) 1-week intervals, which clearly is impossibile because of insurance reimbursement policies and its huge inconvenience for the patient and clinician. Although largely ignored, it is recommended that, because of analytical and biological variability, at least two serial samples be measured before clinical decision making, although even duplicate testing leaves room for misclassification of patient’s risk: ‘‘Based on the prevailing distributions of LDLcholesterol, with two serial measurements and considering a cutpoint of 130 mg/dL, a patient’s LDL-cholesterol can be confidently assumed to be above or below the cutpoint when the mean value is .145 mg/dL or ,115 mg/dL, respectively.sufficient to categorize 71% of the general population as being above or below the 130 mg/dL cutpoint..’’3
Error is not avoided because it is ignored. Thus, the almost universal practice of measuring one sample unquestionably makes care simpler, but with the consequence that important decisions are inevitably based on less than acceptably accurate information. This is especially true for LDL-C measurement.
271
References 1. Rifai N, Dufour DR, Cooper GR. Preanalytical variation in lipid, lipoprotein, and apolipoprotein testing. In: Rifai N, Warnick GR, Dominiczak MH, editors. Handbook of Lipoprotein Testing. 2nd ed. Washington, DC: AACC Press, 2000. 2. National Cholesterol Education Program. Recommendations for improving cholesterol measurement. A report from the Laboratory Standardization Panel of the National Cholesterol Education Program. NIH Publication No. 9022964, Bethesda, Maryland, February, 1990. 3. Bachorik PS, Ross JW, for the NCEP Working Group on Lipoprotein Measurement. National Cholesterol Education Program recommendations for measurement of low-density lipoprotein cholesterol: executive summary. Clin Chem. 1995;41:1414–1420. 4. Stein EA, Myers GL, for the NCEP Working Group on Lipoprotein Measurement. National Cholesterol Education Program recommendations for triglyceride measurement: executive summary. Clin Chem. 1995;41:1421–1426. 5. Warnick GR, Wood PD, for the NCEP Working Group on Lipoprotein Measurement. National Cholesterol Education Program recommendations for measurement of high-density lipoprotein cholesterol: executive summary. Clin Chem. 1995;41:1427–1433. 6. Gibson JC, Rubinstein A, Brown WW. Precipitation of apo E-containing lipoproteins by precipitation reagents for apolipoprotein B. Clin Chem. 1984;30:1784–1788. 7. Friedewald WT, Levy RI, Fredrickson DS. Estimation of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499–502. 8. Kimberly M, Leary E, Cole T, Waymack P. Selection, validation, standardization, and performance of a designated comparison method for HDL cholesterol for use in the cholesterol reference method laboratory network. Clin Chem. 1999;45:1803–1812. 9. 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;56:977–986. 10. Centers for Disease Control and Prevention. Laboratory quality assurance and standardization programs. Available at: http://www.cdc.gov/ labstandards/lsp_methods.html. Assessed December 21, 2010. 11. Hirany S, Li D, Jialal I. A more valid measurement of low-density lipoprotein cholesterol in diabetic patients. Am J Med. 1997;102:48–53. 12. Rubies-Pratt J, Reverter JL, Senti M, et al. Calculated low-density lipoprotein cholesterol should not be used for management of lipoprotein abnormalities in patients with diabetes mellitus. Diabetes Care. 1993; 16:1081–1086. 13. Branchi A, Rovellinni A, Torri A, Sommariva D. Accuracy of calculated serum low-density lipoprotein cholesterol for the assessment of coronary heart disease risk in NIDDM patients. Diabetes Care. 1998;21:1397–1402. 14. McNamara JR, Cohn JS, Wilson PWF, Schaefer EJ. Calculated values for low-density lipoprotein cholesterol in the assessment of lipid abnormalities and coronary disease risk. Clin Chem. 1990;36:36–42. 15. Warnick R, Knopp RH, Fitzpatrick V, Branson L. Estimating lowdensity lipoprotein cholesterol by the Friedewald equation is adequate for classifying patients on the basis of nationally recommended cutpoints. Clin Chem. 1990;36:15–19. 16. Scharnagl H, Nauck M, Wieland H, Marz W. The Friedewald formula underestimates LDL cholesterol at low concentrations. Clin Chem Lab Med. 2001;39:426–431. 17. Baruch L, Agarwal S, Gupta B, et al. Is directly measured low-density lipoprotein clinically equivalent to calculated low-density lipoprotein? J Clin Lipidol. 2010;4:259–264. 18. Demacker PN, Hijmans AG, Brenninkmeijer BJ, Jansen AP, van’t Laar A. Five methods for determining low-density lipoprotein cholesterol compared. Clin Chem. 1984;30:1797–1800. 19. Nauck M, Warnick GR, Rifai N. Methods for measurement of LDL-cholesterol: a critical assessment of direct measurement by homogeneous assays versus calculation. Clin Chem. 2002;48:236–254.
272 20. Miller WG, Waymack PP, Anderson FP, Ethridge SF, Jayne EC. Performance of four homogeneous direct methods for LDL-cholesterol. Clin Chem. 2002;48:489–498. 21. Fei H, Maeda S, Kirii H, Fujigaki S, Maekawa N, Fujii H, et al. Evaluation of two different homogeneous assays for LDL-cholesterol in lipoprotein-X-positive serum. Clin Chem. 2000;46:1351–1356. 22. Iwasaki Y, Matsuyama H, Nakashima N. Improved specificity of a new homogeneous assay for LDL-cholesterol in serum with abnormal lipoproteins. Clin Chem. 2006;52:886–888. 23. Usui S, Kakuuchi H, Okamoto M, Mizukami Y, Okazaki M. Differential reactivity of two homogeneous LDL-cholesterol methods to LDL and VLDL subfractions, as demonstrated by ultracentrifugation and HPLC. Clin Chem. 2002;48:1946–1954. 24. Bayer P, Veinberg F, Couderc R, et al. Multicenter evaluation of four homogeneous LDL-cholesterol assays. Ann Biol Clin. 2005;63:27–41. 25. Esteban-Salan M, Guimon-Bardesi A, Maria de la Viuda-Unzueta J, et al. Analytical and clinical evaluation of two homogeneous assays for LDL-cholesterol in hyperlipidemic patients. Clin Chem. 2000;46: 1121–1131. 26. Lindsey CC, Graham MR, Johnston TP, Kiroff CG, Freshley A. A clinical comparison of calculated versus direct measurement of lowdensity lipoprotein cholesterol level. Pharmacotherapy. 2004;24: 167–172. 27. Rifai N, Iannotti E, DeAngelis K, Law T. Analytical and clinical performance of a homogeneous enzymatic LDL-cholesterol assay compared with the ultracentrifugation-dextran sulfate-Mg21 method. Clin Chem. 1998;44:1242–1250. 28. Nauck M, Graziani MS, Bruton D, et al. Analytical and clinical performance of a detergent-based homogeneous LDL cholesterol assay: a multicenter evaluation. Clin Chem. 2000;46:506–514. 29. Warnick GR. Editor’s notes. The Fats of Life Newsletter, Fall, 2003. 30. Cohn JS, McNamara JR, Cohn SD, Ordovas JM, Schaefer EJ. Postprandial plasma lipoprotein changes in human subjects of different ages. J Lipid Res. 1988;29:469–479. 31. Mora S, Rifai N, Buring JE, Ridker PM. Fasting compared with nonfasting lipids and apolipoproteins for predicting incident cardiovascular events. Circulation. 2008;118:993–1001. 32. Mora S, Rifai N, Buring JE, Ridker PM. Comparison of LDL cholesterol concentrations by Friedewald calculation and direct measurement in relation to cardiovascular events in 27 331 women. Clin Chem. 2009;55:888–894.
Journal of Clinical Lipidology, Vol 5, No 4, August 2011 33. Cooper GR, Smith SJ, Myers GL, Sampson EJ, Magid E. Estimating and minimizing effects of biologic sources of variation by relative range when measuring the mean of serum lipids and lipoproteins. Clin Chem. 1994;40:227–232. 34. Schectman G, Patsches M, Sasse EA. Variability in cholesterol measurements: comparison of calculated and direct LDL cholesterol determinations. Clin Chem. 1996;42:732–737. 35. Sniderman A, McQueen M, Contois J, Williams K, Furberg CD. Why is non-high density lipoprotein cholesterol a better marker of the risk of vascular disease than low-density lipoprotein cholesterol? J Clin Lipidol. 2010;4:152–155. 36. Sniderman AD, Williams K, Contois JH, et al. A meta-analysis of LDL-C, nonHDL-C, and apoB as markers of cardiovascular risk. Circ Cardiovasc Qual Outcomes. 2011;4:337–345. 37. Yusuf S, Hawken S, Ounpuu S, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364:937–952. 38. Barter PJ, Ballantyne CM, Carmena R, et al. Apo B versus cholesterol in estimating cardiovascular risk and in guiding therapy: report of the thirty-person/ten-country panel. J Intern Med. 2006;259:247–258. 39. Brunzell JD, Davidson M, Furberg CD, Goldberg RB, Howard BV, Stein JH, Witztum JL. Lipoprotein management in patients with cardiometabolic risk: consensus conference report from the American Diabetes Association and the American College of Cardiology Foundation. J Am Coll Cardiol. 2008;51:1512–1524. 40. Contois JH, McConnell JP, Sethi AA, et al. Apolipoprotein B and cardiovascular disease risk: position statement from the AACC Lipoproteins and Vascular Diseases Division Working Group on Best Practices. Clin Chem. 2009;55:407–419. 41. Walldius G, Jungner I, Holme I, et al. High apolipoprotein B, low apolipoprotein A-I, and improvement in the prediction of fatal myocardial infarction (AMORIS study): a prospective study. Lancet. 2001;358:2026–2033. 42. Marcovina SM, Albers JJ, dati F, Ledue TB, Ritchie RF. International Federation of Clinical Chemistry standardization project for measurements of apolipoproteins A-I and B. Clin Chem. 1991;37:1676–1682. 43. Marcovina SM, Albers JJ, Kennedy H, Mei JM, Henderson LO, Hannon WH. International Federation of Clinical Chemistry standardization project for measurement of apolipoproteins A-I and B. IV. Comparability of apolipoprotein B values by use of international reference material. Clin Chem. 1994;40:586–592.