Evaluation of four different equations for calculating LDL-C with eight different direct HDL-C assays.

BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) is often calculated (cLDL-C) by the Friedewald equation, which requires high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG). Because there have been considerable changes in the measurement of HDL-C with the introduction of direct assays, several alternative equations have recently been proposed. METHODS: We compared 4 equations (Friedewald, Vujovic, Chen, and Anandaraja) for cLDL-C, using 8 different direct HDL-C (dHDL-C) methods. LDL-C values were calculated by the 4 equations and determined by the ß quantification reference method procedure in 164 subjects. RESULTS: For normotriglyceridemic samples (TG<200mg/dl), between 6.2% and 24.8% of all results exceeded the total error goal of 12% for LDL-C, depending on the dHDL-C assay and cLDL-C equation used. Friedewald equation was found to be the optimum equation for most but not all dHDL-C assays, typically leading to less than 10% misclassification of cardiovascular risk based on LDL-C. Hypertriglyceridemic samples (>200mg/dl) showed a large cardiovascular risk misclassification rate (30%-50%) for all combinations of dHDL-C assays and cLDL-C equations. CONCLUSION: The Friedewald equation showed the best performance for estimating LDL-C, but its accuracy varied considerably depending on the specific dHDL-C assay used. None of the cLDL-C equations performed adequately for hypertriglyceridemic samples.

Reference measurement procedure for total glycerides by isotope dilution GC-MS.

BACKGROUND: The CDC's Lipid Standardization Program established the chromotropic acid (CA) reference measurement procedure (RMP) as the accuracy base for standardization and metrological traceability for triglyceride testing. The CA RMP has several disadvantages, including lack of ruggedness. It uses obsolete instrumentation and hazardous reagents. To overcome these problems the CDC developed an isotope dilution GC-MS (ID-GC-MS) RMP for total glycerides in serum. METHODS: We diluted serum samples with Tris-HCl buffer solution and spiked 200-µL aliquots with [(13)C(3)]-glycerol. These samples were incubated and hydrolyzed under basic conditions. The samples were dried, derivatized with acetic anhydride and pyridine, extracted with ethyl acetate, and analyzed by ID-GC-MS. Linearity, imprecision, and accuracy were evaluated by analyzing calibrator solutions, 10 serum pools, and a standard reference material (SRM 1951b). RESULTS: The calibration response was linear for the range of calibrator concentrations examined (0-1.24 mmol/L) with a slope and intercept of 0.717 (95% CI, 0.7123-0.7225) and 0.3122 (95% CI, 0.3096-0.3140), respectively. The limit of detection was 14.8 µmol/L. The mean %CV for the sample set (serum pools and SRM) was 1.2%. The mean %bias from NIST isotope dilution MS values for SRM 1951b was 0.7%. CONCLUSIONS: This ID-GC-MS RMP has the specificity and ruggedness to accurately quantify total glycerides in the serum pools used in the CDC's Lipid Standardization Program and demonstrates sufficiently acceptable agreement with the NIST primary RMP for total glyceride measurement.

Proposed serum cholesterol reference measurement procedure by gas chromatography-isotope dilution mass spectrometry.

BACKGROUND: Our purpose was to establish a mass spectrometry reference measurement procedure (RMP) for cholesterol to use in the CDC's standardization programs. We explored a gas chromatography-isotope dilution mass spectrometry (GC-IDMS) procedure using a multilevel standard calibration curve to quantify samples with varying cholesterol concentrations. METHODS: We calibrated the mass spectrometry instrument by isotope dilution with a pure primary standard reference material and an isotopically enriched cholesterol analog as the internal standard (IS). We diluted the serum samples with Tris-HCl buffer (pH 7.4, 0.05 mol/L, 0.25% Triton X-100) before analysis. We used 17 serum pools, 10 native samples, and 2 standard reference materials (SRMs). We compared the GC-IDMS measurements with the CDC's modified Abell-Levy-Brodie-Kendall (AK) RMP measurements and assessed method accuracy by analyzing 2 SRMs. We evaluated the procedure for lack of interference by analyzing serum spiked with a mixture of 7 sterols. RESULTS: The mean percent bias between the AK and the GC-IDMS RMP was 1.6% for all samples examined. The mean percent bias from NIST's RMP was 0.5% for the SRMs. The total %CVs for SRM 1951b levels I and II were 0.61 and 0.73%, respectively. We found that none of the sterols investigated interfered with the cholesterol measurement. CONCLUSIONS: The low imprecision, linear response, lack of interferences, and acceptable bias vs the NIST primary RMP qualifies this procedure as an RMP for determining serum cholesterol. The CDC will adopt and implement this GC-IDMS procedure for cholesterol standardization.

Non-HDL cholesterol shows improved accuracy for cardiovascular risk score classification compared to direct or calculated LDL cholesterol in a dyslipidemic population.

BACKGROUND: Our objective was to evaluate the accuracy of cardiovascular disease (CVD) risk score classification by direct LDL cholesterol (dLDL-C), calculated LDL cholesterol (cLDL-C), and non-HDL cholesterol (non-HDL-C) compared to classification by reference measurement procedures (RMPs) performed at the CDC. METHODS: We examined 175 individuals, including 138 with CVD or conditions that may affect LDL-C measurement. dLDL-C measurements were performed using Denka, Kyowa, Sekisui, Serotec, Sysmex, UMA, and Wako reagents. cLDL-C was calculated by the Friedewald equation, using each manufacturer's direct HDL-C assay measurements, and total cholesterol and triglyceride measurements by Roche and Siemens (Advia) assays, respectively. RESULTS: For participants with triglycerides<2.26 mmol/L (<200 mg/dL), the overall misclassification rate for the CVD risk score ranged from 5% to 17% for cLDL-C methods and 8% to 26% for dLDL-C methods when compared to the RMP. Only Wako dLDL-C had fewer misclassifications than its corresponding cLDL-C method (8% vs 17%; P<0.05). Non-HDL-C assays misclassified fewer patients than dLDL-C for 4 of 8 methods (P<0.05). For participants with triglycerides≥2.26 mmol/L (≥200 mg/dL) and<4.52 mmol/L (<400 mg/dL), dLDL-C methods, in general, performed better than cLDL-C methods, and non-HDL-C methods showed better correspondence to the RMP for CVD risk score than either dLDL-C or cLDL-C methods. CONCLUSIONS: Except for hypertriglyceridemic individuals, 7 of 8 dLDL-C methods failed to show improved CVD risk score classification over the corresponding cLDL-C methods. Non-HDL-C showed overall the best concordance with the RMP for CVD risk score classification of both normal and hypertriglyceridemic individuals.

Seven direct methods for measuring HDL and LDL cholesterol compared with ultracentrifugation reference measurement procedures.

BACKGROUND: Methods from 7 manufacturers and 1 distributor for directly measuring HDL cholesterol (C) and LDL-C were evaluated for imprecision, trueness, total error, and specificity in nonfrozen serum samples. METHODS: We performed each direct method according to the manufacturer's instructions, using a Roche/Hitachi 917 analyzer, and compared the results with those obtained with reference measurement procedures for HDL-C and LDL-C. Imprecision was estimated for 35 runs performed with frozen pooled serum specimens and triplicate measurements on each individual sample. Sera from 37 individuals without disease and 138 with disease (primarily dyslipidemic and cardiovascular) were measured by each method. Trueness and total error were evaluated from the difference between the direct methods and reference measurement procedures. Specificity was evaluated from the dispersion in differences observed. RESULTS: Imprecision data based on 4 frozen serum pools showed total CVs <3.7% for HDL-C and <4.4% for LDL-C. Bias for the nondiseased group ranged from -5.4% to 4.8% for HDL-C and from -6.8% to 1.1% for LDL-C, and for the diseased group from -8.6% to 8.8% for HDL-C and from -11.8% to 4.1% for LDL-C. Total error for the nondiseased group ranged from -13.4% to 13.6% for HDL-C and from -13.3% to 13.5% for LDL-C, and for the diseased group from -19.8% to 36.3% for HDL-C and from -26.6% to 31.9% for LDL-C. CONCLUSIONS: Six of 8 HDL-C and 5 of 8 LDL-C direct methods met the National Cholesterol Education Program total error goals for nondiseased individuals. All the methods failed to meet these goals for diseased individuals, however, because of lack of specificity toward abnormal lipoproteins.

Standardization of high-sensitivity immunoassays for measurement of C-reactive protein; II: Two approaches for assessing commutability of a reference material.

BACKGROUND: We evaluated the commutability of a proposed reference material (PRM), with a formulation based on dilution of Certified Reference Material 470 (CRM470), for 24 high-sensitivity C-reactive protein (hsCRP) methods. We also investigated whether calibration by use of PRM was effective in harmonizing results. METHODS: A set of 40 native clinical samples was measured along with PRM and 3 dilutions of PRM. We used weighted least-squares polynomial regression (WLS/PR) to perform comparisons between all method combinations and to calculate normalized residuals for the PRM. The PRM was considered noncommutable if any of the normalized residuals for a method pair was >2. Correspondence analysis (CA) was used to explore the multidimensional relationships between methods and samples to evaluate if the PRM had properties similar to native clinical samples. Clinical sample results from the methods for which PRM was commutable were recalibrated based on the PRM results, and ANOVA was used to estimate the CVs before and after recalibration. RESULTS: After omitting data for 9 methods because of poor precision or procedural flaws, we used data from the 15 remaining methods to evaluate commutability. Using both WLS/PR and CA we found that PRM was noncommutable with 1 method. We found modest improvement in total and among-method CVs when PRM was used to harmonize the results from the 14 methods for which it was commutable. CONCLUSIONS: A PRM with a formulation based on dilution of CRM470 was commutable with native clinical samples for 14 of 15 hsCRP methods that had acceptable precision. For those methods the use of PRM may contribute to improved harmonization of results for native clinical samples.

An overview of inflammatory markers in type 2 diabetes from the perspective of the clinical chemist.

C-reactive protein (CRP), when measured by a highly sensitive method, is a measure of lowgrade, chronic inflammation and is an independent risk factor for type 2 diabetes (T2D) and cardiovascular disease (CVD). CRP also has the capacity to interact with other risk factors to increase the risk for T2D and CVD. Population distributions divided into tertiles provide the capacity to predict onset of T2D and associated CVD. Preanalytical as well as analytical sources of variation in high-sensitivity CRP (hsCRP) measurements need to be standardized in order for CRP results to be optimally useful. The Centers for Disease Control and Prevention and the American Heart Association have issued guidelines for clinical usefulness of hsCRP measurements. The Centers for Disease Control and Prevention has taken steps to standardize hsCRP assays by evaluating secondary reference materials to be used by manufacturers to calibrate their assays.

Variability among five over-the-counter blood glucose monitors.

BACKGROUND: The American Diabetes Association recommends that people with diabetes use self-monitoring to control their blood glucose concentration. To assess the need for standardization, we evaluated the variability among 5 of the most common monitors: MediSense Precision Xtra, Ascencia Dex, Prestige Smart System, OneTouch Ultra, and Accu-Chek Advantage. METHODS: We took steps to minimize preanalytical variation. We also eliminated user variability by using one trained operator to collect samples and perform all testing. Each monitor was used twice with each participant; one test was performed using an aged strip and the other using a fresh strip. We compared monitors using a separate ANOVA for each concentration range and strip lot. RESULTS: The total CVs and the within-strip lot CVs were not statistically different among monitors, ranging from 3.1% to 11.3% and from 2.1% to 8.5%, respectively. There were statistically significant differences among monitors for among-strip lot CVs, which ranged from nearly 0% to 7.5%. The degree of significance increased as the concentration range increased [3.9-5.5 mmol/l: p<0.05; 5.6-7.7 mmol/l: p =0.003; 7.8-11.1 mmol/l: p < 0.001]. The average percent difference between monitor pairs was statistically significant (p < 0.05) in more than half of the paired comparisons, with significant differences ranging from 5.7% to 32.0%. CONCLUSIONS: Monitor results can vary significantly so that agreement among them is poor. Standardization is necessary to minimize variability and to improve patient care.

Standardization of immunoassays for measurement of high-sensitivity C-reactive protein. Phase I: evaluation of secondary reference materials.

BACKGROUND: Inflammation contributes to the development and progression of atherosclerosis, and C-reactive protein (CRP) can be used as a marker to assess risk for cardiovascular diseases. As variability among existing high-sensitivity CRP (hsCRP) assays can lead to misclassification of patients and hamper implementation of population-based medical decision points, standardization of hsCRP assays is needed. METHODS: We evaluated five proposed secondary reference materials, including two diluted preparations of Certified Reference Material 470 (CRM470), two preparations of a serum-based material with recombinant CRP added, and one serum-based material with isolated CRP added. Twenty-one manufacturers participated in the comparison with 28 different assays. We examined imprecision, linearity, and parallelism with these materials and with fresh serum. RESULTS: All materials had similar imprecision; CVs for the undiluted materials were 2.1-3.7%. None of the materials was linear across all assays. Each had between one and three cases of nonlinearity, with one preparation of CRM470 having the fewest cases of nonlinearity. Although none of the materials was parallel across all assays, the differences in slope from fresh serum were similar across all assays. CONCLUSIONS: All materials performed similarly with regard to imprecision, linearity, and parallelism. As one preparation of CRM470 had slightly better characteristics than the other materials and because CRM470 had been certified previously as a reference material for the acute-phase reactant range, it will be used in the next phase to standardize hsCRP assays.

The effects of errors in lipid measurement and assessment.

Accurate cholesterol and lipoprotein measurements have provided dependable and powerful basic risk factors for cardiovascular disease. A battery of total cholesterol (TC), high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, and triglycerides (TG) is recommended in the initial evaluation for classification of patients (based on lipids) into highly desirable, desirable, borderline, high, and very high lipid risk factor for cardiovascular disease. Treatment is based largely on the LDL cholesterol measurement result of the patient. The risk factor score of a patient greatly increases when other risk factors for cardiovascular disease exist, along with increased lipid risk factors. Attainment of the needed acceptable accurate lipid and lipoprotein measurements depends upon prevention or control of multiple sources of errors or variation that can exist in preanalytic, analytic, and postanalytic stages of determination of the reported result. Highly important is to control nonfasting, posture, diet, and alcohol intake in the preanalytic part, elimination of matrix effects and use of accurate calibrators in the analytic part, and check for transcription errors in preparation of reports in the postanalytic part of the measurement of lipids.