Lorin M. Bachmann

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 manufacturers 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.

Specificity Characteristics of 7 Commercial Creatinine Measurement Procedures by Enzymatic and Jaffe Method Principles

BACKGROUND Standardized calibration does not change a creatinine measurement procedures susceptibility to potentially interfering substances. METHODS We obtained individual residual serum or plasma samples (n = 365) from patients with 19 different disease categories associated with potentially interfering substances and from healthy controls. Additional sera at 0.9 mg/dL (80 μmol/L) and 3.8 mg/dL (336 μmol/L) creatinine were supplemented with acetoacetate, acetone, ascorbate, and pyruvate. We measured samples by 4 enzymatic and 3 Jaffe commercially available procedures and by a liquid chromatography/isotope dilution/mass spectrometry measurement procedure against which biases were determined. RESULTS The number of instances when 3 or more results in a disease category had biases greater than the limits of acceptability was 28 of 57 (49%) for Jaffe and 14 of 76 (18%) for enzymatic procedures. For the aggregate group of 59 diabetes samples with increased β-hydroxybutyrate, glucose, or glycosylated hemoglobin (Hb A(1c)), the enzymatic procedures had 10 biased results of 236 (4.2%) compared with 89 of 177 (50.3%) for the Jaffe procedures, and these interferences were highly procedure dependent. For supplemented sera, interferences were observed in 11 of 24 (46%) of groups for Jaffe and 8 of 32 (25%) of groups for enzymatic procedures and were different at low or high creatinine concentrations. CONCLUSIONS There were differences in both magnitude and direction of bias among measurement procedures, whether enzymatic or Jaffe. The influence of interfering substances was less frequent with the enzymatic procedures, but no procedure was unaffected. The details of implementation of a method principle influenced its susceptibility to potential interfering substances.

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 manufacturers 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.

State of the Art for Measurement of Urine Albumin: Comparison of Routine Measurement Procedures to Isotope Dilution Tandem Mass Spectrometry

BACKGROUND Urine albumin is the primary biomarker for detection and monitoring of kidney damage. Because fixed decision criteria are used to identify patients with increased values, we investigated if commonly used routine measurement procedures gave comparable results. METHODS Results from 17 commercially available urine albumin measurement procedures were investigated vs an isotope dilution mass spectrometry (IDMS) procedure. Nonfrozen aliquots of freshly collected urine from 332 patients with chronic kidney disease, diabetes, cardiovascular disease, and hypertension were distributed to manufacturers to perform urine albumin measurements according to the respective instructions for use for each procedure. Frozen aliquots were used for measurements by the IDMS procedure. An error model was used to determine imprecision and bias components. RESULTS Median differences between the largest positive and negative biases vs IDMS were 45%, 37%, and 42% in the concentration intervals of 12-30 mg/L, 31-200 mg/L, and 201-1064 mg/L, respectively. Biases varied with concentration for most procedures and exceeded ± 10% over the concentration interval for 14 of 16 quantitative procedures. Mean biases ranged from -35% to 34% at 15 mg/L. Dilution of samples with high concentrations introduced bias for 4 procedures. The combined CV was >10% for 5 procedures. It was not possible to estimate total error due to dependence of bias on concentration. CVs for sample-specific influences were 0% to 15.2%. CONCLUSIONS Bias was the dominant source of disagreement among routine measurement procedures. Consequently, standardization efforts will improve agreement among results. Variation of bias with concentration needs to be addressed by manufacturers.

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 β 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.

A reference system for urinary albumin: current status

Abstract Background: Increased urinary excretion of albumin reflects kidney damage and is a recognized risk factor for progression of renal and cardiovascular disease. Considerable inter-method differences have been reported for both albumin and creatinine measurement results, and therefore the albumin-to-creatinine ratio. Measurement accuracy is unknown and there are no independent reference measurement procedures for albumin and no reference materials for either measurand in urine. Methods: The National Kidney Disease Education Program (NKDEP) Laboratory Working Group and the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) have initiated joint projects to facilitate standardization of urinary albumin and creatinine measurement. Results: A candidate LC-MS/MS reference measurement procedure for urinary albumin and candidate reference materials for urinary albumin and creatinine has been developed. The status of validations of these reference system components is reported. Conclusions: The development of certified reference materials and reference measurement procedures for urinary albumin will enable standardization of this important measurand.

A Spectrum of Views on Clinical Mass Spectrometry

The June 2009 issue of Clinical Chemistry contained our very first Q&A, which has since become a monthly feature in the journal. In that Q&A we asked 5 experts about mass spectrometry (MS)9 in the clinical laboratory. We wanted to find out where we stood and where we needed to be. Not only has it been nearly 7 years since we first asked about clinical MS, but we have devoted the entire January 2016 issue of Clinical Chemistry to this important technology. In this Q&A we ask 6 experts representing instrument design, research, and the clinical laboratory for their perspectives on where we stand in 2016. We were particularly interested in the challenges instrument manufacturers face in meeting the needs of customers and regulatory agencies, the potential of MS moving toward point-of-care (POC) testing, whether there was a next “big thing” in MS on the horizon, and whether MS had matured to the point that it was becoming a true clinical instrument. As scientists involved in instrument development, what demands are manufacturers facing with new applications or instrument designs? How about regulatory hurdles? Reza Javahery: Increased analytical sensitivity, reproducibility, durability (uptime), and ease of use all continue to be features demanded by users. Thus, we cannot focus on just one of these areas. Serviceability is also a major concern. As far as regulatory hurdles, we are still in an environment where there are no clear guidelines. Bradley Hart: As manufacturers, we are tasked with challenges that include improving ease of use and connectivity to automation and laboratory information systems/laboratory information management systems (LIS/LIMS), handling smaller sample sizes and spot samples, improving sensitivity for challenging applications, translating and enabling clinical omics assessment panels, and ultimately providing solutions that enable customers to deliver personalized and precision medicine. In addition, manufacturers of …

Difference in Bias Approach for Commutability Assessment: Application to Frozen Pools of Human Serum Measured by 8 Direct Methods for HDL and LDL Cholesterol

BACKGROUND We used a difference in bias approach to evaluate the commutability of 4 frozen serum pools for 8 direct methods for measurement of HDL and LDL cholesterol (HDLC and LDLC). METHODS Freshly collected nonfrozen sera from 138 diseased and 37 nondiseased patients and 4 frozen pools from the CDC Lipid Standardization Program were measured by direct methods and by the beta-quantification reference measurement procedure of the CDC. We used an error components model to estimate the difference in the bias component of error plus its uncertainty for frozen pools vs patient samples between the direct method and the reference procedure. Frozen pools with bias differences less than a critical value determined by either medical requirements for bias or the random error components of the measurement procedures were considered commutable. RESULTS On the basis of medical requirement criteria, 1 of the 4 frozen pools was commutable for most of the HDLC methods for both diseased and nondiseased patients, and none was commutable for LDLC methods. On the basis of random error criteria, all of the frozen pools were generally commutable for all of the HDLC methods for both diseased and nondiseased patients, and 1 of the 4 frozen pools was generally commutable for most of the LDLC methods for both diseased and nondiseased patients. CONCLUSIONS Commutability was assessed as the closeness of agreement of the difference in bias between a reference material and a set of patient samples. Criteria for commutability could be based on fixed medical requirements for bias or on random error components.

Baseline Assessment of 25-Hydroxyvitamin D Assay Performance: A Vitamin D Standardization Program (VDSP) Interlaboratory Comparison Study.

The Vitamin D Standardization Program (VDSP) coordinated an interlaboratory study to assess the comparability of measurements of total 25-hydroxyvitamin D [25(OH)D] in human serum, which is the primary marker of vitamin D status. A set of 50 individual donor samples were analyzed by 15 different laboratories representing national nutrition surveys, assay manufacturers, and clinical and/or research laboratories to provide results for total 25(OH)D using both immunoassays (IAs) and LC tandem MS (MS/MS). The results were evaluated relative to bias compared with the target values assigned based on a combination of measurements at Ghent University (Belgium) and the U.S. National Institute of Standards and Technology using reference measurement procedures for the determination of 25(OH)D2 and 25(OH)D3. CV and mean bias for each laboratory and assay platform were assessed and compared with previously established VDSP performance criteria, namely CV ≤ 10% and mean bias ≤ 5%. Nearly all LC-MS/MS results achieved VDSP criteria, whereas only 50% of IAs met the criterion for a ≤10% CV and only three of eight IAs achieved the ≤5% bias. These results establish a benchmark for the evaluation of 25(OH)D assay performance and standardization activities in the future.

Unexpected Test Results in a Patient with Multiple Myeloma

A 53-year-old male patient with an established diagnosis of IgG λ multiple myeloma was seen by a hematologist–oncologist in consultation from an outside hospital. He had previously received 1 cycle of chemotherapy treatment, but he was found to be intermittently noncompliant with his therapy. The patient reported occasional nosebleeds and fatigue. Except for a slightly cachectic appearance, the physical examination was unremarkable. Laboratory results are shown in Table 1. View this table: Table 1. Chemistry and hematology laboratory results. Serum protein electrophoresis revealed monoclonal paraproteinemia in high abundance marked by an intense band in the γ region. Immunofixation electrophoresis was not ordered at that time, but it was previously performed at another institution and was positive for IgG monoclonal protein. The attending pathologist noted the discrepancy between the presence of a monoclonal band by serum protein electrophoresis and the patients quantitative immunoglobulin measurements. Several additional suspicious test results were also noted. Multiple myeloma is a hematologic malignancy characterized by proliferation of a neoplastic plasma cell population that usually leads to abundant production of a monoclonal immunoglobulin, also called paraprotein or M-protein, as well as decreased concentrations of normal polyclonal immunoglobulins. Overwhelming expansion of plasma cells in the bone marrow with concomitant suppression of other normal blood cell lineages often results in thrombocytopenia and anemia, which are classically manifested as symptoms of bleeding and fatigue. Renal insufficiency, as evidenced by increased blood creatinine and blood urea nitrogen concentrations, also may occur and is likely due to filtration of associated monoclonal free light chains, which can cause tubular damage. Serum protein electrophoresis typically yields a discrete band in the γ region, and immunofixation demonstrates the presence of IgG monoclonal protein in over 50% of cases (1). ### QUESTIONS TO CONSIDER 1. What are some expected laboratory results in a patient with multiple myeloma? 2. Which of the patients laboratory test results are unexpected given his diagnosis …