Back to Authors

Bruns, David E.

Mayo Clinic

University of Virginia

Citations 4

Restricted IgG-Kappa and Free Alpha-Heavy-Chain Bands in an Asymptomatic 62-Year-Old Man
Yu, Min , Bruns, David E., Katzmann, Jerry A., Silverman, Lawrence M., Murray, David , Yu, Min , Murray, David L.

Clinical Chemistry | January 29, 2018 | Volume: 64 | Issue: 2 | Pages: 265-268

10.1373/clinchem.2016.269050 Get It

State of the Art for Measurement of Urine Albumin: Comparison of Routine Measurement Procedures to Isotope Dilution Tandem Mass Spectrometry
Bachmann, Lorin M, Nilsson, Göran , Bruns, David E., McQueen, Matthew, Zakowski, Jack, Miller, W. Greg , Lieske, John C.

Clinical Chemistry | November 26, 2013 | Volume: 60 | Issue: 3 | Pages: 471-480

10.1373/clinchem.2013.210302 Get It

Abstract 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.
Failure of Current Laboratory Protocols to Detect Lot-to-Lot Reagent Differences: Findings and Possible Solutions
Algeciras‐Schimnich, Alicia , Bruns, David E., Boyd, James C. , Bryant, Sandra C. , Fortune, Kristin La , Grebe, Stefan K., Algeciras-Schimnich, Alicia

Clinical Chemistry | April 17, 2013 | Volume: 59 | Issue: 8 | Pages: 1187-1194

10.1373/clinchem.2013.205070 Get It

BACKGROUND Maintaining consistency of results over time is a challenge in laboratory medicine. Lot-to-lot reagent changes are a major threat to consistency of results. METHODS For the period October 2007 through July 2012, we reviewed lot validation data for each new lot of insulin-like growth factor 1 (IGF-1) reagents (Siemens Healthcare Diagnostics) at Mayo Clinic, Rochester, MN, and the University of Virginia, Charlottesville, VA. Analyses of discarded patient samples were used for comparison of lots. For the same period, we determined the distributions of reported patient results for each lot of reagents at the 2 institutions. RESULTS Lot-to-lot validation studies identified no reagent lot as significantly different from the preceding lot. By contrast, significant lot-to-lot changes were seen in the means and medians of 105 668 reported patient IGF-I results during the period. The frequency of increased results increased nearly 2-fold to a high of 17%, without detectable changes in the underlying patient demographics. Retrospective statistical analysis indicated that lot-to-lot comparison protocols were underpowered and that validation studies for this assay required testing >100 samples to achieve 90% power to detect reagent lots that would significantly alter the distributions of patient results. CONCLUSIONS The number of test samples required for adequate lot-to-lot validation protocols is high and may be prohibitively large, especially for low-volume or complex assays. Monitoring of the distributions of patient results has the potential to detect lot-to-lot inconsistencies relatively quickly. We recommend that manufacturers implement remote monitoring of patient results from analyzers in multiple institutions to allow rapid identification of between-lot result inconsistency.
Current Issues in Measurement and Reporting of Urinary Albumin Excretion
Miller, W. Greg , Bruns, David E., Hortin, Glen L. , Sandberg, Sverre , Aakre, Kristin M. , McQueen, Matthew, Itoh, Yoshihisa, Seccombe, David , Jones, Graham , Bunk, David M. , Narva, Andrew S., Urine, on behalf of the National Kidney Disease Education Program-IFCC Working Group on Standardization of Albumin in, Lieske, John C. , Curhan, Gary C. , Urine, on behalf of the National Kidney Disease Education Program-IFCC Working Group on Standardization of Albumin in, Aakre, Kristin M

Clinical Chemistry | November 21, 2008 | Volume: 55 | Issue: 1 | Pages: 24-38

10.1373/clinchem.2008.106567 Get It

Abstract Background: Urinary excretion of albumin indicates kidney damage and is recognized as a risk factor for progression of kidney disease and cardiovascular disease. The role of urinary albumin measurements has focused attention on the clinical need for accurate and clearly reported results. The National Kidney Disease Education Program and the IFCC convened a conference to assess the current state of preanalytical, analytical, and postanalytical issues affecting urine albumin measurements and to identify areas needing improvement. Content: The chemistry of albumin in urine is incompletely understood. Current guidelines recommend the use of the albumin/creatinine ratio (ACR) as a surrogate for the error-prone collection of timed urine samples. Although ACR results are affected by patient preparation and time of day of sample collection, neither is standardized. Considerable intermethod differences have been reported for both albumin and creatinine measurement, but trueness is unknown because there are no reference measurement procedures for albumin and no reference materials for either analyte in urine. The recommended reference intervals for the ACR do not take into account the large intergroup differences in creatinine excretion (e.g., related to differences in age, sex, and ethnicity) nor the continuous increase in risk related to albumin excretion. Discussion: Clinical needs have been identified for standardization of (a) urine collection methods, (b) urine albumin and creatinine measurements based on a complete reference system, (c) reporting of test results, and (d) reference intervals for the ACR.