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

同位素稀释 色谱法 尿 串联质谱法 质谱法 化学 同位素 生物化学 物理 量子力学
作者
Lorin M Bachmann,Göran Nilsson,David E. Bruns,Matthew McQueen,John C. Lieske,Jack Zakowski,W. Greg Miller
出处
期刊:Clinical Chemistry [American Association for Clinical Chemistry]
卷期号:60 (3): 471-480 被引量:63
标识
DOI:10.1373/clinchem.2013.210302
摘要

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.
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