Evaluation of Nine Automated High-Sensitivity C-Reactive Protein Methods: Implications for Clinical and Epidemiological Applications. Part 2
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- 1 March 2001
- journal article
- research article
- Published by Oxford University Press (OUP) in Clinical Chemistry
- Vol. 47 (3) , 418-425
- https://doi.org/10.1093/clinchem/47.3.418
Abstract
C-Reactive protein (CRP) can provide prognostic information about risk of future coronary events in apparently healthy subjects. This application requires higher sensitivity assays than have traditionally been available in the clinical laboratory. Nine high-sensitivity CRP (hs-CRP) methods from Dade Behring, Daiichi, Denka Seiken, Diagnostic Products Corporation, Iatron, Kamiya, Olympus, Roche, and Wako were evaluated for limit of detection, linearity, precision, prozone effect, and comparability with samples from 388 apparently healthy individuals. All methods had limits of detection that were lower than the manufacturers' claimed limit of quantification except for the Kamiya, Roche, and Wako methods. All methods were linear at 0.3-10 mg/L. The Diagnostic Products Corporation, Kamiya, Olympus, and Wako methods had imprecision (CVs) >10% at 0.15 mg/L. The Iatron, Olympus, and Wako methods demonstrated prozone effects at hs-CRP concentrations of 12, 206, and 117 mg/L, respectively. hs-CRP concentrations demarcating each quartile in a healthy population were method-dependent. Ninety-two to 95% of subjects were classified into the same quartile of hs-CRP established by the Dade Behring method by the Denka Seiken, Diagnostic Products Corporation, Iatron, and Wako methods. In contrast, 68-77% of subjects were classified into the same quartile by the Daiichi, Kamiya, Olympus, and Roche methods. No subject varied by more than one quartile by any method. Four of the nine examined hs-CRP methods classified apparently healthy subjects into quartiles of hs-CRP similar to the classifications assigned by the comparison method. Additional standardization efforts are required because an individual patient's results will be interpreted using population-based cutpoints.Keywords
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