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Clinical Chemistry 48: 1955-1962, 2002;
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Right arrow Lipids, Lipoproteins, and Cardiovascular Risk Factors
(Clinical Chemistry. 2002;48:1955-1962.)
© 2002 American Association for Clinical Chemistry, Inc.

Effect of Analytical Error on the Assessment of Cardiac Risk by the High-Sensitivity C-Reactive Protein and Lipid Screening Model

John Middleton1

1 Department of Clinical Chemistry Development, Beckman Coulter Inc., 200 S. Kraemer, Brea, CA 92821. Fax 714-961-3740; e-mail Jsmiddleton{at}beckman.com.

Background: Several prospective epidemiologic studies have demonstrated that high-sensitivity C-reactive protein (hsCRP) is an effective serum marker for cardiac risk assessment. When hsCRP is considered in conjunction with traditional lipid screening, its clinical utility is further increased. In this report, hsCRP, HDL-cholesterol (HDLC), and total cholesterol (TC) assay imprecision is evaluated in terms of the impact on the cardiac risk assessment process.

Methods: Cardiac risk assessment events were simulated using software written in Visual Basic for Applications with Microsoft Excel. Representative sets of analyte concentrations were used for true patient cardiac marker values. Monte Carlo simulations about the marker values were run using assay SD estimates based on College of American Pathologists surveys and journal articles.

Results: Risk distributions for reasonable assay imprecision showed clinically significant variation. Estimated relative risks of cardiovascular disease using the Ridker–Rifai quintile model varied by as much as 2.5-, 3.5-, and 6-fold for conditions of low, medium, and high laboratory test imprecision, respectively. The true relative risks were underestimated by >25% in 3%, 6.7%, and 10.5% of cases under conditions of low, medium, and high laboratory test imprecision, respectively, and overestimated by >25% in 4.4%, 8.5%, and 11.1% of cases under those conditions.

Conclusions: Use of the Monte Carlo simulation method as a tool to assess the impact of analytical variation on the clinical decision-making process is valuable. From this analysis, it is shown that multiple measurements of HDLC may reduce misclassifications that result from assay imprecision. This is most important when using HDLC assays that include sample preparation with 500 000 molecular weight dextran sulfate. For these assays the total assay method SDs are higher than for other assay methods. In addition, as demonstrated by a propagation of error analysis, HDLC has the largest component of overall error in the relative risk estimate. Under conditions of typical TC and hsCRP assay performance, replication of these assays is less important.




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