Kinetic Approach Extends the Analytical Measurement Range and Corrects Antigen Excess in Homogeneous Turbidimetric Immunoassays. (19th November 2019)

• Record Type: Journal Article
• Authors: Zaydman, Mark A; Brestoff, Jonathan R; Logsdon, Nicole; Gronowski, Ann M
• Is Part Of: Journal of applied laboratory medicine. Volume 4:Number 2(2019)
• Page Start: 214
• Page End: 223
• Publication Date: 2019-11-19
• Subjects: Clinical chemistry -- Periodicals; Diagnosis, Laboratory -- Periodicals; 616.0756
• DOI: 10.1373/jalm.2019.029256
• Languages: English
• ISSNs: 2576-9456

Abstract

Abstract: Background: Homogeneous turbidimetric immunoassays are widely used in the clinical laboratory and offer short assay times, reduced reagent costs, and the potential for full automation. However, these assays have a limited analytical measurement range (AMR) above which antigen excess leads to falsely low estimates of the analyte concentration (i.e., the hook effect). Traditional methods for correction of antigen excess require sample dilution, compromising time and cost-efficiency. Therefore, novel methods that extend the AMR are needed. Methods: A kinetic model of a generic homogeneous turbidimetric immunoassay was built and then parameterized using a genetic algorithm. Kinetic features that could be used to extend the AMR were identified and subsequently validated with clinical data from consecutive measurements of 2 homogeneous turbidimetric immunoassays: κ serum free light chain and rheumatoid factor. Results: A novel kinetic parameter, the area under the curvature (AUCU), was derived that increases in proportion to the analyte concentration in a range beyond the AMR of conventional end point methods. When applied to clinical data, the AUCU method provided a log-linear calibration curve in the zone of antigen excess extending the AMR by >10-fold for 2 different immunoassays. Conclusions: The AUCU method detects and corrects antigen excess, extending the AMR in homogeneous turbidimetric immunoassays. The advantage of this method over conventional methods would be a reduction in the number of repeated samples, resulting in significant time and cost savings.