Evaluation of procalcitonin immunoassay concordance near clinical decision points.

Clin Chem Lab Med

Department of Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, Nashville, TN, USA.

Published: August 2019

AI Article Synopsis

  • Procalcitonin (PCT) is a key biomarker used to guide decisions in treating systemic bacterial infections, but there's still uncertainty about the consistency across different PCT assays.
  • A study analyzed 37 patient serum samples using four PCT assays and found significant differences in how results were classified at critical decision points for antimicrobial therapy, particularly compared to the BRAHMS KRYPTOR method.
  • The findings suggest that while the assays generally align, many samples could be classified differently among methods, highlighting the urgent need for standardization of PCT testing to ensure reliable clinical interpretations.

Article Abstract

Background Procalcitonin (PCT) is a biomarker for systemic bacterial infections and may aid in decision making for antimicrobial stewardship. Numerous PCT assays are available on common clinical immunoassay platforms. However, questions remain about the harmonization of these assays and whether the same clinical decision points may be used with all methods. Methods Thirty-seven remnant patient serum samples were analyzed across four different PCT assays: Abbott ARCHITECT i2000, bioMérieux MINI VIDAS, Roche Elecsys cobas e 411, and BRAHMS KRYPTOR. Regression analysis was performed, and correlation was assessed at common clinical decision points for antimicrobial therapy: 0.10, 0.25, and 0.50 μg/L. Results Data showed a positive bias of the MINI VIDAS compared to the KRYPTOR (slope=1.188, R=0.9873) and negative biases of both the ARCHITECT i2000 and cobas e 411 compared to the KRYPTOR (slope=0.806, R=0.8864, and slope=0.795, R=0.8974, respectively). A comparison of results at commonly used clinical decision points for antimicrobial stewardship showed that, relative to the KRYPTOR, 21% of samples would be classified into different interpretive categories by the ARCHITECT i2000 method, 31% of samples would be classified differently by the MINI VIDAS method, and 16% of samples would be classified differently by the cobas e 411 method. Conclusions All methods showed reasonable analytical agreement; however, an analysis of result interpretation at clinical decision points showed that many samples were differentially categorized (e.g. shifted by one interpretive category) by the methods. Overall, our findings support a need for harmonization of PCT methods. Until then, institutions should independently evaluate their PCT assays against predicate methods and consider the impact on result interpretation prior to incorporating PCT into clinical practice.

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Source
http://dx.doi.org/10.1515/cclm-2018-1362DOI Listing

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