A new approach for clinical biological assay comparison and standardization: application of principal component analysis to a multicenter study of twenty-one carcinoembryonic antigen immunoassay kits

Abstract

Background: Principal component analysis (PCA) is a powerful mathematical method able to analyze data sets containing a large number of variables. To our knowledge, this method is applied here for the first time in the field of medical laboratory analysis.

Methods: PCA was used to evaluate the results of a blind comparative study of 21 carcinoembryonic antigen (CEA) reagent kits used to determine CEA concentration in a panel of sera from 80 patients.

Results: The mathematical technique first eliminated the variations attributable to the use of different calibrators. The PCA representation then gave a global view of the dispersion of the kits and allowed the identification of a main homogeneous group and of some discrepant kits.

Conclusions: PCA applied to the in vitro diagnostic reagent field could contribute to the standardization process and improve the quality of medical laboratory analyses. A standardization method using a panel of patient sera is proposed.