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Clinical significance of inter-assay discrepancies in serum CA19-9 values: A comparison between CLIA and ECLIA
Ling Zhang1, Yuichiro Uchida2, Midori Saito2
1Fujita Nurse Practitioner Office, Fujita Health University Hospital, Toyoake, Aichi, Japan.
Abstract:
BackgroundSerum carbohydrate antigen 19-9 (CA19-9) is widely used in the management of pancreatic diseases, but results often vary across immunoassay platforms. This study sought to describe how the values obtained by chemiluminescent immunoassay (CLIA) and electrochemiluminescent immunoassay (ECLIA) differ, to assess whether discrepancies vary across concentration ranges, and to identify clinical factors potentially contributing to this variability.MethodsWe examined 1,760 paired samples measured simultaneously by CLIA (Abbott Alinity i) and ECLIA (Roche Cobas e801) during a transition period. To assess agreement between assays, correlation analysis, Passing-Bablok regression, and Bland-Altman analysis were performed on log10-transformed data.Subgroup comparisons were made by CA19-9 concentration, disease category, and hepatobiliary enzyme status. Multivariable regression was used to explore independent factors associated with the magnitude of inter-assay differences.ResultsCorrelation between CLIA and ECLIA was strong (r = 0.94, ρ = 0.89) although a concentration-dependent bias was observed with CLIA yielding higher values at higher concentrations, whereas ECLIA tended to yield higher values at lower concentrations. Discrepancies were greater in pancreatic cancer samples in those with elevated ALP or γ-GT, and at higher concentrations (CLIA ≥ 1000 U/mL). Older age, female sex, pancreatic cancer, and elevated hepatobiliary enzymes were independently associated with larger assay differences (adjusted R2 = 0.13).ConclusionsDespite good overall agreement, the two methods showed variability that could affect clinical interpretation, especially in low or high concentration ranges. When assay changes are unavoidable, using method-specific reference ranges or confirming results near decision thresholds may help ensure consistent interpretation.
