Long-term analytical performance of apixaban measurements based on external quality assessment data.

Objectives

Although direct oral anticoagulants (DOACs) do not usually require monitoring and clinical cut-off values are not well established yet, measurement of apixaban is often requested in emergency settings and may be requested for patients with suspected variable pharmacokinetics. For safe interpretation, results must be comparable between laboratories and platforms. Most external quality assessment (EQA) schemes, however, only provide short-term performance data. This study aimed to assess the long-term analytical performance of apixaban assays using multicenter EQA data and to identify sources of analytical variation.

Methods

Anonymized data from the ECAT program were analyzed. Twice yearly, two lyophilized citrate plasma samples (apixaban range 24-413 ng/mL) were distributed. Consensus values were established, and linear regression of individual laboratory results versus consensus values was performed to calculate slope, intercept, and standard error. Total error, random error, bias (constant and proportional), long-term coefficient of variation (LCVa), and analytical critical difference (ACD) were determined. The effect of platform uniformity was also evaluated.

Results

Data from 233 laboratories representing 238 method-reagent-calibrator combinations met inclusion criteria. Consensus coefficients of variation were < 10% above 50 ng/mL but increased at lower concentrations, reaching 24.6%. Mean total error was 16.8% and was mainly driven by random error (10.7%). Mean total bias was 33.1 ng/mL, predominantly proportional. The median LCVa was 5% (range 1.7-19.9%), and the median ACD was 34.2 ng/mL. Uniform platforms (same-manufacturer equipment, method, and calibrator) showed significantly lower LCVa and ACD than partially or non-uniform platforms.

Conclusions

Apixaban assays demonstrate good long-term precision despite methodological heterogeneity. Proportional bias is the primary source of deviation. Platform harmonization improves reproducibility.