Assessing precision, bias and sigma-metrics of 53 measurands of the Alinity ci system

Assay performance is dependent on the accuracy and precision of a given method. These attributes can be combined into an analytical Sigma-metric, providing a simple value for laboratorians to use in evaluating a test method's capability to meet its analytical quality requirements. Sigma-metrics were determined for 37 clinical chemistry assays, 13 immunoassays, and 3 ICT methods on the Alinity ci system.

Analytical Performance Specifications were defined for the assays, following a rationale of using CLIA goals first, then Ricos Desirable goals when CLIA did not regulate the method, and then other sources if the Ricos Desirable goal was unrealistic. A precision study was conducted at Abbott on each assay using the Alinity ci system following the CLSI EP05-A2 protocol. Bias was estimated following the CLSI EP09-A3 protocol using samples with concentrations spanning the assay's measuring interval tested in duplicate on the Alinity ci system and ARCHITECT c8000 and i2000_SR systems, where testing was also performed at Abbott. Using the regression model, the %bias was estimated at an important medical decisions point. Then the Sigma-metric was estimated for each assay and was plotted on a method decision chart. The Sigma-metric was calculated using the equation: Sigma-metric=(%TEa-|%bias|)/%CV.

The Sigma-metrics and Normalized Method Decision charts demonstrate that a majority of the Alinity assays perform at least at five Sigma or higher, at or near critical medical decision levels.

More than 90% of the assays performed at Five and Six Sigma. None performed below Three Sigma. Sigma-metrics plotted on Normalized Method Decision charts provide useful evaluations of performance. The majority of Alinity ci system assays had sigma values >5 and thus laboratories can expect excellent or world class performance. Laboratorians can use these tools as aids in choosing high-quality products, further contributing to the delivery of excellent quality healthcare for patients.