Improving the Bias of Comparator Methods in Analytical Performance Assessments Through Recalibration

Abstract

Background: In analytical performance studies, the choice of comparator method plays an important role, as studies have shown that there exist relevant systematic differences (bias) between laboratory analyzers. The feasibility of retrospective recalibration of measurement results through comparison with methods or materials of higher metrological order to minimize bias was therefore assessed. Method: Existing data from performance studies of continuous and blood glucose monitoring systems were retrospectively analyzed. Comparison with a higher-order method was performed for two different data sets. In both cases, subject samples were measured, and a subset was also measured on a higher-order method. Recalibration based on higher-order materials (standard reference material [SRM]) was conducted for two different data sets containing results from SRM and subject samples. Linear regression analysis was performed for each device separately. Resulting equations were applied to the respective complete data set of subject samples. Bias between devices in a data set across all subject samples was assessed before and after recalibration. Results: Bias between devices was reduced from −3.6% to +0.6% in one data set and from +11.0% to +0.3% in the other by recalibration based on higher-order method. Using higher-order materials, bias was also reduced by recalibration, but mixed results were found: Bias was reduced from −3.1% to −0.1% in one data set and from −4.3% to −2.7% in the other. Conclusions: Recalibration did lead to a decrease in bias and thus can reduce the impact of the choice of comparator method. The procedure should be verified in a prospectively designed setting.

CGM accuracy: Contrasting CE marking with the governmental controls of the USA (FDA) and Australia (TGA): A narrative review

“…Whereas a factory calibrated CGM device using venous glucose results for their algorithm should use a venous serum glucose measure, such as Yellow Spring Instrument (YSI) as the reference. Of note, Pleus et al 30 showed experimentally that BGM devices have analytical bias exceeding the acceptable levels defined in the Diabetes Laboratory Analysis Guidelines 46 . Pleus et al 30 also reported the analytical bias of the YSI analyser is above the optimal level 30 .…”

“…Of note, Pleus et al 30 showed experimentally that BGM devices have analytical bias exceeding the acceptable levels defined in the Diabetes Laboratory Analysis Guidelines 46 . Pleus et al 30 also reported the analytical bias of the YSI analyser is above the optimal level 30 . However, by using higher‐order mass spectrometry glucose readings to recalibrate retrospectively, the analytical bias of the YSI analysers and BGM devices reduced to optimal levels 30 .…”

“…Pleus et al 30 also reported the analytical bias of the YSI analyser is above the optimal level 30 . However, by using higher‐order mass spectrometry glucose readings to recalibrate retrospectively, the analytical bias of the YSI analysers and BGM devices reduced to optimal levels 30 . This new understanding presents a challenge when interpreting existing CGM accuracy studies while offering recalibration as a solution for the future.…”

“…Therefore, the IFCC Working group on CGM may provide the solution 38 . Once the IFCC team have established traceability, they aim to provide analytical performance criteria and standards along with statistical 10 and recalibration 30 methodologies to ensure consistency and validity. In lieu of the future publication of the ISO standards for CGM systems, we offer an overview of considerations for study design, point accuracy reporting, and point accuracy performance informed by the POCT05, 5 the iCGM criteria 43 and the discussion within this narrative review (Figure 2).…”

“…However, the performance standards will need to be lowered for non-adjunctive F I G U R E 2 Overview regarding an approach to evaluate design, reporting and performance of a CGM accuracy study critically. §Reference glucose readings from an accurate glucose analyser such as Yellow Spring Instrument or blood glucose monitor with readings recalibrated using a glucose measurement from a higher order method (mass spectrometry) 30 . †Paediatric performance data are required to be comparable.…”