Performance criteria based on true and false classification and clinical outcomes. Influence of analytical performance on diagnostic outcome using a single clinical component

Abstract

Background: In the general classical model for diagnoses based on a single analytic component, distributions of healthy and diseased are compared and several investigations of varying analytical performance on the percentage of misclassifications have been published. A new concept based on an alternative type of diagnosing, based on sharp decision limits has been introduced in diagnostic guidelines, but only a few publications on investigation of analytical performance have been seen. Methods: The two diagnostic models (bimodal and unimodal) based on natural logarithmic Gaussian distributions are simulated. Results: In the bimodal model it is possible to evaluate the influence of prevalence of disease in combination with varying analytical performances. In the unimodal model the prevalence is pre-decided by the chosen decision limit. In this model the influence of analytical performance is investigated for diagnosing diabetes using haemoglobin A 1c (HbA 1c ), and for patients with high and low risk for coronary heart disease defined by serum-cholesterol concentrations. Conclusions: For HbA 1c the guidelines and recommendations define a maximum inter-laboratory coefficient of variation of 3.5%, but this is in DCCT units (without a true zero-point), so after transformation to IFCC units (which

Evaluation of Bio-Rad D-100 HbA1c analyzer against Tosoh G8 and Menarini HA-8180V

“…Also, these CV values meet the recommendations made by Sacks et al [12] of within-laboratory CV below 2%. The inter-assay CV% estimated was 0.81% (%HbA 1c ) [1.51% (mmol/mol)], an excellent result which meets the criteria required for the determination of HbA 1c [13] , which are higher in IFCC units (mmol/mol) than in NGSP units (% HbA 1c ) [14] .…”