An improved approach to modelling patient reclassification: HbA 1c as an example

Abstract Background External quality assurance (EQA) programs must assess whether the analytical performance of commonly used in vitro diagnostic (IVD) devices is fit for their intended clinical use. We developed a method for this assessment based on reclassification of results at clinical decision limits and applied it to results from a haemoglobin A 1c (HbA 1c ) EQA program. Content Using a commutable EQA program to provide analytical performance characteristics, we simulated 10,000 measurements of the HbA 1c value of each of 6,326 subjects in the National Health and Nutrition Survey (NHANES) by common IVD devices and the NHANES device. A parametric empirical Bayes approach was used to account for regression to the mean. We estimated the rates at which the IVD devices would reclassify results and compared them with the estimated reclassification rate for the NHANES device, calculating the difference between them as the ‘incremental reclassification rate’ (IRR). IRRs were ‘optimal’ if