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Background A major objective of the IFCC Task Force on implementation of HbA1c standardization is to develop a model to define quality targets for HbA1c. Methods Two generic models, the Biological Variation and Sigma-metrics model, are investigated. Variables in the models were selected for HbA1c and data of EQA/PT programs were used to evaluate the suitability of the models to set and evaluate quality targets within and between laboratories. Results In the biological variation model 48% of individual laboratories and none of the 26 instrument groups met the minimum performance criterion. In the Sigma-metrics model, with a total allowable error (TAE) set at 5 mmol/mol (0.46% NGSP) 77% of the individual laboratories and 12 of 26 instrument groups met the 2 sigma criterion. Conclusion The Biological Variation and Sigma-metrics model were demonstrated to be suitable for setting and evaluating quality targets within and between laboratories. The Sigma-metrics model is more flexible as both the TAE and the risk of failure can be adjusted to requirements related to e.g. use for diagnosis/monitoring or requirements of (inter)national authorities. With the aim of reaching international consensus on advice regarding quality targets for HbA1c, the Task Force suggests the Sigma-metrics model as the model of choice with default values of 5 mmol/mol (0.46%) for TAE, and risk levels of 2 and 4 sigma for routine laboratories and laboratories performing clinical trials, respectively. These goals should serve as a starting point for discussion with international stakeholders in the field of diabetes.

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Diagnosing and monitoring the treatment of people with diabetes is a global issue and uses considerable resources in laboratories and clinics worldwide. Hemoglobin A1c (HbA1c) has been the mainstay of monitoring glycemic control in people with diabetes for many years and more recently it has been advocated as a diagnostic tool for type 2 diabetes mellitus (T2DM). Good analytical performance is key to the successful use of any laboratory test, but is critical when using the test to diagnose disease, especially when the potential number of diagnoses could exceed 500 million people. Very small variations in bias or increased imprecision could lead to either a missed diagnosis or overdiagnosis of the disease and given the scale of the global disease burden, this could mean erroneous categorization of potentially millions of people. Fundamental to good performance of diagnostic testing is standardization, with defined reference materials and measurement procedures. In this review, we discuss the historical steps to first harmonize HbA1c testing, followed by the global standardization efforts and provide an update on the current situation and future goals for HbA1c testing.