Impact of haemoglobin variants on the diagnostic sensitivity of glycated haemoglobin (HbA1c) assay methodologies in sub-Saharan Africa: a laboratory-based method validation study

Abstract

Introduction: the utility of glycated haemoglobin (HbA1c) for the diagnosis and monitoring of diabetes in sub-Saharan Africa is uncertain due to limited data on the performance of the available HbA1c assay methods in this population, which has a high prevalence of haemoglobin variants. We aimed to compare the diagnostic accuracy of the major HbA1c methodologies (Boronate Affinity, Capillary Electrophoresis, High Performance Liquid Chromatography, Immunoassay) in an African population, and assess the impact of the common haemoglobin variant HbAS (sickle cell trait).

Methods: whole blood samples were obtained from 182 individuals living with type 2 diabetes in Uganda. HbA1c values for each method were compared to average glucose measured over 14 days by continuous glucose monitoring (CGM). To determine concordance, the three HbA1c assay methods were compared to the capillary electrophoresis method.

Results: there was a strong correlation between CGM average glucose levels and all four HbA1c methodologies (r=0.81-0.89) which did not differ in those with and without HbAS (present in 37/182 participants). The presence of HbAS did not alter the relationship between HbA1c and CGM glucose for any assay (p for interaction >0.2 for all methods). Diagnostic accuracy for CGM average glucose thresholds of 7 and 10mmol/L was similar across methods (area under the receiver operating characteristic curve 0.80-0.84 and 0.76-0.84 respectively). The maximum bias between the HbA1c assay methodologies was 2 mmol/mol (2.07%).

Conclusion: all major HbA1c technologies offer accurate and comparable HbA1c measurement even in this population with high prevalence of haemoglobin variants.

Keywords: Glycated haemoglobin (HbA1c); HbA1c methodologies; continuous glucose monitoring; haemoglobin variants.

Figure 1

sample testing flow chart of studies on the impact of haemoglobin variants on accuracy of HbA1c results when compared to average glucose CGM results and diagnostic accuracy studies between the index methodologies being compared to a reference method

Figure 2

correlation graphs between the average CGM glucose results(mmol/L) and HbA1c(mmol/mol) of the different methodologies with a positive association represented by “R” and grey area representing 95% confidence interval for A) HPLC; B) capillary electrophoresis; C) Immunoassay; D) boronate affinity

Figure 3

correlation graphs each having the Pearson correlation coefficients (R) value, between the average CGM glucose results(mmol/L) and different HbA1c methodologies (mmol/mol); A) HPLC, B) capillary electrophoresis, C) immunoassay, D) boronate affinity split by haemoglobin types “HbA and HbAS” whereby the circle represents the HbA type haemoglobin and triangle represents the HbAS

Figure 4

Bland Altman plots for A) HPLC B) immunoassay C) boronate affinity in comparison to capillary electrophoresis HbA1c method; the two straight lines represent the limits of agreement at 95%, and the dashed line represents the mean difference between the methods Supplementary data

Figure 5

correlation graphs with a Pearson correlation coefficient (r) value at 95% confidence interval between the fasting blood glucose(mmol/L) and HbA1c methodologies(mmol/mol) A) HPLC; B) capillary electrophoresis; C) immunoassay; D) boronate affinity