Tze Ping Loh1, Sunil Kumar Sethi2, Moh Sim Wong3, E Shyong Tai4, Shih Ling Kao4. 1. Department of Laboratory Medicine, National University Hospital, Singapore. Electronic address: tploh@hotmail.com. 2. Department of Laboratory Medicine, National University Hospital, Singapore. 3. Department of Laboratory Medicine, Khoo Teck Puat Hospital, Singapore. 4. Department of Medicine, National University Hospital, Singapore.
Abstract
OBJECTIVES: The relationship between glycated hemoglobin A1c (HbA1c) and average glucose has been described by the empirically derived estimated average glucose (eAG) equation in the A1c-Derived Average Glucose (ADAG) study, with extensive calibration efforts in four secondary reference HbA1c methods. It is not known if this relationship is preserved when HbA1c is measured by routine laboratory methods under routine conditions. DESIGN AND METHODS: We measured average glucose (mAG) by six days of continuous glucose monitoring in 45 adults with stable HbA1c (<1% HbA1c change in the preceding two months). Subjects with medical conditions that may confound HbA1c measurement, including anemia and hemoglobinopathy, were excluded. HbA1c was measured using Bio-Rad Variant II (cation-exchange HPLC), Bio-Rad in2it (boronate affinity HPLC) and Roche Tina-quant (immunoassay) methods. RESULTS: The average differences between eAG derived from the routine HbA1c methods and mAG were 10.4% (Variant II), 6.0% (Tina-quant) and 1.0% (in2it). The regression coefficients between the mAG and HbA1c are different between in2it (mAG, mmol/L=0.58 × %HbA1c + 2.3), Tina-quant and Variant II (both mAG, mmol/L=0.66 × %HbA1c + 1.9). However, the 95% confidence intervals of the slope and bias of these methods overlap. The correlation between mAG and HbA1c was greatest when measured using the Variant II (r(2)=0.84), followed by Tina-quant (r(2)=0.82) and in2it (r(2)=0.71). CONCLUSIONS: The relationship between HbA1c and measured average glucose is method-dependent despite improved HbA1c standardization. The differences in relationship may reflect as discrepant eAG and home glucose monitoring results.
OBJECTIVES: The relationship between glycated hemoglobin A1c (HbA1c) and average glucose has been described by the empirically derived estimated average glucose (eAG) equation in the A1c-Derived Average Glucose (ADAG) study, with extensive calibration efforts in four secondary reference HbA1c methods. It is not known if this relationship is preserved when HbA1c is measured by routine laboratory methods under routine conditions. DESIGN AND METHODS: We measured average glucose (mAG) by six days of continuous glucose monitoring in 45 adults with stable HbA1c (<1% HbA1c change in the preceding two months). Subjects with medical conditions that may confound HbA1c measurement, including anemia and hemoglobinopathy, were excluded. HbA1c was measured using Bio-Rad Variant II (cation-exchange HPLC), Bio-Rad in2it (boronate affinity HPLC) and Roche Tina-quant (immunoassay) methods. RESULTS: The average differences between eAG derived from the routine HbA1c methods and mAG were 10.4% (Variant II), 6.0% (Tina-quant) and 1.0% (in2it). The regression coefficients between the mAG and HbA1c are different between in2it (mAG, mmol/L=0.58 × %HbA1c + 2.3), Tina-quant and Variant II (both mAG, mmol/L=0.66 × %HbA1c + 1.9). However, the 95% confidence intervals of the slope and bias of these methods overlap. The correlation between mAG and HbA1c was greatest when measured using the Variant II (r(2)=0.84), followed by Tina-quant (r(2)=0.82) and in2it (r(2)=0.71). CONCLUSIONS: The relationship between HbA1c and measured average glucose is method-dependent despite improved HbA1c standardization. The differences in relationship may reflect as discrepant eAG and home glucose monitoring results.