Strongest correlation of HbA(1c) with 1-month-earlier glucose levels in type 2 diabetes

The correlation of hemoglobin A1c to blood glucose

The understanding that hemoglobin A1c (HbA1c) represents the average blood glucose level of patients over the previous 120 days underlies the current management of diabetes. Even in making such a statement, we speak of "average blood glucose" as though "blood glucose" were itself a simple idea. When we consider all the blood glucose forms-arterial versus venous versus capillary, whole blood versus serum versus fluoride-preserved plasma, fasting versus nonfasting-we can start to see that this is not a simple issue. Nevertheless, it seems as though HbA1c correlates to any single glucose measurement. Having more than one measurement and taking those measurements in the preceding month improves the correlation further. In particular, by having glucose measurements that reflect both the relatively lower overnight glucose levels and measurements that reflect the postprandial peaks improves not only our ability to manage diabetes patients, but also our understanding of how HbA1c levels are determined. Modern continuous glucose monitoring (CGM) devices may take thousands of glucose results over a week. Several studies have shown that CGM glucose averages account for the vast proportion of the variation of HbA1c. The ability to relate HbA1c to average glucose may become a popular method for reporting HbA1c, eliminating current concerns regarding differences in HbA1c standardization. Hemoglobin A1c expressed as an average glucose may be more understandable to patients and improve not only their understanding, but also their ability to improve their diabetes management.

Interindividual divergence in the relationship between the values of plasma glucose and hemoglobin A1c in type 2 diabetes

OBJECTIVE

To verify the relationships between the values of plasma glucose (PG) and hemoglobin A(1c)(HbA(1c)) in type 2 diabetic outpatients.

METHODS

The pre- and postbreakfast PG and HbA(1c) values were monitored every month for 44-90 months. The single regression lines between the values of PG and HbA(1c) were compared for the slopes and intercepts on the designated ordinates of the regression lines.

PATIENTS OR MATERIALS

Nine patients of type 2 diabetes not treated with insulin: three males and six females, aged 43-79 years participated.

RESULTS

The HbA(1c) level was combined with the pre- and postbreakfast PG values obtained at one month prior to its determination, because the combinations were correlated most strongly. The slopes of the regression line ranged from 0.33-0.50%/mmol/L and the intercepts at PG level equal to 9.6 mmol/L ranged from 6.95-9.77% in the relationship between the values of 1-month earlier prebreakfast PG and HbA(1c). Twenty-eight pairs had significantly different intercepts. Meanwhile, there was no pair that had significantly different slopes. Similar results were obtained in the relationship between the values of 1-month earlier postbreakfast PG and HbA(1c).

CONCLUSION

There was interindividual divergence of the regression lines which was due to the difference in the intercepts but not the slopes.

Hemoglobin A1c (HbA1c) predicts future drug treatment for diabetes mellitus: a follow-up study using routine clinical data in a Japanese university hospital

Hemoglobin A1c (HbA1c) has been widely used as a measure of glycemic control in patients with diabetes mellitus. However, the role of HbA1c in the prediabetic stage has received little attention, although the effectiveness of early intensive intervention for the prediabetic patients defined by plasma glucose is well documented. In this study, routine clinical data in a Japanese university hospital were used to address whether the level of HbA1c predicted drug treatment for diabetes mellitus. The study population consisted of 38,628 adolescent and adult patients (>or=15 years old) who used routine medical care services provided by the hospital and who were prescribed no anti-diabetic drugs in the 12 months before the 3-year study period. The rates of starting anti-diabetic drugs during the study period were calculated for subgroups divided by the level of HbA1c followed by Kaplan-Meier survival analysis and Cox proportional-hazard regression. In addition, the medical records of middle-aged patients with borderline (5.6-6.4%) and high (>or=6.5%) levels of HbA1c were examined to estimate the rates of initial drug treatment for type 2 diabetes mellitus. The rate (95% confidence interval; CI) of beginning anti-diabetic drug therapy was 1.5 (0.9-2.5)/1000 patient-years in patients with a normal level of HbA1c (<5.6%), which is similar to 2.1 (1.8-2.5)/1000 patient-years in patients with no HbA1c data, but lower than the value of 23.0 (18.6-28.6) and 161.8 (144.8-180.7)/1000 patient-years in those with borderline and high levels of HbA1c, respectively (P < 0.001). In a small group of 513 middle-aged patients, the rates of initial drug treatment for type 2 diabetes mellitus were 39.4 (28.1-55.1)/1000 patient-years and 270.4 (209.4-349.0)/1000 patient-years in those with borderline and high levels of HbA1c, respectively. A borderline (5.6-6.4%) or high (>or=6.5%) level of HbA1c was found to strongly predict future drug treatment for diabetes mellitus.

Assessment of the relationship between glucose and A1c using kinetic modeling

Treatment goals for diabetic patients are directed towards lowering A1c values by controlling blood glucose concentrations (BGC), making it important to understand the relationship between the two parameters. Because findings from clinical trials about the relationship between BGC and A1c values show a profound variability around the obtained regression lines, they are difficult to apply to individual patients. Therefore, a model was developed and applied based on the kinetics of HbA1c formation and removal. It takes the instability of A1c and loss of hemoglobin into consideration. Data from clinical studies and hypothetical scenarios were used to test the model and to describe the relationship between A1c and BGC. A close agreement between experimental and calculated data was obtained in steady-state and non-steady-state conditions. Aside the erythrocyte life span, the chemical instability of A1c appears to affect A1c levels markedly and their changes due to therapy. A threefold increase in BGC over 30 days prior to A1c measurement can cause an increase in A1c value of about 120% as compared with 4% when it occurs 4 months prior to A1c measurement. Profound daily fluctuations in BGC result in minor changes in A1c. In conclusion, A1c provides information about a patient's glycemia, mainly over the past 2 months, and may not reflect well daily blood glucose fluctuations. This model might be suitable to identify individual differences in glycation rates.