Wilson et al. (1) recently used continuous glucose monitoring (CGM) to estimate mean blood glucose (MG) and calculate an MG-to-HbA1c ratio to assess biological variation in HbA1c in pediatric type 1 diabetic patients. The authors reported that patients with relatively low or high ratios at one clinic visit tended to have similarly low or high ratios at subsequent visits. The same group previously used CGM-derived MG to calculate the hemoglobin glycation index (HGI) as a measure of biological variation in HbA1c (2). Their results showed that HGI was quantitatively consistent within individuals at baseline and at follow-up clinic visits. This observation confirmed prior reports of HGI consistency within patients over time where MG was estimated using less advanced technologies such as patient blood glucose meter data or timed glucose profile sets (3,4). Because CGM is widely accepted as the gold standard for directly estimating MG, the studies by Wilson et al. both strongly suggest that interindividual variation in HGI is not an artifact of interindividual bias in blood glucose measurement.

Although their MG-to-HbA1c ratio results provide further evidence of phenotypic consistency within individuals over time, the authors did not explain why they switched from HGI to the ratio. When our group first developed the HGI (3), we considered but decided against the use of ratios for assessing biological variation in HbA1c for the following reasons: First, ratios subsume all effects into one statistic which makes it more difficult to inherently grasp the relationship between the two directly measured metrics, especially if the relationship is nonlinear as is the case for MG-to-HbA1c ratio versus MG or HbA1c. It is also more difficult to statistically work with variances of ratios than variances of the metrics that make up the ratio. Without a reference range, the ratio is relatively uninformative. In contrast, glycation indices such as HGI and the glycation gap (GG) of Cohen et al. (5) automatically provide clinicians with a meaningful and easily remembered reference point because both are approximately normally distributed in human populations with a mean of zero (35). HGI and GG are calculated as the difference between an individual's observed HbA1c and a predicted HbA1c calculated by inserting either the subject's date-matched MG (for HGI) or fructosamine (for GG) into the population linear regression equation for HbA1c versus MG or fructosamine. Because of how they are calculated, HGI and GG measure HbA1c controlled for MG or fructosamine, respectively. HGI and GG not only provide an immediately recognizable reference point, they also reflect the relative direction (negative or positive) and magnitude of each individual's HbA1c response. An HGI or GG greater than zero indicates a tendency for higher than average HbA1c independent of the effects of MG or fructosamine. Values lower than zero indicate a tendency for lower than average HbA1c. Ratios do not provide these same inherent advantages. We suggest that compared with ratios, HGI and GG are superior metrics of biological variation in HbA1c and recommend their use in future studies of this phenomenon and its impact on diabetes diagnosis and management.

No potential conflicts of interest relevant to this article were reported.

1.
Wilson
DM
,
Xing
D
,
Cheng
J
, et al
;
Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group
.
Persistence of individual variations in glycated hemoglobin: analysis of data from the Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Randomized Trial
.
Diabetes Care
2011
;
34
:
1315
1317
2.
Wilson
DM
,
Kollman
C
,
Xing
D
, et al
;
Diabetes Research in Children Network (DirecNet) Study Group
.
Relationship of A1C to glucose concentrations in children with type 1 diabetes: assessments by high-frequency glucose determinations by sensors
.
Diabetes Care
2008
;
31
:
381
385
3.
Hempe
JM
,
Gomez
R
,
McCarter
RJ
 Jr
,
Chalew
SA
.
High and low hemoglobin glycation phenotypes in type 1 diabetes: a challenge for interpretation of glycemic control
.
J Diabetes Complications
2002
;
16
:
313
320
4.
McCarter
RJ
,
Hempe
JM
,
Gomez
R
,
Chalew
SA
.
Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes
.
Diabetes Care
2004
;
27
:
1259
1264
5.
Cohen
RM
,
Holmes
YR
,
Chenier
TC
,
Joiner
CH
.
Discordance between HbA1c and fructosamine: evidence for a glycosylation gap and its relation to diabetic nephropathy
.
Diabetes Care
2003
;
26
:
163
167
Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.