Clin Chem Lab Med 2015; 53(1): e15–e17
Letter to the Editor Bogdan Solnica*, Malgorzata Grzanka, Maria Kapusta, Natalia Nowak, Jan Skupien, Krystyna Slowinska-Solnica, Bartlomiej Matejko, Tomasz Klupa and Maciej T. Malecki
Association of retrospective markers of glycemia and the use of continuous glucose monitoring in white adults with type 2 diabetes mellitus – a preliminary report Keywords: 1,5-anhydroglucitol; blood glucose; fructos amine; glycated hemoglobin. DOI 10.1515/cclm-2014-0580 Received June 1, 2014; accepted June 18, 2014; previously published online July 11, 2014
To the Editor, Glycemic control monitoring includes real-time measurements performed through self-monitoring of blood glucose (SMBG) or continuous glucose monitoring (CGM) and retrospective markers of glycemia [1]. Glycated hemoglobin (HbA1c) is an extensively used retrospective marker reflecting the average blood glucose level over the previous 8–12 weeks [1, 2]. However, the use of HbA1c has multiple limitations virtually eliminating the use of HbA1c in some patients with diabetes [2]. This fact has directed the attention to a group of intermediate retrospective markers of glycemia. The list includes fructosamine (FA), glycated albumin (GA) and 1,5-anhydroglucitol (1,5-AG). These markers reflect glycemia during the previous 1–4 weeks [2]. They may not only replace HbA1c in some groups of *Corresponding author: Bogdan Solnica, MD, PhD, Department of Diagnostics, Jagiellonian University Medical College, Kopernika 15a, 31-501 Krakow, Poland, Phone/Fax: +4812 4248365, E-mail: [email protected] Malgorzata Grzanka, Natalia Nowak and Bartlomiej Matejko: Department of Metabolic Diseases, Jagiellonian University Medical College, Krakow, Poland Maria Kapusta and Krystyna Slowinska-Solnica: Department of Diagnostics, Jagiellonian University Medical College, Krakow, Poland Jan Skupien, Tomasz Klupa and Maciej T. Malecki: Department of Metabolic Diseases, Jagiellonian University Medical College, Krakow, Poland; and University Hospital, Krakow, Poland
subjects with diabetes but also provide supplementary information, e.g., on short-term glycemic fluctuations. We aimed to assess the relationship between HbA1c, FA, 1,5-AG, and a set of summary metrics of CGM. The study included 19 adults (9 women and 10 men), white Caucasians, with type 2 diabetes (T2DM) and no presence of advanced chronic complications. The patients with liver and/or kidney disease were excluded. The details of clinical characteristics are provided in the Supplemental Data (Table 1), that accompanies the article at http://www. degruyter.com/view/j/cclm.2015.53.issue-1/issue-files/ cclm.2015.53.issue-1.xml. All procedures were in accordance with the ethical standards on human experimentation and with the Helsinki Declaration. The Jagiellonian University Bioethical Committee approved the study. All studied patients underwent CGM for 12 consecutive days, using iPro® CGMS (Medtronic, Minneapolis, USA), utilizing two iPro® compatible Enlite sensors (days 1–6 and 7–12). The following CGM parameters were calculated with the Glyculator software: –– mean blood glucose (MBG), standard deviation (SD) and coefficient of variation (CV); –– J index –based on the combination of information from the mean and SD calculated as 0.001 × (mean+SD)2; –– mean amplitude of glycemic excursions (MAGE) – calculated based on the arithmetic mean of differences between consecutive peaks and nadirs of differences greater than one SD of glycemia; –– percentage of glucose values below 3.9 mmol/L (% 7.0) and above 10.0 mmol/L (% > 10.0). HbA1c, FA and 1,5-AG were measured at the time of CGM discontinuation. HbA1c was measured in EDTA whole blood by the HPLC on the Variant II analyzer (Bio-Rad Laboratories Ltd., Hertfordshire, UK). The method remains
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e16 Solnica et al.: Retrospective markers of glycemia and the CGM results in systems of international quality control to ensure the standards of the HbA1c measurements. Serum FA was measured using the spectrophotometric method based on the reduction of nitroblue tetrazolium (NBT) (BioSystems S.A., Barcelona, Spain) on the MaxMat PL chemistry analyzer (MaxMat, Montpelier, France). The within- and between-run imprecision CVs of this assay amounted to 2.7% and 4.3%, respectively. Plasma 1,5-AG was measured by ELISA [Human 1,5-anhydroglucitol (1,5-AG) ELISA kit, CUSABIO, Wuhan, China] on the Benchmark Microplate Reader (Bio-Rad). For this assay, the within- and betweenrun CVs were 10.0. Currently, SMBG is considered the basis for monitoring of glycemic control in clinical practice [1]. However, intensive SMBG is recommended as obligatory only in patients treated with multiple daily insulin injections or continuous subcutaneous insulin infusion, mainly type 1 diabetes subjects [1]. Its effectiveness in T2DM is still under debate [3]. HbA1c measurements are recommended to complement SMBG. A growing body of evidence demonstrates that not only hyperglycemia but also glycemic variability is of clinical importance [4–6]. Thus, the question arises how to detect hyperglycemic excursions and assess glycemic variability. The gold standard in detecting glycemic fluctuations is CGM, which is more effective than SMBG but the CGM use is still expensive, time-consuming and invasive. Here, for the first time in a white Caucasian cohort of T2DM patients, we evaluated the relationship between HbA1c, FA and 1,5- AG, and the summary metrics of CGM. No correlations between HbA1c and CGM parameters reflecting glycemic variability were found. FA is a marker of glycemic control over a period of 2–3 weeks [2]. In our study FA correlated with MBG within 14 days and also with J index, % 10.0. These findings suggest the possibility for retrospective detection of periods of hypo- or hyperglycemia. FA has been reported as comparable with fasting plasma glucose in identifying subjects with undiagnosed diabetes and as the useful adjuvant to fasting plasma glucose in screening for poor glycemic control [7]. FA testing has also limitations, mostly abnormal protein metabolism [3]. Plasma 1,5-AG reflects the inhibition of its renal tubular reabsorption by glucose when gluco suria occurs and therefore assess glycemic control within
Table 1 Correlations of CGM parameters with retrospective markers of glycemia. CGMS parameter
MBG SD CV J-index MAGE % 7.0 % > 10.0 Reference/ target values
HbA1c
Fructosamine
1,5-anhydroglucitol
R (p-value)
R (p-value)
R (p-value)
0.44 (0.074) 0.41 (0.10) 0.29 (0.26) 0.43 (0.087) 0.47 (0.054) –0.25 (0.33) 0.38 (0.13) 0.39 (0.12) ≤ 7% (53 mmol/mol)
0.50 (0.042) 0.38 (0.13) 0.27 (0.29) 0.47 (0.057) 0.43 (0.084) –0.54 (0.025) 0.36 (0.15) 0.50 (0.038) 205–265 μmol/L
–0.43 (0.081) –0.54 (0.025) –0.50 (0.040) –0.49 (0.047) –0.49 (0.047) 0.04 (0.87) –0.40 (0.11) –0.48 (0.053) 10.7–32.0 μg/mL (men), 6.8–29.3 μg/mL (women)
CV, percentage coefficient of variation; MBG, mean blood glucose; % 7.0, percentage of glucose values above 7.0 mmol/L; % > 10.0, percentage of glucose values above 10.0 mmol/L; SD, standard deviation.
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Solnica et al.: Retrospective markers of glycemia and the CGM results e17
2 weeks [2]. In our study correlations between plasma 1,5-AG and SD, CV, J-index, MAGE were found confirming the ability of 1,5-AG to detect glycemic excursions reported in other studies [8, 9]. Additionally, a borderline correlation with % > 10.0 was found, which suggests the potential use of 1,5-AG as a marker of hyperglycemia above the renal threshold. Similar results were reported by Sun et al. based on the analysis of the relationship between serum 1,5-AG levels and the 72 h CGM parameters in 71 T2DM patients from China [10]. Our data obtained in a smaller group of white T2DM patients but based on a longer period of CGM confirm relationships found by Sun and colleagues in the European cohort. The lack of correlation between the three studied markers may be partially explained by the fact that they reflect blood glucose levels during various time periods. Additionally, the limited number of examined T2DM patients, an important shortcoming of this study, could have also contributed to this fact. In summary, our study suggests that in T2DM patients, FA seems to be particularly useful in reflecting short-term average glucose level, hypoglycemia and hyperglycemia. 1,5-AG is the best marker for retrospective assessment glycemic variability. This could be the basis of its recommended use to detect glycemic excursions, particularly postprandial hyperglycemia in patients with normal kidney function. 1,5-AG as a short-term glycemic marker can potentially complement HbA1c in T2DM patients who do not perform SMBG. However, the use of 1,5-AG for this purpose requires further studies to determine the target values for results interpretation. Moreover, the conclusions of the study should be limited to the T2DM patients with similar clinical characteristics. Acknowledgments: The results of this study were presented as a poster during the 2013 EASD meeting in Barcelona. The authors are grateful to Ms Aleksandra Malecka (Warsaw University) for her editorial and linguistic assistance. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. Financial support: None declared. Employment or leadership: None declared.
Honorarium: None declared. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
References 1. American Diabetes Association standards of medical care in diabetes – 2013. Diabetes Care 2013;36(Suppl 1):S11–66. 2. Wright LA, Hirsch IB. The challenge of the use of glycemic biomarkers in diabetes: reflecting on hemoglobin A1C, 1,5-anhydroglucitol, and the glycated proteins fructosamine and glycated albumin. Diabetes Spectr 2012;25:141–9. 3. Davis WA, Bruce DG, Davis TM. Does self-monitoring of blood glucose improve outcome in type-2 diabetes? The Fremantle Diabetes Study. Diabetologia 2007;50:510–5. 4. Siegelaar SE, Holleman F, Hoekstra JB, DeVries JH. Glucose variability; does it matter? Endocr Rev 2010;31:171–82. 5. Standl E, Schnell O, Ceriello A. Postprandial hyperglycemia and glycemic variability. Should we care? Diabetes Care 2011;34(Suppl 2):120–7. 6. Miller ME, Williamson JD, Gerstein HC, Byington RP, Cushman WC, Ginsberg HN, et al. Effects of randomization to intensive glucose control on adverse events, cardiovascular disease, and mortality in older versus younger adults in the ACCORD trial. Diabetes Care 2014;37:634–43. 7. Carter AW, Borchardt N, Cooney M, Greene D. Dual test diabetes screening project: screening for poor glycemic control in a large workplace population. Diabetes Technol Ther 2000;2:529–36. 8. Dungan KM, Buse JB, Largay J, Kelly MM, Button EA, Kato S, et al. 1,5-anhydroglucitol and postprandial hyperglycemia as measured by continuous glucose monitoring system in moderately controlled patients with diabetes. Diabetes Care 2006;29:1214–9. 9. Kishimoto M, Yamasaki Y, Kubota M, Arai K, Morishima T, Kawamore R, et al. 1,5-anhydro-d-glucitol evaluated daily glycemic excursions in well-controlled NIDDM. Diabetes Care 1995;18:1156–9. 10. Sun J, Dou J, Wang X, Yang G, Lü Z, Zheng H, et al. Correlation between 1,5-anhydroglucitol and glycemic excursions in type 2 diabetic patients. Chin Med J 2011;124:3641–5.
Supplemental Material: The online version of this article (DOI: 10.1515/cclm-2014-0580) offers supplementary material, available to authorized users.
Brought to you by | University of Iowa Libraries Authenticated Download Date | 5/29/15 11:04 PM
Letter to the Editor Bogdan Solnica*, Malgorzata Grzanka, Maria Kapusta, Natalia Nowak, Jan Skupien, Krystyna Slowinska-Solnica, Bartlomiej Matejko, Tomasz Klupa and Maciej T. Malecki
Association of retrospective markers of glycemia and the use of continuous glucose monitoring in white adults with type 2 diabetes mellitus – a preliminary report Keywords: 1,5-anhydroglucitol; blood glucose; fructos amine; glycated hemoglobin. DOI 10.1515/cclm-2014-0580 Received June 1, 2014; accepted June 18, 2014; previously published online July 11, 2014
To the Editor, Glycemic control monitoring includes real-time measurements performed through self-monitoring of blood glucose (SMBG) or continuous glucose monitoring (CGM) and retrospective markers of glycemia [1]. Glycated hemoglobin (HbA1c) is an extensively used retrospective marker reflecting the average blood glucose level over the previous 8–12 weeks [1, 2]. However, the use of HbA1c has multiple limitations virtually eliminating the use of HbA1c in some patients with diabetes [2]. This fact has directed the attention to a group of intermediate retrospective markers of glycemia. The list includes fructosamine (FA), glycated albumin (GA) and 1,5-anhydroglucitol (1,5-AG). These markers reflect glycemia during the previous 1–4 weeks [2]. They may not only replace HbA1c in some groups of *Corresponding author: Bogdan Solnica, MD, PhD, Department of Diagnostics, Jagiellonian University Medical College, Kopernika 15a, 31-501 Krakow, Poland, Phone/Fax: +4812 4248365, E-mail: [email protected] Malgorzata Grzanka, Natalia Nowak and Bartlomiej Matejko: Department of Metabolic Diseases, Jagiellonian University Medical College, Krakow, Poland Maria Kapusta and Krystyna Slowinska-Solnica: Department of Diagnostics, Jagiellonian University Medical College, Krakow, Poland Jan Skupien, Tomasz Klupa and Maciej T. Malecki: Department of Metabolic Diseases, Jagiellonian University Medical College, Krakow, Poland; and University Hospital, Krakow, Poland
subjects with diabetes but also provide supplementary information, e.g., on short-term glycemic fluctuations. We aimed to assess the relationship between HbA1c, FA, 1,5-AG, and a set of summary metrics of CGM. The study included 19 adults (9 women and 10 men), white Caucasians, with type 2 diabetes (T2DM) and no presence of advanced chronic complications. The patients with liver and/or kidney disease were excluded. The details of clinical characteristics are provided in the Supplemental Data (Table 1), that accompanies the article at http://www. degruyter.com/view/j/cclm.2015.53.issue-1/issue-files/ cclm.2015.53.issue-1.xml. All procedures were in accordance with the ethical standards on human experimentation and with the Helsinki Declaration. The Jagiellonian University Bioethical Committee approved the study. All studied patients underwent CGM for 12 consecutive days, using iPro® CGMS (Medtronic, Minneapolis, USA), utilizing two iPro® compatible Enlite sensors (days 1–6 and 7–12). The following CGM parameters were calculated with the Glyculator software: –– mean blood glucose (MBG), standard deviation (SD) and coefficient of variation (CV); –– J index –based on the combination of information from the mean and SD calculated as 0.001 × (mean+SD)2; –– mean amplitude of glycemic excursions (MAGE) – calculated based on the arithmetic mean of differences between consecutive peaks and nadirs of differences greater than one SD of glycemia; –– percentage of glucose values below 3.9 mmol/L (% 7.0) and above 10.0 mmol/L (% > 10.0). HbA1c, FA and 1,5-AG were measured at the time of CGM discontinuation. HbA1c was measured in EDTA whole blood by the HPLC on the Variant II analyzer (Bio-Rad Laboratories Ltd., Hertfordshire, UK). The method remains
Brought to you by | University of Iowa Libraries Authenticated Download Date | 5/29/15 11:04 PM
e16 Solnica et al.: Retrospective markers of glycemia and the CGM results in systems of international quality control to ensure the standards of the HbA1c measurements. Serum FA was measured using the spectrophotometric method based on the reduction of nitroblue tetrazolium (NBT) (BioSystems S.A., Barcelona, Spain) on the MaxMat PL chemistry analyzer (MaxMat, Montpelier, France). The within- and between-run imprecision CVs of this assay amounted to 2.7% and 4.3%, respectively. Plasma 1,5-AG was measured by ELISA [Human 1,5-anhydroglucitol (1,5-AG) ELISA kit, CUSABIO, Wuhan, China] on the Benchmark Microplate Reader (Bio-Rad). For this assay, the within- and betweenrun CVs were 10.0. Currently, SMBG is considered the basis for monitoring of glycemic control in clinical practice [1]. However, intensive SMBG is recommended as obligatory only in patients treated with multiple daily insulin injections or continuous subcutaneous insulin infusion, mainly type 1 diabetes subjects [1]. Its effectiveness in T2DM is still under debate [3]. HbA1c measurements are recommended to complement SMBG. A growing body of evidence demonstrates that not only hyperglycemia but also glycemic variability is of clinical importance [4–6]. Thus, the question arises how to detect hyperglycemic excursions and assess glycemic variability. The gold standard in detecting glycemic fluctuations is CGM, which is more effective than SMBG but the CGM use is still expensive, time-consuming and invasive. Here, for the first time in a white Caucasian cohort of T2DM patients, we evaluated the relationship between HbA1c, FA and 1,5- AG, and the summary metrics of CGM. No correlations between HbA1c and CGM parameters reflecting glycemic variability were found. FA is a marker of glycemic control over a period of 2–3 weeks [2]. In our study FA correlated with MBG within 14 days and also with J index, % 10.0. These findings suggest the possibility for retrospective detection of periods of hypo- or hyperglycemia. FA has been reported as comparable with fasting plasma glucose in identifying subjects with undiagnosed diabetes and as the useful adjuvant to fasting plasma glucose in screening for poor glycemic control [7]. FA testing has also limitations, mostly abnormal protein metabolism [3]. Plasma 1,5-AG reflects the inhibition of its renal tubular reabsorption by glucose when gluco suria occurs and therefore assess glycemic control within
Table 1 Correlations of CGM parameters with retrospective markers of glycemia. CGMS parameter
MBG SD CV J-index MAGE % 7.0 % > 10.0 Reference/ target values
HbA1c
Fructosamine
1,5-anhydroglucitol
R (p-value)
R (p-value)
R (p-value)
0.44 (0.074) 0.41 (0.10) 0.29 (0.26) 0.43 (0.087) 0.47 (0.054) –0.25 (0.33) 0.38 (0.13) 0.39 (0.12) ≤ 7% (53 mmol/mol)
0.50 (0.042) 0.38 (0.13) 0.27 (0.29) 0.47 (0.057) 0.43 (0.084) –0.54 (0.025) 0.36 (0.15) 0.50 (0.038) 205–265 μmol/L
–0.43 (0.081) –0.54 (0.025) –0.50 (0.040) –0.49 (0.047) –0.49 (0.047) 0.04 (0.87) –0.40 (0.11) –0.48 (0.053) 10.7–32.0 μg/mL (men), 6.8–29.3 μg/mL (women)
CV, percentage coefficient of variation; MBG, mean blood glucose; % 7.0, percentage of glucose values above 7.0 mmol/L; % > 10.0, percentage of glucose values above 10.0 mmol/L; SD, standard deviation.
Brought to you by | University of Iowa Libraries Authenticated Download Date | 5/29/15 11:04 PM
Solnica et al.: Retrospective markers of glycemia and the CGM results e17
2 weeks [2]. In our study correlations between plasma 1,5-AG and SD, CV, J-index, MAGE were found confirming the ability of 1,5-AG to detect glycemic excursions reported in other studies [8, 9]. Additionally, a borderline correlation with % > 10.0 was found, which suggests the potential use of 1,5-AG as a marker of hyperglycemia above the renal threshold. Similar results were reported by Sun et al. based on the analysis of the relationship between serum 1,5-AG levels and the 72 h CGM parameters in 71 T2DM patients from China [10]. Our data obtained in a smaller group of white T2DM patients but based on a longer period of CGM confirm relationships found by Sun and colleagues in the European cohort. The lack of correlation between the three studied markers may be partially explained by the fact that they reflect blood glucose levels during various time periods. Additionally, the limited number of examined T2DM patients, an important shortcoming of this study, could have also contributed to this fact. In summary, our study suggests that in T2DM patients, FA seems to be particularly useful in reflecting short-term average glucose level, hypoglycemia and hyperglycemia. 1,5-AG is the best marker for retrospective assessment glycemic variability. This could be the basis of its recommended use to detect glycemic excursions, particularly postprandial hyperglycemia in patients with normal kidney function. 1,5-AG as a short-term glycemic marker can potentially complement HbA1c in T2DM patients who do not perform SMBG. However, the use of 1,5-AG for this purpose requires further studies to determine the target values for results interpretation. Moreover, the conclusions of the study should be limited to the T2DM patients with similar clinical characteristics. Acknowledgments: The results of this study were presented as a poster during the 2013 EASD meeting in Barcelona. The authors are grateful to Ms Aleksandra Malecka (Warsaw University) for her editorial and linguistic assistance. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. Financial support: None declared. Employment or leadership: None declared.
Honorarium: None declared. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
References 1. American Diabetes Association standards of medical care in diabetes – 2013. Diabetes Care 2013;36(Suppl 1):S11–66. 2. Wright LA, Hirsch IB. The challenge of the use of glycemic biomarkers in diabetes: reflecting on hemoglobin A1C, 1,5-anhydroglucitol, and the glycated proteins fructosamine and glycated albumin. Diabetes Spectr 2012;25:141–9. 3. Davis WA, Bruce DG, Davis TM. Does self-monitoring of blood glucose improve outcome in type-2 diabetes? The Fremantle Diabetes Study. Diabetologia 2007;50:510–5. 4. Siegelaar SE, Holleman F, Hoekstra JB, DeVries JH. Glucose variability; does it matter? Endocr Rev 2010;31:171–82. 5. Standl E, Schnell O, Ceriello A. Postprandial hyperglycemia and glycemic variability. Should we care? Diabetes Care 2011;34(Suppl 2):120–7. 6. Miller ME, Williamson JD, Gerstein HC, Byington RP, Cushman WC, Ginsberg HN, et al. Effects of randomization to intensive glucose control on adverse events, cardiovascular disease, and mortality in older versus younger adults in the ACCORD trial. Diabetes Care 2014;37:634–43. 7. Carter AW, Borchardt N, Cooney M, Greene D. Dual test diabetes screening project: screening for poor glycemic control in a large workplace population. Diabetes Technol Ther 2000;2:529–36. 8. Dungan KM, Buse JB, Largay J, Kelly MM, Button EA, Kato S, et al. 1,5-anhydroglucitol and postprandial hyperglycemia as measured by continuous glucose monitoring system in moderately controlled patients with diabetes. Diabetes Care 2006;29:1214–9. 9. Kishimoto M, Yamasaki Y, Kubota M, Arai K, Morishima T, Kawamore R, et al. 1,5-anhydro-d-glucitol evaluated daily glycemic excursions in well-controlled NIDDM. Diabetes Care 1995;18:1156–9. 10. Sun J, Dou J, Wang X, Yang G, Lü Z, Zheng H, et al. Correlation between 1,5-anhydroglucitol and glycemic excursions in type 2 diabetic patients. Chin Med J 2011;124:3641–5.
Supplemental Material: The online version of this article (DOI: 10.1515/cclm-2014-0580) offers supplementary material, available to authorized users.
Brought to you by | University of Iowa Libraries Authenticated Download Date | 5/29/15 11:04 PM
