- Email: [email protected]
Comments on the article “Effects of vildagliptin twice daily vs. sitagliptin once daily on 24-hour acute glucose fluctuations” by Marfella et al.: (Journal of Diabetes and Its Complications 24 [2010] 79–83)
Journal of Diabetes and Its Complications 25 (2011) 352–353
Contents lists available at ScienceDirect
Journal of Diabetes and Its Complications j o u r n a l h o m e p a g e : W W W. J D C J O U R N A L . C O M
Letter to the Editor
Comments on the article “Effects of vildagliptin twice daily vs. sitagliptin once daily on 24-hour acute glucose fluctuations” by Marfella et al.: (Journal of Diabetes and Its Complications 24 [2010] 79–83)
Postprandial hyperglycemia is considered an independent risk factor for cardiovascular disease (Haffner, 1998; Ceriello et al., 2004). Postprandial glucose spikes lead to labile nonenzymatic glycation, oxidative stress and, subsequently, endothelial dysfunction (Ceriello, 2001). Therefore, in daily clinical practice, it is clinically desirable to use an antidiabetic drug strategy which effectively corrects not only the fasting plasma glucose, but also the postprandial glucose excursions. The agonists of glucagon-like peptide (GLP) 1 receptor and the inhibitors of dipeptidyl peptidase IV (DPP-4) are able to increase the glucose-dependent insulin secretion; therefore, they may be the drugs of choice to correct these metabolic abnormalities without inducing delayed, unwanted, hypoglycemic reactions. The pathophysiological reason for this positive action stands on the observation that a decreased GLP-1 response is seen in type 2 diabetic patients (Vilsboll et al., 2003). In their article, Marfella and colleagues conducted a crosssectional, non-placebo-controlled, unblinded study to compare the efficacy of sitagliptin 100 mg once daily vs. vildagliptin 50 mg twice daily on daily blood glucose fluctuations. The fluctuations were assessed by 48-h continuous subcutaneous glucose monitoring (CSGM) in patients with type 2 diabetes that was inadequately controlled by metformin. Their findings were the following: Both drugs significantly and similarly decreased the fasting and postprandial glucose levels and hemoglobin A1c (HbA1c) after a 3-month period. They used CGMS profiles to calculate the so-called mean amplitude of glycemic excursions (MAGE) (Service et al., 1970). They found that treatment with sitagliptin was associated with a higher MAGE (59±16) than vildagliptin (34±7; Pb0.05). Concurrently, vildagliptin treatment was associated with a lower glucagon level and with higher circulating GLP-1 levels despite comparable fasting and postprandial insulin concentrations. This study presents several shortcomings. The only statistically significant result between vildagliptin and sitagliptin is a lower value of MAGE observed for vildagliptin. It should be noted that, in the paper, no primary data of the CSGM are presented; this leads to misleading results for several reasons. From a methodological standpoint, MAGE was originally and arbitrarily defined as a divergence of either a peak or nadir of plasma glucose greater than 1 standard deviation (S.D.) of the glucose value assessed (Service et al., 1970). However, MAGE was first proposed for assessing the variability of few discrete plasma measurements and not for CSGM glucose profiles. This is of importance since 2 patients may 1056-8727/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.jdiacomp.2010.12.001
have the same glucose excursions but different S.Ds.; this would lead to remarkably different values of MAGE. Another important point is that CSGM data are asymmetric since the hypoglycemic range is much narrower than the hyperglycemic range; therefore, MAGE introduces a “hypersensitivity bias” toward the peaks and “hyposensitivity bias” toward the nadir. A higher value of MAGE during the sitagliptin treatment would therefore imply a “hypersensitivity bias” during this treatment, a situation difficult to justify in the presence of similar levels of fasting plasma glucose, postprandial plasma glucose and HbA1c values during both treatment as reported by the authors. Another important area of concern, with a definitive need for the primary data, is that it is unclear whether the authors have used the same S.D. to calculate excursion on different days or use the S.D. derived on data from only that one day. The HbA1c value is the target of most intervention trials designed to assess the relevance of glucose reduction on cardiovascular outcomes. In type 1 diabetic patients, as in the DCCT trial, the reduction of HbA1c explained only part of the beneficial effect of the improved metabolic control on microvascular complications (Lachin, Genuth, Nathan, Zinman, & Rutledge, 2008). In type 2 diabetic patients, the reduction of HbA1c has been disappointing in terms of cardiovascular outcomes (Del Prato, 2009). Therefore, there must be a factor not captured by HbA1c which may account for the complex relationships between plasma glucose, and micro- and macrovascular complications. Such factor may be represented by the fluctuations of blood glucose levels around the mean. The connections between glucose variability and microvascular complications have been either confirmed (Brownlee & Hirsch, 2006) or refuted (Kilpatrick, Rigby, & Atkin, 2009). Several studies have shown that postprandial glucose is predictive of future cardiovascular events, although most data are obtained in subjects not already diagnosed as having diabetes (Balkau et al., 1998; Esposito et al., 2008). Recent studies have not been able to confirm earlier ones showing that postprandial hyperglycemia is more of a cardiovascular risk than preprandial hyperglycemia (Pankow et al., 2007; Barr et al., 2007). The main intervention study specifically targeting postprandial hyperglycemia (and therefore reducing glucose variability) showed no benefit. Therefore, the precise role of glucose variability in the development of vascular complications in type 2 diabetic patients remains unanswered. Therefore, the report of an increased MAGE vs. similar HbA1c, similar fasting plasma glucose and similar postprandial plasma glucose of one treatment over another remains an elusive finding and a clinical “mystery.”
Letter to the Editor
This is true not only for macrovascular complication but also for beta cell function for which glucose variability was never tested. Gliptins have a good oral bioavailability which is not significantly influenced by food intake; these drugs lead to sustained DPP-4 enzyme inactivation, the only exception being vildagliptin for which a twice-daily administration is recommended because of a shorter half-life. In the context of this study, sitagliptin has a terminal half-life of 10 to 12 h at doses of 25 to 100 mg with an achieved target inhibition of DPP-4 (≥80%) over 24 h (Alba et al., 2009; Bergman et al., 2007; Vincent et al., 2007). On the contrary, the terminal blood half-life t1/2 of vildagliptin ranges from 1.32 to 2.43 h, and it inhibits DPP-4 (N90%) at all doses (Bergman et al., 2007; Vincent et al., 2007). Based on these parameters, the finding of a significantly higher concentration of intact GLP-1 during vildagliptin throughout the day reported in Fig. 1 is contradictory. In the manuscript, it is not mentioned when drugs were administered; however, assuming that they were ingested at 8:00 a.m. for sitagliptin and at 13:00 and 20:00, respectively, for vildagliptin, one would expect higher concentrations of intact GLP-1 from 8:00 a.m. to 13:00 for sitaglitptin, similar levels in the afternoon and slightly higher concentration only after dinner for vildagliptin. Furthermore, in Fig. 1 of their article, it appears that there is no more pronounced GLP-1 release in the morning as recently shown by Lindgren et al. (2009); this may suggest untruthful GLP-1 assay. This concern is further enhanced when one compares the vildagliptin-mediated increases in intact GLP-1 observed in this article with those reported by other groups. Mari and colleagues showed that 28 days of 100 mg vildagliptin bid leads to a 2.5-fold increase in intact GLP-1 concentrations with a rather narrow daily oscillation in GLP-1 concentration between 10 and 20 pmol/L, whereas Marfella and colleagues report intact GLP-1 excursions double those observed by Mari et al. (2005). Last but not least, the authors did not provide GLP-1 circulation data either in baseline conditions or during placebo-controlled arm. In conclusion, the findings of Marfella and colleagues for the decreased mean glycemic amplitude excursions during vildagliptin vs. sitagliptin do not appear to be robust enough to substantiate the choice of the former drug to control postprandial plasma glucose in type 2 diabetic patients. Furthermore, the lack of primary data, some awkwardness in the analytical approach and the unclear clinical significance of their results pinpoint the need for a more consistent clinical trial. Angelo Avogaro Department of Clinical and Experimental Medicine University of Padova Medical School, Padova, Italy E-mail address: [email protected] 2 November 2010 Available online 21 February 2011
353
References Alba, M., Sheng, D., Guan, Y., Williams-Herman, D., Larson, P., Sachs, J. R., Thornberry, R., Herman, G., Kaufman, K. D., & Goldstein, B. J. (2009). Sitagliptin 100 mg daily effect on DPP-4 inhibition and compound-specific glycemic improvement. CMRO, 25, 2507−2514. Balkau, B., Shipley, M., Jarrett, R. J., Pyorala, K., Pyorala, M., Forhan, A., & Eschwege, E. (1998). High blood glucose concentration is a risk factor for mortality in middle-aged nondiabetic men. 20-year follow-up in the Whitehall Study, the Paris Prospective Study, and the Helsinki Policemen Study. Diabetes Care, 21, 360−367. Barr, E. L., Zimmet, P. Z., Welborn, T. A., Jolley, D., Magliano, D. J., Dunstan, D. W., Cameron, A. J., Dwyer, T., Taylor, H. R., Tonkin, A. M., Wong, T. Y., McNeil, J., & Shaw, J. E. (2007). Risk of cardiovascular and all-cause mortality in individuals with diabetes mellitus, impaired fasting glucose, and impaired glucose tolerance: the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab). Circulation, 116, 151−157. Bergman, A., Ebel, D., Liu, F., Stone, J., Wang, A., Zeng, W., Chen, L., Dilzer, S., Lasseter, K., Herman, G., Wagner, J., & Krishna, R. (2007). Absolute bioavailability of sitagliptin, an oral dipeptidyl peptidase-4 inhibitor, in healthy volunteers. Biopharmaceutics and Drug Disposition, 28, 315−322. Brownlee, M., & Hirsch, I. B. (2006). Glycemic variability: a hemoglobin A1cindependent risk factor for diabetic complications. JAMA, 295, 1707−1708. Ceriello, A. (2001). Mechanisms of tissue damage in the postprandial state. International Journal of Clinical Practice Supplement, 7−12. Ceriello, A., Hanefeld, M., Leiter, L., Monnier, L., Moses, A., Owens, D., Tajima, N., & Tuomilehto, J. (2004). Postprandial glucose regulation and diabetic complications. Archives of Internal Medicine, 164, 2090−2095. Del Prato, S. (2009). Megatrials in type 2 diabetes. From excitement to frustration? Diabetologia, 52, 1219−1226. Esposito, K., Ciotola, M., Carleo, D., Schisano, B., Sardelli, L., Di Tommaso, D., Misso, L., Saccomanno, F., Ceriello, A., & Giugliano, D. (2008). Post-meal glucose peaks at home associate with carotid intima-media thickness in type 2 diabetes. Journal of Clinical Endocrinology and Metabolism, 93, 1345−1350. Haffner, S. M. (1998). The importance of hyperglycemia in the nonfasting state to the development of cardiovascular disease. Endocrine Reviews, 19, 583−592. Kilpatrick, E. S., Rigby, A. S., & Atkin, S. L. (2009). Effect of glucose variability on the longterm risk of microvascular complications in type 1 diabetes. Diabetes Care, 32, 1901−1903. Lachin, J. M., Genuth, S., Nathan, D. M., Zinman, B., & Rutledge, B. N. (2008). Effect of glycemic exposure on the risk of microvascular complications in the diabetes control and complications trials revisited. Diabetes, 57, 995−1001. Lindgren, O., Mari, A., Deacon, C. F., Carr, R. D., Winzell, M. S., Vikman, J., & Ahren, B. (2009). Differential islet and incretin hormone responses in morning versus afternoon after standardized meal in healthy men. Journal of Clinical Endocrinology and Metabolism, 94, 2887−2892. Mari, A., Sallas, W. M., He, Y. L., Watson, C., Ligueros-Saylan, M., Dunning, B. E., Deacon, C. F., Holst, J. J., & Foley, J. E. (2005). Vildagliptin, a dipeptidyl peptidase-IV inhibitor, improves model-assessed beta-cell function in patients with type 2 diabetes. Journal of Clinical Endocrinology and Metabolism, 90, 4888−4894. Pankow, J. S., Kwan, D. K., Duncan, B. B., Schmidt, M. I., Couper, D. J., Golden, S., & Ballantyne, C. M. (2007). Cardiometabolic risk in impaired fasting glucose and impaired glucose tolerance: the Atherosclerosis Risk in Communities Study. Diabetes Care, 30, 325−331. Service, F. J., Molnar, G. D., Rosevear, J. W., Ackerman, E., Gatewood, L. C., & Taylor, W. F. (1970). Mean amplitude of glycemic excursions, a measure of diabetic instability. Diabetes, 19, 644−655. Vilsboll, T., Krarup, T., Sonne, J., Madsbad, S., Volund, A., Juul, A. G., & Holst, J. J. (2003). Incretin secretion in relation to meal size and body weight in healthy subjects and people with type 1 and type 2 diabetes mellitus. Journal of Clinical Endocrinology and Metabolism, 88, 2706−2713. Vincent, S. H., Reed, J. R., Bergman, A. J., Elmore, C. S., Zhu, B., Xu, S., Ebel, D., Larson, P., Zeng, W., Chen, L., Dilzer, S., Lasseter, K., Gottesdiener, K., Wagner, J. A., & Herman, G. A. (2007). Metabolism and excretion of the dipeptidyl peptidase 4 inhibitor [14C]sitagliptin in humans. Drug Metabolism and Disposition, 35, 533−538.
Contents lists available at ScienceDirect
Journal of Diabetes and Its Complications j o u r n a l h o m e p a g e : W W W. J D C J O U R N A L . C O M
Letter to the Editor
Comments on the article “Effects of vildagliptin twice daily vs. sitagliptin once daily on 24-hour acute glucose fluctuations” by Marfella et al.: (Journal of Diabetes and Its Complications 24 [2010] 79–83)
Postprandial hyperglycemia is considered an independent risk factor for cardiovascular disease (Haffner, 1998; Ceriello et al., 2004). Postprandial glucose spikes lead to labile nonenzymatic glycation, oxidative stress and, subsequently, endothelial dysfunction (Ceriello, 2001). Therefore, in daily clinical practice, it is clinically desirable to use an antidiabetic drug strategy which effectively corrects not only the fasting plasma glucose, but also the postprandial glucose excursions. The agonists of glucagon-like peptide (GLP) 1 receptor and the inhibitors of dipeptidyl peptidase IV (DPP-4) are able to increase the glucose-dependent insulin secretion; therefore, they may be the drugs of choice to correct these metabolic abnormalities without inducing delayed, unwanted, hypoglycemic reactions. The pathophysiological reason for this positive action stands on the observation that a decreased GLP-1 response is seen in type 2 diabetic patients (Vilsboll et al., 2003). In their article, Marfella and colleagues conducted a crosssectional, non-placebo-controlled, unblinded study to compare the efficacy of sitagliptin 100 mg once daily vs. vildagliptin 50 mg twice daily on daily blood glucose fluctuations. The fluctuations were assessed by 48-h continuous subcutaneous glucose monitoring (CSGM) in patients with type 2 diabetes that was inadequately controlled by metformin. Their findings were the following: Both drugs significantly and similarly decreased the fasting and postprandial glucose levels and hemoglobin A1c (HbA1c) after a 3-month period. They used CGMS profiles to calculate the so-called mean amplitude of glycemic excursions (MAGE) (Service et al., 1970). They found that treatment with sitagliptin was associated with a higher MAGE (59±16) than vildagliptin (34±7; Pb0.05). Concurrently, vildagliptin treatment was associated with a lower glucagon level and with higher circulating GLP-1 levels despite comparable fasting and postprandial insulin concentrations. This study presents several shortcomings. The only statistically significant result between vildagliptin and sitagliptin is a lower value of MAGE observed for vildagliptin. It should be noted that, in the paper, no primary data of the CSGM are presented; this leads to misleading results for several reasons. From a methodological standpoint, MAGE was originally and arbitrarily defined as a divergence of either a peak or nadir of plasma glucose greater than 1 standard deviation (S.D.) of the glucose value assessed (Service et al., 1970). However, MAGE was first proposed for assessing the variability of few discrete plasma measurements and not for CSGM glucose profiles. This is of importance since 2 patients may 1056-8727/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.jdiacomp.2010.12.001
have the same glucose excursions but different S.Ds.; this would lead to remarkably different values of MAGE. Another important point is that CSGM data are asymmetric since the hypoglycemic range is much narrower than the hyperglycemic range; therefore, MAGE introduces a “hypersensitivity bias” toward the peaks and “hyposensitivity bias” toward the nadir. A higher value of MAGE during the sitagliptin treatment would therefore imply a “hypersensitivity bias” during this treatment, a situation difficult to justify in the presence of similar levels of fasting plasma glucose, postprandial plasma glucose and HbA1c values during both treatment as reported by the authors. Another important area of concern, with a definitive need for the primary data, is that it is unclear whether the authors have used the same S.D. to calculate excursion on different days or use the S.D. derived on data from only that one day. The HbA1c value is the target of most intervention trials designed to assess the relevance of glucose reduction on cardiovascular outcomes. In type 1 diabetic patients, as in the DCCT trial, the reduction of HbA1c explained only part of the beneficial effect of the improved metabolic control on microvascular complications (Lachin, Genuth, Nathan, Zinman, & Rutledge, 2008). In type 2 diabetic patients, the reduction of HbA1c has been disappointing in terms of cardiovascular outcomes (Del Prato, 2009). Therefore, there must be a factor not captured by HbA1c which may account for the complex relationships between plasma glucose, and micro- and macrovascular complications. Such factor may be represented by the fluctuations of blood glucose levels around the mean. The connections between glucose variability and microvascular complications have been either confirmed (Brownlee & Hirsch, 2006) or refuted (Kilpatrick, Rigby, & Atkin, 2009). Several studies have shown that postprandial glucose is predictive of future cardiovascular events, although most data are obtained in subjects not already diagnosed as having diabetes (Balkau et al., 1998; Esposito et al., 2008). Recent studies have not been able to confirm earlier ones showing that postprandial hyperglycemia is more of a cardiovascular risk than preprandial hyperglycemia (Pankow et al., 2007; Barr et al., 2007). The main intervention study specifically targeting postprandial hyperglycemia (and therefore reducing glucose variability) showed no benefit. Therefore, the precise role of glucose variability in the development of vascular complications in type 2 diabetic patients remains unanswered. Therefore, the report of an increased MAGE vs. similar HbA1c, similar fasting plasma glucose and similar postprandial plasma glucose of one treatment over another remains an elusive finding and a clinical “mystery.”
Letter to the Editor
This is true not only for macrovascular complication but also for beta cell function for which glucose variability was never tested. Gliptins have a good oral bioavailability which is not significantly influenced by food intake; these drugs lead to sustained DPP-4 enzyme inactivation, the only exception being vildagliptin for which a twice-daily administration is recommended because of a shorter half-life. In the context of this study, sitagliptin has a terminal half-life of 10 to 12 h at doses of 25 to 100 mg with an achieved target inhibition of DPP-4 (≥80%) over 24 h (Alba et al., 2009; Bergman et al., 2007; Vincent et al., 2007). On the contrary, the terminal blood half-life t1/2 of vildagliptin ranges from 1.32 to 2.43 h, and it inhibits DPP-4 (N90%) at all doses (Bergman et al., 2007; Vincent et al., 2007). Based on these parameters, the finding of a significantly higher concentration of intact GLP-1 during vildagliptin throughout the day reported in Fig. 1 is contradictory. In the manuscript, it is not mentioned when drugs were administered; however, assuming that they were ingested at 8:00 a.m. for sitagliptin and at 13:00 and 20:00, respectively, for vildagliptin, one would expect higher concentrations of intact GLP-1 from 8:00 a.m. to 13:00 for sitaglitptin, similar levels in the afternoon and slightly higher concentration only after dinner for vildagliptin. Furthermore, in Fig. 1 of their article, it appears that there is no more pronounced GLP-1 release in the morning as recently shown by Lindgren et al. (2009); this may suggest untruthful GLP-1 assay. This concern is further enhanced when one compares the vildagliptin-mediated increases in intact GLP-1 observed in this article with those reported by other groups. Mari and colleagues showed that 28 days of 100 mg vildagliptin bid leads to a 2.5-fold increase in intact GLP-1 concentrations with a rather narrow daily oscillation in GLP-1 concentration between 10 and 20 pmol/L, whereas Marfella and colleagues report intact GLP-1 excursions double those observed by Mari et al. (2005). Last but not least, the authors did not provide GLP-1 circulation data either in baseline conditions or during placebo-controlled arm. In conclusion, the findings of Marfella and colleagues for the decreased mean glycemic amplitude excursions during vildagliptin vs. sitagliptin do not appear to be robust enough to substantiate the choice of the former drug to control postprandial plasma glucose in type 2 diabetic patients. Furthermore, the lack of primary data, some awkwardness in the analytical approach and the unclear clinical significance of their results pinpoint the need for a more consistent clinical trial. Angelo Avogaro Department of Clinical and Experimental Medicine University of Padova Medical School, Padova, Italy E-mail address: [email protected] 2 November 2010 Available online 21 February 2011
353
References Alba, M., Sheng, D., Guan, Y., Williams-Herman, D., Larson, P., Sachs, J. R., Thornberry, R., Herman, G., Kaufman, K. D., & Goldstein, B. J. (2009). Sitagliptin 100 mg daily effect on DPP-4 inhibition and compound-specific glycemic improvement. CMRO, 25, 2507−2514. Balkau, B., Shipley, M., Jarrett, R. J., Pyorala, K., Pyorala, M., Forhan, A., & Eschwege, E. (1998). High blood glucose concentration is a risk factor for mortality in middle-aged nondiabetic men. 20-year follow-up in the Whitehall Study, the Paris Prospective Study, and the Helsinki Policemen Study. Diabetes Care, 21, 360−367. Barr, E. L., Zimmet, P. Z., Welborn, T. A., Jolley, D., Magliano, D. J., Dunstan, D. W., Cameron, A. J., Dwyer, T., Taylor, H. R., Tonkin, A. M., Wong, T. Y., McNeil, J., & Shaw, J. E. (2007). Risk of cardiovascular and all-cause mortality in individuals with diabetes mellitus, impaired fasting glucose, and impaired glucose tolerance: the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab). Circulation, 116, 151−157. Bergman, A., Ebel, D., Liu, F., Stone, J., Wang, A., Zeng, W., Chen, L., Dilzer, S., Lasseter, K., Herman, G., Wagner, J., & Krishna, R. (2007). Absolute bioavailability of sitagliptin, an oral dipeptidyl peptidase-4 inhibitor, in healthy volunteers. Biopharmaceutics and Drug Disposition, 28, 315−322. Brownlee, M., & Hirsch, I. B. (2006). Glycemic variability: a hemoglobin A1cindependent risk factor for diabetic complications. JAMA, 295, 1707−1708. Ceriello, A. (2001). Mechanisms of tissue damage in the postprandial state. International Journal of Clinical Practice Supplement, 7−12. Ceriello, A., Hanefeld, M., Leiter, L., Monnier, L., Moses, A., Owens, D., Tajima, N., & Tuomilehto, J. (2004). Postprandial glucose regulation and diabetic complications. Archives of Internal Medicine, 164, 2090−2095. Del Prato, S. (2009). Megatrials in type 2 diabetes. From excitement to frustration? Diabetologia, 52, 1219−1226. Esposito, K., Ciotola, M., Carleo, D., Schisano, B., Sardelli, L., Di Tommaso, D., Misso, L., Saccomanno, F., Ceriello, A., & Giugliano, D. (2008). Post-meal glucose peaks at home associate with carotid intima-media thickness in type 2 diabetes. Journal of Clinical Endocrinology and Metabolism, 93, 1345−1350. Haffner, S. M. (1998). The importance of hyperglycemia in the nonfasting state to the development of cardiovascular disease. Endocrine Reviews, 19, 583−592. Kilpatrick, E. S., Rigby, A. S., & Atkin, S. L. (2009). Effect of glucose variability on the longterm risk of microvascular complications in type 1 diabetes. Diabetes Care, 32, 1901−1903. Lachin, J. M., Genuth, S., Nathan, D. M., Zinman, B., & Rutledge, B. N. (2008). Effect of glycemic exposure on the risk of microvascular complications in the diabetes control and complications trials revisited. Diabetes, 57, 995−1001. Lindgren, O., Mari, A., Deacon, C. F., Carr, R. D., Winzell, M. S., Vikman, J., & Ahren, B. (2009). Differential islet and incretin hormone responses in morning versus afternoon after standardized meal in healthy men. Journal of Clinical Endocrinology and Metabolism, 94, 2887−2892. Mari, A., Sallas, W. M., He, Y. L., Watson, C., Ligueros-Saylan, M., Dunning, B. E., Deacon, C. F., Holst, J. J., & Foley, J. E. (2005). Vildagliptin, a dipeptidyl peptidase-IV inhibitor, improves model-assessed beta-cell function in patients with type 2 diabetes. Journal of Clinical Endocrinology and Metabolism, 90, 4888−4894. Pankow, J. S., Kwan, D. K., Duncan, B. B., Schmidt, M. I., Couper, D. J., Golden, S., & Ballantyne, C. M. (2007). Cardiometabolic risk in impaired fasting glucose and impaired glucose tolerance: the Atherosclerosis Risk in Communities Study. Diabetes Care, 30, 325−331. Service, F. J., Molnar, G. D., Rosevear, J. W., Ackerman, E., Gatewood, L. C., & Taylor, W. F. (1970). Mean amplitude of glycemic excursions, a measure of diabetic instability. Diabetes, 19, 644−655. Vilsboll, T., Krarup, T., Sonne, J., Madsbad, S., Volund, A., Juul, A. G., & Holst, J. J. (2003). Incretin secretion in relation to meal size and body weight in healthy subjects and people with type 1 and type 2 diabetes mellitus. Journal of Clinical Endocrinology and Metabolism, 88, 2706−2713. Vincent, S. H., Reed, J. R., Bergman, A. J., Elmore, C. S., Zhu, B., Xu, S., Ebel, D., Larson, P., Zeng, W., Chen, L., Dilzer, S., Lasseter, K., Gottesdiener, K., Wagner, J. A., & Herman, G. A. (2007). Metabolism and excretion of the dipeptidyl peptidase 4 inhibitor [14C]sitagliptin in humans. Drug Metabolism and Disposition, 35, 533−538.