Literature DB >> 27882107

Effects of sitagliptin as initial therapy in newly diagnosed elderly type 2 diabetics: A randomized controlled study.

Xiaoyan Xiao1, Xiaopei Cui2, Jianbo Zhang3, Zhenxia Han2, Yu Xiao2, Nan Chen2, Baoying Li2, Mei Cheng2, Haiqing Gao2, Kuanxiao Tang2.   

Abstract

The objective of this study was to investigate the characteristics of blood glycemic excursion, incretins and pancreatic hormone secretion in elderly people with newly diagnosed type 2 diabetes mellitus (T2DM) and to study the effects of sitagliptin on glycemic excursion in these subjects. A total of 129 newly diagnosed T2DM patients were enrolled in the study from March 2012 to August 2013. Clinical data, serum incretin, pancreatic hormone and continuous glucose monitoring data were collected. Among these subjects, elderly patients (NEDM) randomly received metformin combined with sitagliptin phosphate or glimepiride for 24 weeks. The blood glucose, glycosylated hemoglobin A1c (GHbA1c), serum incretins and pancreatic hormone levels were determined. During the oral glucose tolerance test (OGTT), 30 min insulin and C-peptide levels, 120 min insulin levels and ratio of the increases of insulin and blood glucose levels after 30 min of sugar loading (∆Ins30/∆Glu30) were significantly lower in elderly patients than in middle-aged patients (P<0.05). In addition, the glucagon elevation at 30 min was higher and the glucagon-like peptide-1 (GLP-1) at 30 min was lower in the elderly patients (P<0.05). Glucose excursion indices, including the standard deviation of the average blood glucose, intraday mean average glucose excursions (MAGE), and mean of daily differences (MODD), were significantly higher in the elderly patients (P<0.05). During the OGTT, insulin, C-peptide and ∆Ins30/∆Glu30 results at 30 min and GLP-1 levels at 120 min in NEDM subjects were significantly increased (P<0.05) and glucagon levels at 30 min was significantly lower after sitagliptin treatment (P<0.05) compared with glimepiride. Moreover, MAGE and MODD were significantly lower in the sitagliptin group after treatment compared to those in the glimepiride group (P<0.05). No severe hypoglycemia or cardiovascular diseases were observed. Strong blood glucose excursions occur in elderly patients with newly diagnosed T2DM. Sitagliptin phosphate combined with metformin effectively and safely improves glycemic excursion and carbohydrate metabolism in NEDM patients by promoting the first phase of insulin and incretin secretion and inhibiting glucagon secretion of.

Entities:  

Keywords:  elderly; glycemic excursion; incretins; sitagliptin; type 2 diabetes

Year:  2016        PMID: 27882107      PMCID: PMC5103735          DOI: 10.3892/etm.2016.3729

Source DB:  PubMed          Journal:  Exp Ther Med        ISSN: 1792-0981            Impact factor:   2.447


Introduction

The morbidity of type 2 diabetes mellitus (T2DM), particularly in elderly people, is increasing in China due to changes in lifestyle that have occurred in recent years. The prevalence of diabetes in individuals >60 years old is ~20.4% (1,2). However, blood glycemic excursion (BGE) is poorly understood in this particular population. Traditional treatment strategies for newly diagnosed elderly diabetics include one or more oral medications in addition to diet and exercise therapy, selected according to the level of blood glucose. Insulin injections remain the most potent therapy for uncontrolled T2DM. Multiple daily insulin injections can result in decreased variability of 24 h glucose levels (3) and delay the onset or progression of associated microvascular complications (4). However, hypoglycemia is a frequent side effect during insulin treatment, particularly in elderly patients. Sitagliptin, a dipeptidyl peptidase-4 (DPP-4) inhibitor, increases endogenous glucagon-like peptide 1 (GLP-1) secretion and improves β-cell function and glycemic excursions without inducing hypoglycemia in patients with T2DM (5,6). DPP-4 inhibitors provide a beneficial effect on body weight, episodes of hypoglycemia, and total adverse events as determined via meta-analysis (7). Furthermore, the effect of DPP-4 inhibitors on glycated hemoglobin A1c (GHbA1c) has been suggested to be greater in older adults than in younger adults with T2DM (8), which makes DPP-4 inhibitors a good choice for the clinical treatment of elderly patients with T2DM. The present randomized case-controlled study was designed to examine the characteristics of glycemic excursion, incretins and pancreatic hormone secretion in elderly patients with newly diagnosed T2DM and to investigate the effects of sitagliptin on glycemic excursions in such patients.

Materials and methods

Subjects

A total of 129 patients newly diagnosed with T2DM from Qilu Hospital of Shandong University (Jinan, China) were enrolled in this study from March 2012 to August 2013. Inclusion criteria were as follows: i) Results from an oral glucose tolerance test in accordance with the standards set by the World Health Organization in 1999 (9) for patients with newly diagnosed T2DM; ii) aged between 45 and 80 years; iii) negative plasma glutamic acid decarboxylase antibody, islet cell antibody and insulin autoantibody test results; and iv) no previous use of hypoglycemic drugs. The exclusion criteria were as follows: i) Fasting blood glucose >16.7 mmol/l or GHbA1c >10%; ii) acute diabetic complications such as ketoacidosis; iii) severe hepatic, renal, cerebral-cardiovascular or gastrointestinal co-morbidities; or iv) allergies to metformin hydrochloride, sitagliptin phosphate or glimepiride. Patients were divided into two age groups: Aged ≥65 years (NEDM group, n=86) and middle-aged group (45–65 years old; NMDM group, n=43). The elderly subjects were randomly assigned to receive sitagliptin phosphate (Januvia; Hangzhou MSD Pharmaceutical Co., Ltd., Hangzhou, China) combined with metformin (Glucophage; Sino-American Shanghai Squibb Pharmaceuticals Co., Ltd., Shanghai, China) and were defined as the SIG group or took glimepiride [Sanofi (Beijing) Pharmaceuticals Co., Ltd., Beijing, China] combined with metformin and were defined as the GLM group. The dose of sitagliptin was 100 mg once daily, and the initial dose of glimepiride was 1 mg once daily, and then titrated to 4 mg once daily, according to the patient's glucose level. The initial dose of metformin was 0.25 g thrice daily and then increased to 0.5 g thrice daily according to the patient's glucose level. The study was approved by the institutional ethical review committee of Qilu Hospital of Shandong University (Approval ID: KLS12185), and informed written consent was obtained from each patient prior to participation.

Clinical and laboratory parameters

Clinical data including gender, age, height, weight, waist measurement, systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI) and past medical history were collected. Fasting fingertip blood glucose, GHbA1c, total serum cholesterol (TC), triglyceride (TG), low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C) and uric acid (UA) levels were evaluated using fully automatic biochemical analysis instruments.

Continuous blood glucose monitoring

Subjects who agreed to use a blood glucose monitoring system (NEDM, n=41; NMDM, n=21) used a continuous glucose monitor (CGMS System Gold; Medtronic MiniMed, Inc., Northridge, CA, USA) for 72 h. The patient maintained a normal amount of diet and exercise during monitoring to evaluate glucose variability. The fluctuant indices of glucose included mean blood glucose (MBG), standard deviation (SD) of the average blood glucose, intraday mean amplitude of glucose excursion (MAGE), and mean of daily differences (MODD) of interday blood glucose.

Oral glucose tolerance test (OGTT) and pancreatic hormone measurements

An OGTT was performed at the beginning and end of the study. Serum glucose (glucose oxidase method) (10), insulin (chemiluminescence assay; #03649928; Siemens Healthcare Diagnostics, Inc., Tarrytown, NY, USA), C-peptide (C-P; #03649933; Siemens Healthcare Diagnostics, Inc.), glucagon [GLC enzyme-linked immunosorbent assay (ELISA); R&D Systems, Inc., Minneapolis, MN, USA] and glucagon-like peptide-1 (GLP-1; ELISA; R&D Systems, Inc.) were evaluated at 0, 30 and 120 min during the OGTT. The areas under the curve (AUC) for blood glucose, insulin, glucagon and GLP-1 were calculated using the following formula: 0.25 × [(FX + (4 × 30 min X) + (3 × 120 min X)]. FX, 30 min × and 120 min X are the values of blood glucose at 0 min, insulin at 30 min, and glucagon or GLP-1 at 120 min, respectively, during the OGTT. The homeostatic model assessment of β cell function (HOMA-β) was calculated from fasting blood glucose (FBG) and fasting insulin (FINS; measured at 0 min during the OGTT) levels as follows: 20 × FINS/(FBG − 3.5). HOMA-insulin resistance (HOMA-IR) was calculated as follows: (FBG × FINS)/22.5. The early phase of HOMA-β was evaluated as the ratio of the net increments of insulin and blood glucose levels after 30 min of sugar loading: ∆Ins30/∆Glu30 (∆Ins30 and ∆Glu30 are the increases in insulin and blood glucose levels, respectively, at 30 min of the OGTT) (11).

Follow-up visits

For the follow-up assessment, all patients were evaluated at the clinic at 4, 8, 12 and 24 weeks after enrollment. The follow-up visits were completed in all 129 patients. Blood glucose variation was measured using a fingertip micro blood glucose instrument, and treatment plans were adjusted according to the treatment guidelines for elderly patients with diabetic mellitus (12). Hypoglycemia was recorded. A self-monitored blood glucose level <3.9 mmol/l was defined as hypoglycemia, and patients with hypoglycemic symptoms were defined as having symptomatic hypoglycemia, and those requiring management with emergency treatment were defined as having severe hypoglycemia. The onset and related hospitalization of severe cardiocerebral diseases including myocardial infarction, heart failure and stroke were also recorded.

Statistical analysis

Data are presented as the mean ± SD. SPSS software (version 16.0; SPSS, Inc., Chicago, IL, USA) was used for all statistical analysis. Data from experiments were analyzed using Student's t–test or Chi-square tests, wherever appropriate. P<0.05 was considered to indicate a statistically significant difference.

Results

Clinical parameters and blood glucose fluctuation in the NEDM and NMDM groups

As shown in Table I, age, SBP and LDL-C (P<0.05) levels were significantly different in the NEDM group compared with the NMDM group. There was no significant difference in other indices, including waist measurement, BMI, DBP and TG, TC, HDL-C and UA levels between the two groups.
Table I.

Clinical characteristics of the two age groups.

CharacteristicsNMDMNEDM
No. (M/F)43 (23/20)86 (45/41)
Age (years)49.2±4.568.6±5.2[a]
BMI (kg/m2)27.80±3.1628.22±3.42
Waist (cm)85.44±6.8487.03±7.18
SBP (mmHg)130.7±14.6138.5±14.2[b]
DBP (mmHg)74.1±9.872.4±10.5
TG (mmol/l)2.62±0.602.47±0.66
TC (mmol/l)5.82±2.015.68±1.53
HDL-C (mmol/l)1.28±0.551.14±0.42
LDL-C (mmol/l)3.51±0.534.43±0.67[b]
UA (µmol/l)390.75±91.05383.06±75.29
GHbA1c (%)7.59±1.607.21±1.24
MBG (mmol/l)[c]11.03±0.5212.16±0.35
SD (mmol/l)[c]1.85±0.123.29±0.17[a]
MAGE (mmol/l)[c]4.83±0.258.06±0.38[a]
MODD (mmol/l)[c]1.70±0.062.62±0.08[b]

BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; UA, uric acid; GHbA1c, glycosylated hemoglobin A1c; MBG, mean blood glucose; SD, standard deviation; MAGE, mean average blood glucose excursions; MODD, mean of daily differences; M, male; F, female; NMDM, middle-aged patients with diabetes mellitus (45–65 years old); NEDM, elderly patients with diabetes mellitus (≥65 years old).

P<0.01

P<0.05 vs. the NMDM group.

Number of cases using a continuous glucose monitor: NEDM group, n=41; NMDM group, n=21.

Although the GHbA1c levels were not different between the two groups (P>0.05), the CGMS results showed that the FBG level in the NEDM group was slightly elevated, and the blood glucose level increased postprandially and then dropped sharply. Glycemic excursion parameters including the SD, MAGE and MODD in the NEDM group were greater than those in the NMDM group (P<0.05). However, the MBG of the two groups exhibited no significant difference (Table I).

Characteristics of incretins in the NEDM group

During the OGTT, blood glucose levels at 0 and 120 min were lower and those at 30 min were higher in the NEDM group compared with the NMDM group (P<0.05; Fig. 1). The insulin levels at 0, 30 and 120 min and the C-P and GLP-1 levels at 30 min were also lower in the NEDM group than in the NMDM group (8.09 vs 9.86 mIU/L; P<0.05). The glucagon level at 0 min was lower and at 30 min higher in the NEDM group than in the NMDM group (P<0.05; Fig. 1). The AUCins, ∆Ins30/∆Glu30 and AUCglp-1 in the NEDM group were lower than those the NMDM group (P<0.05; Table II). These results indicate that the secretion of GLP-1 and insulin decreased in the early phase and was accompanied by increased secretion of glucagon by α cells during this time.
Figure 1.

Glucose, incretins and pancreatic hormones during the OGTT in the two age groups at different time points. (A) Blood glucose levels,. (B) insulin levels, (C) C-peptide levels, (D) glucagon levels and (E) GLP-1 levels in the OGTT at 0, 30 and 120 min. OGTT, oral glucose tolerance test; GLP-1, glucagon-like peptide-1; NMDM, middle-aged patients with diabetes mellitus (45–65 years old); NEDM, elderly patients with diabetes mellitus (≥65 years old) *P<0.05 and **P<0.01 vs. the NMDM group.

Table II.

AUCs and indices of the two age groups.

VariableNMDMNEDM
AUCBG26.75±2.4228.64±2.75
AUCIns107.27±9.2082.33±7.26[a]
AUCGlc324.61±30.33335.28±36.59
AUCGLP-1169.11±15.46139.52±14.07[a]
HOMA-β37.05±3.2041.02±3.76
HOMA-IR3.48±0.253.54±0.26
ΔIns30/ΔGlu307.15±0.582.88±0.22[b]

AUC, area under the curve; BG, blood glucose; Ins, insulin; Glc, glucagon; GLP-1, glucagon-like peptide-1; HOMA-β, homeostatic model assessment of β cell function; HOMA-IR, HOMA-insulin resistance; ΔIns30/ΔGlu30, ratio of increments of insulin and blood glucose levels after 30 min of sugar loading; NMDM, middle-aged patients with diabetes mellitus (45–65 years old; n=43); NEDM, elderly patients with diabetes mellitus (≥65 years old; n=86).

P<0.05

P<0.01 vs. the NMDM group.

Effect of sitagliptin on glucose excursion and incretins in the NEDM group

No significant differences in clinical characteristics, GHbA1C or CGMS glucose fluctuation indices were observed between the GLM and SIG groups prior to treatment (P>0.05; Table III). However, after 24 weeks of treatment, these parameters improved in both the SIG and GLM groups (P<0.05). Moreover, the MAGE and MODD in the SIG group were significantly lower compared with those in the GLM group (P<0.05; Table IV).
Table III.

Clinical characteristics of the GLM and SIG groups of NEDM subjects at baseline.

VariableGLM groupSIG group
No. (M/F)18 (10/8)23 (13/10)
Age (years)69.1±6.568.7±6.3
BMI (kg/m2)27.92±3.8728.34±3.81
Waist (cm)87.81±7.6788.16±7.66
SBP (mmHg)137.3±13.6139.7±14.1
DBP (mmHg)71.8±10.572.5±10.8
TG (mmol/l)2.55±0.712.39±0.69
TC (mmol/l)5.87±1.645.59±1.65
HDL-C (mmol/l)1.09±0.371.16±0.46
LDL-C (mmol/l)4.18±0.494.53±0.64
UA (µmol/l)381.56±74.37385.44±76.22

GLM group, patients treated with glimepiride and metformin; SIG group, patients treated with sitagliptin and metformin; NEDM, elderly patients with diabetes mellitus (≥65 years old); M, male; F, female; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; UA, uric acid.

Table IV.

Glucose excursion parameters between the SIG and GLM groups.

GLM groupSIG group


ParameterPretreatmentAfter treatmentPretreatmentAfter treatment
GHbA1c (%)7.27±1.156.47±0.70[a]7.32±1.016.25±0.62[a]
MBG (mmol/l)11.89±1.128.82±0.85[a]12.16±1.358.35±0.79[b]
SD (mmol/l)3.18±0.451.63±0.23[a]3.29±0.471.57±0.21[a]
MAGE (mmol/l)8.27±1.216.01±0.77[a]8.06±1.184.42±0.46[b, c]
MODD (mmol/l)3.70±0.462.63±0.37[a]3.62±0.481.74±0.21[a, d]

GLM, treated with glimepiride and metformin (n=18, 10 M and 8 F); SIG, treated with sitagliptin and metformin (n=23, 13 M and 10 F); GHbA1c, glycosylated hemoglobin A1c; MBG, mean blood glucose; SD, standard deviation; MAGE, mean average blood glucose excursions; MODD, mean of daily differences; M, male; F, female.

P<0.05

P<0.01 vs. pretreatment;

P<0.01

P<0.05 vs. the GLM group.

No significant difference existed between the GLM and SIG groups for glucose, insulin, C-P, glucagon and GLP-1 during the OGTT prior to treatment (P>0.05). However, these parameters significantly improved in the two groups after treatment (P<0.05). Furthermore, with regard to OGTT results in the SIG group, the levels of insulin and C-P at 30 min and of GLP-1 at 0 and 30 min significantly increased (P<0.05), whereas the glucagon level at 30 min dropped sharply (P<0.01) compared with pre-treatment levels. In the GLM group, the levels of insulin and C-P at 120 min were significantly increased (P<0.05), whereas the glucagon and GLP-1 levels were maintained (P>0.05) compared with pre-treatment levels. In the SIG group post-treatment, glucose and glucagon levels at 30 min were lower compared with those in the GLM group (P<0.05), whereas insulin and GLP-1 levels at 30 min were higher compared with those in the GLM group (P<0.05; Fig. 2).
Figure 2.

Glucose, incretins and pancreatic hormones during the OGTT before (Pre) and after sitagliptin (SIG) or glimepiride (GLM) treatment. (A) Blood glucose, (B) insulin, (C) C-peptide, (D) glucagon and (E) GLP-1 levels during the OGTT were measured in the SIG and GLM groups before and after treatment. OGTT, oral glucose tolerance test; GLP-1, glucagon-like peptide-1. *P<0.05 and **P<0.01 vs. pre-treatment; #P<0.05 and ##P<0.01 vs. the GLM group.

As shown in Fig. 3, the AUCs for glucose, insulin, glucagon and GLP-1, and the HOMA-β, HOMA-IR and ∆Ins30/∆Glu30 indices in the SIG and GLM groups were comparable prior to treatment (P>0.05). After treatment, all of these indices significantly improved in the SIG group (P<0.05), with the exception of the HOMA-IR. In the GLM group, the AUC for glucose significantly decreased (P<0.05), whereas the AUC for insulin, HOMA-β and ∆Ins30/∆Glu30 significantly increased (P<0.05). In addition, the AUC for INS, GLP-1 and ∆Ins30/∆Glu30 in the SIG group were higher than those in the GLM group following treatment (P<0.05), whereas the AUC for glucagon was lower (P<0.05).
Figure 3.

Area under the curve (AUC) comparisons during the OGTT after sitagliptin (SIG) or glimepiride (GLM) treatment. (A) Glucose, (B) serum insulin, (C) C-peptide and (D) GLP-1 AUCs were analyzed at different time points during the OGTT. (D) The AUC of GLP-1 was significantly increased after SIG treatment, but not after GLM treatment. (E) The SIG and GLM groups showed similar increases in HOMA-β AUC during treatment, with no significant difference between groups. (F) Neither sitagliptin nor glimepiride affected the HOMA-IR. (G) The AUC of ∆Ins30/∆Glu30 increased in the two groups, although a greater increase occurred in the SIG group. OGTT, oral glucose tolerance test; GLP-1, glucagon-like peptide-1; HOMA-β, homeostatic model assessment of β cell function; HOMA-IR, HOMA-insulin resistance; ΔIns30/ΔGlu30, ratio of increments of insulin and blood glucose levels after 30 min of sugar loading. *P<0.05 and **P<0.01 vs. pre-treatment; #P<0.05 and ##P<0.01 vs. the GLM group.

Other effects

The average body weight significantly decreased in the SIG group following treatment (78.2±4.5 kg at baseline vs. 75.8±4.0 kg at the end of treatment; P<0.05), whereas there was no significant change in the average body weight (79.0±4.6 kg at baseline vs. 78.1±4.3 kg at the end of treatment; P>0.05) in the GLM group. The body weights were significantly different in the SIG group compared with the GLM group at the end of treatment (P<0.05). The incidence of symptomatic hypoglycemia in the SIG and GLM groups was 2.9 and 4.7%, respectively (P<0.05). No severe hypoglycemia was observed in any subject. No myocardial infarction, heart failure, and stroke occurred during the follow up.

Discussion

The amplitude of glucose variability increases from subjects with normal glucose tolerance (NGT) to those in patients with T2DM. When compared with individuals with NGT and impaired glucose regulation, subjects with NMDM show more predominant intra- and interday glucose variability and postprandial glucose excursion (13). However, to the best of our knowledge, there has been no case-control study regarding the characteristics of glycemic excursion in NEDM patients. In the present study, glucose variability was observed as a slight increase in FBG level and a sharp increase in the postprandial glucose level in NEDM patients. The CGMS glucose excursion parameters such as MAGE and MODD were also observed to increase and exhibited extreme fluctuations. The feature of glucose fluctuation in T2DM is closely associated with the number and function of β cells and the secretion level and function of insulin, glucagon and GLP-1. Previous studies have already verified that aging has a negative effect on islet function (14,15). In hyperglycemic clamp experiments, first and second phase insulin secretion in people with NGT normally decrease by 0.7% per year, with a greater reduction in the first phase compared with the second phase (16). A study involving Chinese individuals with NGT also demonstrate that insulin secretion and the ability of islets to compensate decrease with age for basal glucose levels and after oral glucose loading (17). Age-related IGT in healthy elderly people is not caused by a reduction in β cell number but rather the secretion and function of insulin (18), as β cells in all age groups including healthy, aged and very aged remain stable (19,20). Patients with IGT and elderly diabetes mellitus (EDM) subjects have a 40 and 50% deficit, respectively, in the number of β cells compared with those in healthy controls (21,22). This deficit results from decreased proliferation and replication along with increased apoptosis and necrosis of β cells with aging (20). However, β cell secretion in EDM patients gradually decreases as diabetes mellitus progresses, with urinal C-P decreasing 6% per year (23). Glucagon and GLP-1 secretion levels in the early phase for EDM patients remain unclear. In the present study, the ∆Ins30/∆Glu30, and the AUCIns and GLP-1 level at 30 min were lower in the NEDM group than in the NMDM group, and the glucagon level increased at 30 min in the NEDM group. These results indicate that the synthesis of glycogen by the liver significantly decreases under the action of insulin, whereas the breakdown of liver glycogen into glucose is accelerated by glucagon, resulting in the highly undulating glycemic excursions in NEDM subjects. The results of the present study demonstrate that aging impairs GLP-1 secretion, which contributes to high post-prandial glycemia, and these data are in accordance with results of a recent study (24). DPP-4 inhibitors and sulfonylureas are important second-line anti-diabetic agents used with metformin or as a monotherapy. DPP-4 degrades endogenous GLP-1 following its secretion. Sitagliptin is a highly selective DPP-4 inhibitor that inhibits ≥80% of plasma DPP-4 activity and augments the level of active GLP-1 following an OGTT (5). Animal experiments have indicated that GLP-1 reduces β cell apoptosis, improves β cell replication and regeneration, and inhibits α cell oversecretion (25). A clinical study has found that sitagliptin phosphate used as a monotherapy or in combination with other antidiabetic drugs can help improve GLP-1 secretion and β cell function, resulting in improved glycemic control (26). Rauch et al administered a 7-week monotherapy of linagliptin to T2DM subjects aged from 18 to 80 years and found that the treatment significantly increased the GLP-1 level, suppressed glucagon and improved the FBG and HbA1c levels (27). In the present study, after 24 weeks of metformin combined with sitagliptin phosphate treatment in the NEDM group, it was found that insulin secretion in the early phase and GLP-1 secretion was improved, and the abnormal secretion of glucagon was suppressed. However, metformin combined with glimepiride did not change the GLC and GLP-1 levels, suggesting that the combination of metformin with sitagliptin phosphate has a synergistic effect for the treatment of NEDM. In a previous study, the FBG and 2 h postprandial blood glucose levels in newly diagnosed NEDM subjects decreased after 24 weeks of sitagliptin monotherapy (6). Sitagliptin monotherapy treatment significantly and rapidly improves glycemic measures and is well tolerated in patients with T2DM aged ≥65 years (28). In the present study, sitagliptin improved early phase insulin secretion and GLP-1 levels and suppressed the reverse secretion of α cells in the NEDM group. Increased early phase insulin secretion promotes glucose intake and metabolism in cells while increased serum GLP-1 may improve the early phase secretion of β cells in NEDM patients. Notably, a recent study has shown that glucose fluctuations during the acute phase of acute myocardial infarction affect the myocardial salvage index (MSI), and the plasma GLP-1 level is positively correlated with the MSI. Since coronary artery diseases (CADs) are common in elderly people with T2DM, this finding indicates that patients with CAD may obtain greater benefits after sitagliptin treatment (29). Animal experiments and clinical research have found that the hypoglycemic effect of sitagliptin presents glucose dependence (30,31). Notably, the prevalence of cerebral-cardiovascular disease in EDM patients is much higher than in other groups (32), so safety is particularly important. There are previous reports concerning the association of sitagliptin with heart failure (33,34), however, in the present study, no severe cardiovascular diseases occurred. This study demonstrates that the combination of metformin with sitagliptin is a relatively safe treatment for NEDM patients. This study has several limitations. First, the sample size was low. Second, not all subjects underwent continuous blood glucose monitoring due to the cost of this system. Third, this study was a small-size clinical observation, and the mechanism was not investigated. More studies are required to explain the underlying mechanism. In conclusion, in NEDM patients, blood glucose fluctuations occur due to defects in the first phase of insulin and incretin secretion and the excessive secretion of glucagon by pancreatic α cells. Sitagliptin phosphate combined with metformin effectively and safely improves glycemic excursion and carbohydrate metabolism in NEDM patients by promoting the first phase of insulin and incretin secretion and inhibiting the secretion of glucagon.
  34 in total

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Authors:  Nir Barzilai; Hua Guo; Erin M Mahoney; Suzanne Caporossi; Gregory T Golm; Ronald B Langdon; Debora Williams-Herman; Keith D Kaufman; John M Amatruda; Barry J Goldstein; Helmut Steinberg
Journal:  Curr Med Res Opin       Date:  2011-03-23       Impact factor: 2.580

2.  Evaluation of Trinder's glucose oxidase method for measuring glucose in serum and urine.

Authors:  J A Lott; K Turner
Journal:  Clin Chem       Date:  1975-11       Impact factor: 8.327

3.  Impaired incretin secretion and pancreatic dysfunction with older age and diabetes.

Authors:  Bruno Geloneze; Maria da Saude de Oliveira; Ana Carolina Junqueira Vasques; Fernanda Satake Novaes; José Carlos Pareja; Marcos Antonio Tambascia
Journal:  Metabolism       Date:  2014-04-12       Impact factor: 8.694

4.  Insulinotropic glucagon-like peptide 1 agonists stimulate expression of homeodomain protein IDX-1 and increase islet size in mouse pancreas.

Authors:  D A Stoffers; T J Kieffer; M A Hussain; D J Drucker; S Bonner-Weir; J F Habener; J M Egan
Journal:  Diabetes       Date:  2000-05       Impact factor: 9.461

5.  Estimating physician effects on glycemic control in the treatment of diabetes: methods, effects sizes, and implications for treatment policy.

Authors:  Peter W Tuerk; Martina Mueller; Leonard E Egede
Journal:  Diabetes Care       Date:  2008-02-19       Impact factor: 19.112

6.  Acute-phase glucose fluctuation is negatively correlated with myocardial salvage after acute myocardial infarction.

Authors:  Ikuko Teraguchi; Toshio Imanishi; Yuichi Ozaki; Takashi Tanimoto; Minoru Ueyama; Makoto Orii; Yasutsugu Shiono; Kunihiro Shimamura; Kohei Ishibashi; Takashi Yamano; Yasushi Ino; Tomoyuki Yamaguchi; Kumiko Hirata; Takashi Kubo; Tokio Sanke; Takashi Akasaka
Journal:  Circ J       Date:  2013-11-02       Impact factor: 2.993

7.  Comparative effectiveness of basal-bolus versus premix analog insulin on glycemic variability and patient-centered outcomes during insulin intensification in type 1 and type 2 diabetes: a randomized, controlled, crossover trial.

Authors:  Marcia A Testa; Jasvinder Gill; Max Su; Ralph R Turner; Lawrence Blonde; Donald C Simonson
Journal:  J Clin Endocrinol Metab       Date:  2012-07-31       Impact factor: 5.958

8.  β-cell mass and turnover in humans: effects of obesity and aging.

Authors:  Yoshifumi Saisho; Alexandra E Butler; Erica Manesso; David Elashoff; Robert A Rizza; Peter C Butler
Journal:  Diabetes Care       Date:  2012-08-08       Impact factor: 19.112

9.  Comment on: Valette et al. Melanocortin-4 receptor mutations and polymorphisms do not affect weight loss after bariatric surgery. PLOS ONE 2012; 7(11):E48221.

Authors:  David Meyre; Philippe Froguel; Fritz F Horber; John G Kral
Journal:  PLoS One       Date:  2014-03-31       Impact factor: 3.240

10.  Linagliptin increases incretin levels, lowers glucagon, and improves glycemic control in type 2 diabetes mellitus.

Authors:  Thomas Rauch; Ulrike Graefe-Mody; Carolyn F Deacon; Arne Ring; Jens J Holst; Hans-Juergen Woerle; Klaus A Dugi; Tim Heise
Journal:  Diabetes Ther       Date:  2012-09-18       Impact factor: 2.945

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1.  Hypoglycemic agents and glycemic variability in individuals with type 2 diabetes: A systematic review and network meta-analysis.

Authors:  SuA Oh; Sujata Purja; Hocheol Shin; Minji Kim; Eunyoung Kim
Journal:  Diab Vasc Dis Res       Date:  2022 May-Jun       Impact factor: 3.541

2.  Influence of dipeptidyl peptidase-4 inhibitors on glycemic variability in patients with type 2 diabetes: A meta-analysis of randomized controlled trials.

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Journal:  Front Endocrinol (Lausanne)       Date:  2022-08-09       Impact factor: 6.055

3.  Effect of DPP-IV Inhibitors on Glycemic Variability in Patients with T2DM: A Systematic Review and Meta-Analysis.

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Journal:  Sci Rep       Date:  2019-09-16       Impact factor: 4.379

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