|Year : 2020 | Volume
| Issue : 5 | Page : 434-445
Efficacy and safety of novel dipeptidyl-peptidase-4 inhibitor evogliptin in the management of type 2 diabetes mellitus: A meta-analysis
Deep Dutta1, Saptarshi Bhattacharya2, Aishwarya Krishnamurthy2, Lokesh Kumar Sharma3, Meha Sharma4
1 Department of Endocrinology, Center for Endocrinology, Diabetes, Arthritis and Rheumatism (CEDAR) Super-speciality Clinics, Dwarka, India
2 Department of Endocrinology, Max Superspeciality Hospital, Patparganj, India
3 Department of Biochemistry, Dr Ram Manohar Lohia (RML) Hospital, Dwarka, New Delhi, India
4 Department of Rheumatology, CEDAR Superspeciality Clinics, Dwarka, New Delhi, India
|Date of Submission||30-Jun-2020|
|Date of Decision||30-Jul-2020|
|Date of Acceptance||21-Sep-2020|
|Date of Web Publication||9-Nov-2020|
Center for Endocrinology, Diabetes, Arthritis and Rheumatism (CEDAR) Super-speciality Clinics, Dwarka, New Delhi - 110 075
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Aims: No meta-analysis is available which has summarized and holistically analyzed the efficacy and safety of evogliptin. We undertook this meta-analysis to address this gap in knowledge Methods: Electronic databases were searched for RCTs involving diabetes patients receiving evogliptin in intervention arm and placebo/active comparator in control arm. Primary outcome was to evaluate changes in HbA1c. Secondary outcomes were to evaluate alterations in fasting glucose, postprandial glucose, lipids, insulin resistance, patients achieving glycemic targets of HbA1c <7% and <6.5%, and adverse events. Results: From initially screened 57 articles, data from six RCTs involving 887 patients was analyzed [three having sitagliptin/linagliptin as active comparator; three having placebo in control group]. Evogliptin was noninferior to sitagliptin/linagliptin regarding HbA1c reduction at 12 weeks [mean difference (MD) -0.06%; 95%CI: -0.23–0.11%; P = 0.48] and 24 weeks (MD 0.04%; 95%CI: -0.11–0.19%; P = 0.60) follow-up. Evogliptin was superior to placebo regarding HbA1c reduction at 12-weeks (MD -0.57%; 95%CI: -0.62– -0.52%; P < 0.001) and 24 weeks (MD -0.28%; 95%CI: -0.47 – -0.09%; P = 0.004). Evogliptin was noninferior to sitagliptin/linagliptin regarding patients achieving HbA1c <7% and <6.5% at 12 weeks and 24 weeks follow-up. Total adverse events [Risk ratio (RR) 0.98; 95% CI: 0.72–1.32; P = 0.89] and severe adverse events (RR 0.65; 95% CI: 0.25–1.67; P = 0.37) were not significantly different among groups. Patients receiving evogliptin did not have increased symptomatic (RR 0.46; 95% CI: 0.10–2.16; P = 0.32) and asymptomatic (RR 1.09; 95% CI: 0.61–1.97; P = 0.77) hypoglycaemia. Conclusion: Evogliptin is well tolerated and has good glycemic efficacy over 6 months use for T2DM management
Keywords: Evogliptin, glycemic efficacy, meta-analysis, safety, type 2 diabetes mellitus
|How to cite this article:|
Dutta D, Bhattacharya S, Krishnamurthy A, Sharma LK, Sharma M. Efficacy and safety of novel dipeptidyl-peptidase-4 inhibitor evogliptin in the management of type 2 diabetes mellitus: A meta-analysis. Indian J Endocr Metab 2020;24:434-45
|How to cite this URL:|
Dutta D, Bhattacharya S, Krishnamurthy A, Sharma LK, Sharma M. Efficacy and safety of novel dipeptidyl-peptidase-4 inhibitor evogliptin in the management of type 2 diabetes mellitus: A meta-analysis. Indian J Endocr Metab [serial online] 2020 [cited 2020 Dec 5];24:434-45. Available from: https://www.ijem.in/text.asp?2020/24/5/434/300333
| Introduction|| |
Evogliptin, a novel, highly selective dipeptidyl-peptidase-4 inhibitor (DPP4i) was first approved for clinical use in South Korea in October, 2015. In India, it is available for management of type 2 diabetes mellitus (T2DM), since its approval in August 2018. Owing to its long half-life of 33 h, it is dosed at 5 mg once daily. It causes a sustained inhibition of more than 80% of the enzyme activity, by interacting with the S2-extensive subsite of the dipeptidyl-peptidase-4(DPP4) enzyme's active site. This occurs within one hour of ingestion and remains sustained over 24 h at the recommended dosage of 5 mg once daily., There is a resulting 1.5- to 2.4-fold increase in the postprandial active glucagon-like peptide-1 levels, with an effective postprandial plasma glucose (PPG) reduction by 25–35%. It is believed that dose adjustment is not warranted in the presence of diabetes kidney disease, as the drug predominantly undergoes hepatic metabolism via CYP3A4., Clinical trials from different parts of the globe (Korea, UK, Brazil and India) have reported good glycemic efficacy of evogliptin in T2DM. However literature search reveals that till date, there is no meta-analysis of the clinical efficacy and safety of this novel DPP4i. We undertook this meta-analysis to address this gap in knowledge.
| Methods|| |
This meta-analysis was carried out according to the recommendations of the Cochrane Handbook for Systematic Reviews of Interventions and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, the filled checklist of which can be found at the end of the manuscript. The predefined protocol has been submitted for registration in PROSPERO having registration number of CRD42020190459. As ethical approval already exists for individual studies included in the meta-analysis, no separate approval was required for this study.
The PICOS criteria were used to screen and select the studies for this meta-analysis with patients (P) being people living with T2DM; intervention (I) being use of evogliptin for managing T2DM; control (C) being patients either on placebo or any other approved medication for managing T2DM; outcomes (O) being evaluated were impact on HbA1c, fasting plasma glucose (FPG), PPG, and adverse events. Only patients with T2DM were considered for this meta-analysis. Patients with other forms of diabetes were excluded. Only those studies with at least two treatment groups, with one of the group receiving evogliptin either alone or a part of standard diabetes treatment regimen (SDTR) and the other group receiving placebo or another DPP4 inhibitor, either alone or as a part of SDTR were included.
The primary outcome was to evaluate the changes in HbA1c. The secondary outcomes were to evaluate the alterations in FPG, percentage of patients achieving glycemic targets of HbA1c <7% and <6.5%, changes in lipid parameters, insulin resistance parameters (HOMA-IR: Homeostatic Model Assessment of Insulin Resistance; QUICKI: Quantitative insulin sensitivity check index), discontinuation of medication due to adverse events, and any other adverse events as described by authors. Analysis was done based on whether the control group received an active comparator (usually another DPP4 inhibitor) – labeled here as the active control group (ACG) or a placebo – labeled as passive control group (PCG).
Search method for identification of studies
A detailed electronic databases of Medline (Via PubMed), Embase (via Ovid SP), Cochrane central register of controlled trials (CENTRAL) (for trials only), ctri.nic.in, clinicaltrials.gov, global health, and Google scholar were searched using a Boolean search strategy: (evogliptin) AND (diabetes).
Data extraction and study selection
Data extraction was carried out independently by two authors using standard data extraction forms. In cases where more than one publication of a single study group were found, results were grouped together and relevant data from each report were used in the analyses. Data on the primary and secondary outcomes as stated above was extracted. Patient characteristics (including demographic information and comorbidities) from the different studies included in the analysis were noted in a tabular form [Table 1]. All disagreements were resolved by the third and fourth authors.
|Table 1: Patients characteristics of randomized controlled trials on use of evogliptin in type-2 diabetes in this meta.analysis (Ref)|
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Assessment of risk of bias in included studies
Three authors independently assessed the risk of bias using the risk of bias assessment tool in Review Manager (Revman) Version 5.3 (The Cochrane Collaboration, Oxford, UK 2014) software. The following points were taken into consideration. Selection bias (adequate sequence generation and allocation concealment) was assessed. It was analyzed whether or not the knowledge of the allocated interventions was adequately prevented during the study. Participants and personnel (performance bias) blinding was specifically evaluated as was the blinding of the outcome assessors (detection bias). It was also assessed whether or not the incomplete outcome data issue was adequately addressed (attrition bias) and if reports of the study were free of suggestion of selective outcome reporting (reporting bias). Lastly, it was evaluated if the study was apparently free of other problems that could put it at a risk of bias. Any disagreements were resolved by the fourth author.
Measures of treatment effect
For continuous variables, the outcomes were expressed as mean differences (MD). Conventional units were used for analysis, and all studies reporting results in SI units were converted to conventional units for analysis. For dichotomous outcomes (treatment success) results were expressed as risk ratios (RR) with 95% confidence intervals (CI). For adverse events, results were expressed as post treatment absolute risk differences. RevMan 5.3 was used for comparing MD of the different primary and secondary outcomes between the evogliptin and the control groups of the included studies.
Dealing with missing data
Any additional information required from the original authors were requested by written e-mail correspondence and any relevant information thus obtained were included in the meta-analysis. Evaluation of important numerical data such as screened and randomized people as well as intention-to-treat, as-treated and per-protocol populations were carefully performed. Attrition rates, for example drop-outs, losses to follow-up and withdrawals were investigated.
Assessment of heterogeneity
Heterogeneity was initially assessed by studying the forest plot generated for the primary and secondary outcomes of this study. Subsequently heterogeneity was analyzed using a Chi2 test on N-1 degrees of freedom, with an alpha of 0.05 used for statistical significance and with the I2 test. The interpretation of I2 values is as follows: 0–40%: might not be important; 30–60%: may represent moderate heterogeneity; 50–90%: may represent substantial heterogeneity; 75P–100%: considerable heterogeneity. The importance of the observed value of I2 depends on the magnitude and direction of treatment effects and the strength of the evidence for heterogeneity (e.g., P value from the Chi2 test, or a CI for I2).
Grading of the results
An overall grading of the evidence related to each of the primary and secondary outcomes of the meta-analysis was done using the GRADE (Grades of Recommendation, Assessment, Development, and Evaluation) approach. The GRADE approach defines the quality of a body of evidence as the extent to which one can be confident that an estimate of effect or association is close to the true quantity of specific interest. The quality of a body of evidence involves consideration of within-trial risk of bias (methodological quality), directness of evidence, heterogeneity, precision of effect estimates, and risk of publication bias. The GRADEpro Guideline Development Tool software (McMaster University and Evidence Prime Inc, 2015) was used to create the Summary of Findings (SoF) table in this meta-analysis [Table 3]. Publication bias was assessed by plotting the Funnel Plot, which specifically targets small study bias, in which small studies tend to show larger estimates of effects and greater variability than larger studies. The presence of one or more of the smaller studies outside the inverted funnel plot was taken as an evidence of presence of significant publication bias.
Data was pooled as random effect model for the analysis of primary and secondary outcomes. The outcomes were expressed as 95% confidence intervals (95%CI). Forrest plots were plotted using RevMan 5.3 software, with left side of the graph favoring evogliptin and right side of the graph favoring control. P < 0.05 was considered statistically significant.
| Results|| |
A total of 57 articles were found after the initial search [Figure 1]. Following screening of the titles, abstracts, followed by full-texts, the search was reduced down to 11 RCTs, which were evaluated for inclusion in this meta-analysis [Figure 1]. Six RCTs in people with T2DM which fulfilled all criteria were analyzed in this meta-analysis.,,,,, Five RCTs were excluded as they evaluated the pharmacokinetic and pharmacodynamic properties of evogliptin.,,,,
|Figure 1: Flowchart elaborating on study retrieval and inclusion in the meta-analysis. RCT: randomized controlled trial|
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Of the six RCTs included in this meta-analysis, RCTs by Cercato et al., Ajmani et al., and Hong et al. had sitagliptin as active control and that by Kim et al. had linagliptin.,,, Hence, the data from these studies have been analyzed separately as ACG. RCTs by Park et al. and Jung et al. had placebo in the control group and hence were grouped and analyzed in the PCG., The details of all the RCTs included in this meta-analysis have been elaborated in [Table 1].
Risk of bias in the included studies
The summaries of risk of bias of the six studies included in the meta-analysis have been elaborated in [Figure 2]a and [Figure 2]b. Random sequence generation, performance bias, detection bias, attrition bias, and reporting bias were judged to be at low risk of bias in all the six studies (100%). Allocation concealment (selection bias) was at low risk in four out of six studies (66.67%). In two of the studies, the nature of selection bias was not clear. Source of funding, especially pharmaceutical, authors from the pharmaceutical organizations and conflict of interests were looked into the “other bias” section. Other bias was judged to be at low risk in only one out of the six studies (16.67%) [Figure 2] and [Figure 3]. The glycemic outcomes have been separately analyzed for 12 and 24 weeks follow-up, as per the available data.
|Figure 2: (a): Risk of bias graph: review authors' judgments about each risk of bias item presented as percentages across all included studies; (b): risk of bias summary: review authors' judgments about each risk of bias item for each included study|
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|Figure 3: Forest plot highlighting the impact of evogliptin after 12 weeks of therapy on (a) HbA1c (as compared to ACG); (b) fasting glucose (as compared to ACG); (c) percent of people achieving HbA1c <7% (as compared to ACG); (d) percent of people achieving HbA1c <6.5% (as compared to ACG); (e): HbA1c (as compared to PCG); (f): fasting glucose (as compared to PCG); (g) HbA1c <7% (as compared to PCG); and (h): HbA1c less than 6.5% (as compared to PCG). ACG: active control group; PCG: passive control group|
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Effect of evogliptin on primary outcomes
Four studies with 506 patients analyzed the impact of evogliptin on HbA1c after 12 weeks and 3 studies with 514 patients assessed it at 24 weeks of follow-up. When compared to the ACG, evogliptin was noninferior to sitagliptin/linagliptin with regards to HbA1c reduction at 12 weeks [MD -0.06% (95% CI: -0.23–0.11%); P = 0.48; I2 = 0% (low heterogeneity); [Figure 3]a; moderate certainty of evidence (MCE)] and 24 weeks of follow-up [MD 0.04% (95% CI: -0.11 – 0.19%); P = 0.60; I2 = 0% (low heterogeneity); [[Figure 4]a; high certainty of evidence (HCE)].
|Figure 4: Forest plot highlighting the impact of evogliptin after 24 weeks of therapy on (a) HbA1c (as compared to ACG); (b) fasting glucose (as compared to ACG); (c) percent of people achieving HbA1c <7% (as compared to ACG); (d) percent of people achieving HbA1c <6.5% (as compared to ACG); (e): HbA1c (as compared to PCG); and (f): Fasting glucose (as compared to PCG) RCT: randomized controlled trial. ACG: active control group; PCG: passive control group ACG: active control group; PCG: passive control group|
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Similar analysis was not possible for evogliptin compared to PCG as data was available only from one study at 12 weeks of follow-up (Jung et al., 2015) and 24 weeks of follow-up (Park et al. 2017). Analysis of data from these studies revealed evogliptin was superior to placebo with regards to HbA1c reduction at 12 weeks [MD -0.57% (95% CI: -0.62 – -0.52%); P < 0.001; [Figure 3]e; MCE] and 24 weeks [MD -0.28% (95% CI: -0.47 – -0.09%); P = 0.004; [Figure 4]e; HCE] follow-up.
Effect of evogliptin on secondary outcomes
Fasting plasma glucose
Four studies with 506 patients analyzed the impact of evogliptin on FPG at 12 weeks and 3 studies with 514 patients evaluated it at 24 weeks of follow-up. When compared to the ACG, evogliptin was noninferior to sitagliptin/linagliptin with regards to FPG reduction at 12 weeks [MD 3.97 mg/dL (95% CI: -2.87 – 10.8 mg/dL); P = 0.26; I2 = 0% (low heterogeneity); [Figure 3]b; HCE] and 24 weeks of follow-up [MD 0.53 mg/dL (95% CI: -5.52 – 6.58 mg/dL); P = 0.86; I2 = 0% (low heterogeneity); [[Figure 4]b; HCE].
Similar analysis was not possible for evogliptin compared to PCG as data was available only from one study at 12 weeks of follow-up (Jung et al., 2015) and 24 weeks of follow-up (Park et al. 2017). Analysis of data from these studies revealed evogliptin was superior to placebo with regards to FPG reduction at 12 weeks [MD -21.42 mg/dL (95% CI: -35.01 – 7.83 mg/dL); P = 0.002; [[Figure 3]f; MCE] and 24 weeks [MD -7.07 mg/dL (95% CI: -11.05 – 3.09 mg/dL); P = 0.0005; [[Figure 4]f; HCE] follow-up.
Glycated Haemoglobin <7%
Four studies with 495 patients and one study with 150 patients analyzed the impact of evogliptin on attaining glycemic target of HbA1c <7% at 12 weeks and 24 weeks of follow-up, respectively. When compared to the ACG, evogliptin was noninferior to sitagliptin/linagliptin with regards to percent of patients achieving HbA1c <7% at 12 weeks [Odds Ratio (OR) 0.91 (95% CI: 0.60–1.40); P = 0.68; I2 = 0% (low heterogeneity); [[Figure 3]c; HCE] and 24 weeks of follow-up [OR 1.45 (95% CI: 0.68–3.12); P = 0.34; [[Figure 4]c; HCE].
Similar analysis was not possible for evogliptin compared to PCG as data was available only from one study at 12 weeks of follow-up (Jung et al., 2015) and 24 weeks of follow-up (Park et al. 2017). Analysis of data from these studies revealed that percent of patients achieving HbA1c <7% at 12 weeks was higher in the evogliptin group as compared to those receiving placebo at 12 weeks follow-up [OR 1.69 (95% CI: 0.68–4.21); P = 0.26; [[Figure 3]g; HCE], but statistically not significant. No similar data was available for the PCG at 24 weeks follow-up.
Glycated Haemoglobin <6.5%
Impact of evogliptin on percent of patient attaining glycemic target of HbA1c <6.5% at 12 weeks was assessed in two studies with 138 patients and that at 24 weeks was analyzed in another two studies with 421 patients. When compared to ACG, evogliptin was noninferior to sitagliptin/linagliptin with regards to percent of patients achieving HbA1c <6.5% at 12 weeks [OR 0.33 (95% CI: 0.06–1.80); P = 0.20; [[Figure 3]e; MCE] and 24 weeks of follow-up [OR 0.96 (95% CI: 0.65–1.42); P = 0.83; I2 = 67% (moderate heterogeneity); [[Figure 4]e; MCE]. On analysis of data from PCG, percent of patients achieving HbA1c <6.5% at 12 weeks was higher in the evogliptin group as compared to placebo at 12 weeks follow-up, which approached statistical significance [OR 3.61 (95% CI: 0.92–14.14); P = 0.07; [[Figure 3]e; MCE]. However this data was available only from one study. No similar data was available for the PCS at 24 weeks follow-up.
Data from six studies (887 patients) was analyzed to evaluate the impact of evogliptin on the occurrence of adverse events [(total adverse events (TAEs) and severe adverse events (SAEs)]. The occurrence of TAEs was not statistically different in patients receiving evogliptin as compared to controls [RR 0.98 (95% CI: 0.72–1.32); P = 0.89; I2 = 17% (low heterogeneity); [[Figure 5]a; HCE]. The occurrence of SAEs was not statistically different in patients receiving evogliptin as compared to controls [RR 0.65 (95% CI: 0.25–1.67); P = 0.37; I2 = 0% (low heterogeneity); [[Figure 5]b; HCE]. There were no reports of pancreatitis in any of the study participants in all the six studies evaluated in this meta-analysis.
|Figure 5: Forest plot highlighting the side effect profile of the use of evogliptin as compared to controls focusing on (a): Total Adverse Events (TAEs); (b): severe Adverse Events (SAEs); (c): symptomatic hypoglycaemia; and (d): asymptomatic hypoglycaemia|
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Data from five studies (801 patients) were analyzed to evaluate the risk of symptomatic and asymptomatic hypoglycemia in patients receiving evogliptin as compared to the controls. Patients receiving evogliptin did not have increased risks of symptomatic [RR 0.46 (95% CI: 0.10–2.16); P = 0.32; I2 = 0% (low heterogeneity); [Figure 5]c; HCE] and asymptomatic [RR 1.09 (95% CI: 0.61–1.97); P = 0.77; I2 = 0% (low heterogeneity); [Figure 5]d; HCE] hypoglycaemia.
Lipid parameters and insulin resistance
Data from two studies (421 patients) were analyzed to evaluate the impact of evogliptin on different lipid parameters (total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). No significant difference was noted among patients receiving evogliptin as compared to controls with regards to total cholesterol [MD -0.93 mg/dL (95% CI: -5.73 – 3.87 mg/dL); P = 0.71; I2 = 0% (low heterogeneity)], triglycerides [MD -3.09 mg/dL (95% CI: -17.79–11.61 mg/dL); P = 068; I2 = 0% (low heterogeneity)], LDL-C [MD -1.37 mg/dL (95% CI: -5.92–3.18 mg/dL); P = 0.56; I2 = 0% (low heterogeneity)] and HDL-C [MD -0.36 mg/dL (95% CI: -1.90–1.18 mg/dL); P = 0.65; I2 = 0% (low heterogeneity)].
Data from two studies (290 patients) were analyzed to evaluate the impact of evogliptin on measures of insulin resistance. There was no significant difference in HOMA-IR [MD -0.01 (95% CI: -0.73–0.72); P = 0.99; I2 = 0% (low heterogeneity)] and QUICKI [MD 0.00 (95% CI: -0.00–0.00); P = 0.96; I2 = 0% (low heterogeneity)] among patients receiving evogliptin as compared to controls.
Funnel plot of all the included studies in the meta-analysis (assessing the publication bias) of the main outcomes assessed in this study. High publication bias was evident for Hba1c (12 weeks) and fasting glucose (12 weeks) for PCG. With regards to all the other parameters, there was no evidence of publication bias as all the studies fell well within the funnel plot. The SoF of the key parameters of this meta-analysis has been elaborated in [Table 2].
| Discussion|| |
No other class of antidiabetes medications has such a multitude of molecules as the DPP4i with 12 different DPP4i approved for clinical use in different countries across the globe. DPP4i gained much popularity after the launch of sitagliptin in 2006, because of the ease of their use, tolerability, good safety profile, and low hypo glycemic potential. Evogliptin belongs to the newer generation of DPP4i. With some special properties such as the high specificity for the DPP4 enzyme, a long half-life facilitating a once daily dosage, dual renal, and hepatic excretion permitting its use in mild to moderate renal failure as well as hepatic disease., This meta-analysis highlights the good glycemic efficacy of evogliptin in comparison to other established DPP4i like sitagliptin and linagliptin over period of 12–24 weeks. Evogliptin was noninferior to sitagliptin and linagliptin but superior to placebo with regards to achieving good glycemic control, as reflected in HbA1c and FPG reduction. This meta-analysis provides reassuring data on the safety of evogliptin. It is well tolerated and as compared to other DPP4i and placebo, without increased risk of adverse events. It was found to be lipid neutral and had no significant impact on insulin resistance parameters (HOMA-IR and QUICKI).
We must highlight that data with regards to evogliptin use from RCT is largely restricted to 24 weeks. Hence, there remains the need for RCTs with longer follow-up to establish the glycemic durability of evogliptin. These RCTs would also help us in generating useful long-term cardiovascular and renal safety data of evogliptin. In animal studies, evogliptin has been demonstrated to reduce the high-fat diet-induced atherosclerotic plaque area in the ApoE knockout mouse model. The protective effect of evogliptin on atherosclerotic progression is believed to be through inhibition of vascular inflammation.
DPP4 inhibitors have demonstrated protective effects against diabetic kidney disease, with encouraging data coming from linagliptin and sitagliptin. In animal models, evogliptin has been observed to have beneficial impact on renal fibrosis through inhibition of the transforming growth factor-β/Smad3 signaling pathway. It would be interesting to know the impact of evogliptin on urine albumin excretion. Evogliptin has been found to significantly reduce hepatic triglyceride accumulation, inflammation, and fibrosis as well as restored insulin sensitivity, in mice models of hepatic steatosis and steatohepatitis induced through high fat high fructose diet. Although from mechanistic studies, evogliptin is largely “nephro-safe” and “hepatic-safe,” we need focused RCTs in special populations (viz. people living with chronic kidney disease, liver disease), before evogliptin use can be recommended in these special clinical scenarios.
To conclude, it may be said that this first meta-analysis on the efficacy and safety of evogliptin in T2DM provides us with reassuring data on the good glycemic efficacy with good tolerability of this molecule over a period of 6 months clinical use.
Study was planned by DD and MS. Literature search and review was done by LKS and SB. Data extraction was done by SB and AK. Data analysis was done by DD. All authors contributed equally to the manuscript preparation.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| Risk of Bias Assessment for the Metanalysis|| |
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2]