Evaluation of the hypoglycemic and hypotensive efficacy of sodium-glucose cotransporter-2 inhibitors in patients with type 2 diabetes: A model-based dose-response network meta-analysis

Sanbao Chai, Fengqi Liu, Pei Li, Siyan Zhan, Feng Sun

Intelligent Pharmacy ›› 2025, Vol. 3 ›› Issue (2) : 150-158.

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Intelligent Pharmacy ›› 2025, Vol. 3 ›› Issue (2) : 150-158. DOI: 10.1016/j.ipha.2025.02.001
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Evaluation of the hypoglycemic and hypotensive efficacy of sodium-glucose cotransporter-2 inhibitors in patients with type 2 diabetes: A model-based dose-response network meta-analysis

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Abstract

Aims: To study the dose effect relationship of sodium-glucose cotransporter-2 inhibitor (SGLT-2i) in reducing blood glucose and blood pressure in type 2 diabetes mellitus (T2DM).

Materials and methods: We searched PubMed, Embase, Web of Science, Cochrane Library, and clinicaltrials.gov for related literature, with the search period spanning from the establishment of each platform to May 1, 2024. The main analysis method used is model-based network meta-analysis.

Results: A total of 192 RCTs involving 67,677 patients with T2DM were included in this study. The results showed that SGLT-2i reduced glycated hemoglobin A1c (HbA1c) in T2DM by 0.50 % (95 % CI: 0.49 % ~ 0.50 %) compared with placebo. The hypoglycemic effects of Luseogliflozin and Henagliflozin on HbA1c ranked first and second, with values of 0.92 % (95 % CI: 0.61 % ~ 1.28 %) and 0.91 % (95 % CI: 0.61 % ~ 1.36 %), respectively. Compared with placebo, the results showed that SGLT-2i lowered systolic blood pressure (SBP) by 3.23 mmHg (95 % CI: 3.19 mmHg ~ 3.26 mmHg) and diastolic blood pressure (DBP) by 4.16 mmHg (95 % CI: 4.13 mmHg ~ 4.18 mmHg) in patients with T2DM, respectively. Canagliflozin showed the greatest reduction in SBP and Luseogliflozin showed the greatest reduction in DBP, respectively.

Conclusions: The effect of SGLT-2i in reducing HbA1c in patients with T2DM increased with increasing daily dose, with Luseogliflozin and Henagliflozin being the most effective. SGLT-2i significantly reduced both SBP and DBP in T2DM, but there was no significant dose-response relationship. Among the SGLT-2i, Canagliflozin and Luseo-gliflozin exhibited better antihypertensive effects.

Keywords

SGLT-2 inhibitors / Type 2 diabetes mellitus / Systematic review / Model-based network meta-analysis / Dose-response

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Sanbao Chai, Fengqi Liu, Pei Li, Siyan Zhan, Feng Sun. Evaluation of the hypoglycemic and hypotensive efficacy of sodium-glucose cotransporter-2 inhibitors in patients with type 2 diabetes: A model-based dose-response network meta-analysis. Intelligent Pharmacy, 2025, 3(2): 150‒158 https://doi.org/10.1016/j.ipha.2025.02.001

References

[1]
Toyama T , Neuen BL , Jun M , et al. Effect of SGLT2 inhibitors on cardiovascular, renal and safety outcomes in patients with type 2 diabetes mellitus and chronic kidney disease: a systematic review and meta-analysis. Diabetes Obes Metabol. 2019; 21: 1237- 1250.
CrossRef Google scholar
[2]
Tilinca MC , Tiuca RA , Tilea I , Varga A . The SGLT-2 inhibitors in personalized therapy of diabetes mellitus patients. J Personalized Med. 2021; 11: 1249.
CrossRef Google scholar
[3]
Zinman B , Wanner C , Lachin JM , et al. EMPA-REG OUTCOME Investigators. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med. 2015; 373: 2117- 2128.
CrossRef Google scholar
[4]
Neal B , Perkovic V , Mahaffey KW , et al, CANVAS Program Collaborative Group . Canagliflozin and cardiovascular and renal events in type 2 diabetes. N Engl J Med. 2017; 377: 644- 657.
CrossRef Google scholar
[5]
Wiviott SD , Raz I , Bonaca MP , et al. DECLARE-TIMI 58 Investigators. Dapagliflozin and cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2019; 380: 347- 357.
CrossRef Google scholar
[6]
Perkovic V , Jardine MJ , Neal B , et al. Canagliflozin and renal outcomes in type 2 diabetes and nephropathy. N Engl J Med. 2019; 380: 2295- 2306.
CrossRef Google scholar
[7]
Heerspink HJL , Stefánsson BV , Correa-Rotter R , et al, DAPA-CKD Trial Committees and Investigators . Dapagliflozin in patients with chronic kidney disease. N Engl J Med. 2020; 383: 1436- 1446.
CrossRef Google scholar
[8]
Cowie MR , Fisher M . SGLT2 inhibitors: mechanisms of cardiovascular benefit beyond glycaemic control. Nat Rev Cardiol. 2020; 17: 761- 772.
CrossRef Google scholar
[9]
Georgianos PI , Agarwal R . Ambulatory blood pressure reduction with SGLT-2 inhibitors: dose-response meta-analysis and comparative evaluation with low-dose hydrochlorothiazide. Diabetes Care. 2019; 42: 693- 700.
CrossRef Google scholar
[10]
Tsapas A , Karagiannis T , Kakotrichi P , et al. Comparative efficacy of glucose-lowering medications on body weight and blood pressure in patients with type 2 diabetes: a systematic review and network meta-analysis. Diabetes Obes Metabol. 2021; 23: 2116- 2124.
CrossRef Google scholar
[11]
Mawdsley D , Bennetts M , Dias S , Boucher M , Welton NJ . Model-based network metaanalysis: a framework for evidence synthesis of clinical trial data. CPT Pharmacometrics Syst Pharmacol. 2016; 5: 393- 401.
CrossRef Google scholar
[12]
Hutton B , Salanti G , Caldwell DM , et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med. 2015; 162: 777- 784.
CrossRef Google scholar
[13]
Page MJ , McKenzie JE , Bossuyt PM , et al. Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement. J Clin Epidemiol. 2021; 134: 103- 112.
CrossRef Google scholar
[14]
Shim S , Yoon BH , Shin IS , Bae JM . Network meta-analysis: application and practice using Stata. Epidemiol Health. 2017; 39: e2017047.
CrossRef Google scholar
[15]
Langford O , Aronson JK , van Valkenhoef G , Stevens RJ . Methods for meta-analysis of pharmacodynamic dose-response data with application to multi-arm studies of alogliptin. Stat Methods Med Res. 2018; 27: 564- 578.
CrossRef Google scholar
[16]
Dias S , Welton NJ , Caldwell DM , Ades AE . Checking consistency in mixed treatment comparison meta-analysis. Stat Med. 2010; 29: 932- 944.
CrossRef Google scholar
[17]
Higgins JPT , Thomas J , Chandler J , et al., eds. Cochrane Handbook for Systematic Reviews of Interventions; 2022 (updated february 2022). cochrane version 6.3. www.training.cochrane.org/handbook.
[18]
University of Bern IoSaPM . Cinema: Confidence in Network Metaanalysis. 2017. available: cinema. ispm. ch (accessed may 2021).
[19]
Hussain M , Elahi A , Iqbal J , Bilal Ghafoor M , Rehman H , Akhtar S . Comparison of efficacy and safety profile of sodium-glucose cotransporter-2 inhibitors as add-on therapy in patients with type 2 diabetes. Cureus. 2021; 13: e14268.
CrossRef Google scholar
[20]
Hussein H , Zaccardi F , Khunti K , et al. Efficacy and tolerability of sodium-glucose co-transporter-2 inhibitors and glucagon-like peptide-1 receptor agonists: a systematic review and network meta-analysis. Diabetes Obes Metabol. 2020; 22: 1035- 1046.
CrossRef Google scholar
[21]
Avgerinos I , Karagiannis T , Kakotrichi P , et al. Sotagliflozin for patients with type 2 diabetes: a systematic review and meta-analysis. Diabetes Obes Metabol. 2022; 24: 106- 114.
CrossRef Google scholar
[22]
Palmer SC , Tendal B , Mustafa RA , et al. Sodium-glucose cotransporter protein-2 (SGLT-2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists for type 2 diabetes: systematic review and network meta-analysis of randomised controlled trials. BMJ. 2021; 372: m4573.
[23]
Weber MA , Schiffrin EL , White WB , et al. Clinical practice guidelines for the management of hypertension in the community a statement by the American Society of Hypertension and the International Society of Hypertension. J Hypertens. 2014; 32: 3- 15.
CrossRef Google scholar
[24]
Bangalore S , Kumar S , Lobach I , Messerli FH . Blood pressure targets in subjects with type 2 diabetes mellitus/impaired fasting glucose: observations from traditional and bayesian random-effects meta-analyses of randomized trials. Circulation. 2011; 123: 2799- 2810, 2799 p following 2810.
CrossRef Google scholar
[25]
Hermida RC , Ayala DE , Mojón A , Fernández JR . Sleep-time blood pressure as a therapeutic target for cardiovascular risk reduction in type 2 diabetes. Am J Hypertens. 2012; 25: 325- 334.
CrossRef Google scholar
[26]
Yan C , Thijs L , Cao Y , et al. Opportunities of antidiabetic drugs in cardiovascular medicine: a meta-analysis and perspectives for trial design. Hypertension. 2020; 76: 420- 431.
CrossRef Google scholar
[27]
Pedder H , Dias S , Bennetts M , Boucher M , Welton NJ . Joining the dots: linking disconnected networks of evidence using dose-response model-based network meta-analysis. Med Decis Mak. 2021; 41: 194- 208.
CrossRef Google scholar

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