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Insulin glargine/lixisenatide fixed-ratio combination (iGlarLixi) compared with premix or addition of meal-time insulin to basal insulin in people with type 2 diabetes: A systematic review and Bayesian network meta-analysis

Lookup NU author(s): Emeritus Professor Philip Home

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Abstract

© 2020 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.Aim: To assess the efficacy and safety of iGlarLixi, a fixed-ratio combination of insulin glargine 100 U/mL and lixisenatide, relative to premix insulin and other insulin options through network meta-analysis. Methods: A systematic literature search identified randomized controlled trials (RCTs) comparing iGlarLixi, premix insulin or basal insulin (BI) in combination with meal-time insulin, in people inadequately controlled with BI. Eligible RCTs were compared using Bayesian network meta-analysis. Results: Eight RCTs, some open-label, involving 3538 participants, with a study duration of 24-30 weeks were included. The estimated difference in HbA1c reduction with iGlarLixi compared with premix insulin was −0.50%-units (95% credible interval: −0.93 to −0.06) with 98% probability of iGlarLixi being superior to premix. Estimates for iGlarLixi versus meal-time + BI (thrice-daily meal-time insulin + basal) and basal-plus (once-daily meal-time insulin + BI) were −0.35 (−0.89 to +0.13)%-units and −0.68 (−1.18 to −0.17)%-units with probabilities of real difference of 94% and 99%, respectively. Safety outcome analysis suggested that iGlarLixi had lower rates of both confirmed and documented symptomatic hypoglycaemia compared with premix insulin (probabilities of 85% and 93%, respectively) and lower weight gain (probability 98%). Conclusions: iGlarLixi showed similar or improved efficacy and safety versus other intensification choices from BI included in this study, providing a clinically relevant treatment option in people with type 2 diabetes not well controlled on BI.

Publication metadata

Author(s): Home P, Blonde L, Kalra S, Ji L, Guyot P, Brulle-Wohlhueter C, Murray E, Shah R, Sayre T, Shaunik A

Publication type: Article

Publication status: Published

Journal: Diabetes, Obesity and Metabolism

Year: 2020

Volume: 22

Issue: 11

Pages: 2179-2188

Print publication date: 01/11/2020

Online publication date: 22/07/2020

Acceptance date: 21/07/2020

Date deposited: 03/12/2020

ISSN (print): 1462-8902

ISSN (electronic): 1463-1326

Publisher: Blackwell Publishing Ltd

URL: https://doi.org/10.1111/dom.14148

DOI: 10.1111/dom.14148

PubMed id: 32700442

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