GLPwatch

Basal insulin combined incretin mimetic therapy with glucagon-like protein 1 receptor agonists as an upcoming option in the treatment of type 2 diabetes: a practical guide to decision making.

Ther Adv Endocrinol Metab · 2014

Last updated 2026-05-28

Combining basal insulin with GLP-1 receptor agonists (GLP-1 RAs) is a new treatment option for type 2 diabetes, often used when blood sugar control isn’t achieved with basal insulin alone. Short-acting GLP-1 RAs like exenatide or lixisenatide may help if blood sugar rises after meals, while long-acting options like liraglutide may target high fasting blood sugar. This approach, called BIT, builds on existing basal insulin therapy (BOT) to better personalize treatment.

AI summary of the abstract below.

JournalTher Adv Endocrinol Metab, 2014
Citations11
Relative citation ratio0.42
NIH percentile25
Molecules
Conditions studied Type 2 Diabetes

Abstract

The combination of basal insulin and glucagon-like protein 1 receptor agonists (GLP-1 RAs) is a new intriguing therapeutic option for patients with type 2 diabetes. In our daily practice we abbreviate this therapeutic concept with the term BIT (basal insulin combined incretin mimetic therapy) in a certain analogy to BOT (basal insulin supported oral therapy). In most cases BIT is indeed an extension of BOT, if fasting, prandial or postprandial blood glucose values have not reached the target range. In our paper we discuss special features of combinations of short- or prandial-acting and long- or continuous-acting GLP-1 RAs like exenatide, lixisenatide and liraglutide with basal insulin in relation to different glycemic targets. Overall it seems appropriate to use a short-acting GLP-1 RA if, after the near normalization of fasting blood glucose with BOT, the prandial or postprandial values are elevated. A long-acting GLP-1 RA might well be given, if fasting blood glucose values are the problem. Based on pathophysiological findings, recent clinical studies and our experience with BIT and BOT as well as BOTplus we developed chart-supported algorithms for decision making, including features and conditions of patients. The development of these practical tools was guided by the need for a more individualized antidiabetic therapy and the availability of the new BIT principle.

Verbatim abstract via PubMed 25419451 ↗