Efficacy of Glucagon-like Peptide-1 Receptor Agonists According to Type 2 Diabetes Subtypes

Diabetes Mellitus, Type 2 Clinical Trial

Official title: Efficacy of Glucagon-like Peptide-1 Receptor Agonists According to Type 2 Diabetes Subtypes: an Italian Monocentric Retrospective Study

Status Completed

Clinical Trial Summary

The goal of this observational retrospective study is to understand whether glucagon-like peptide-1 receptor agonists (GLP-1RA), which are a group of antidiabetes drugs, may act differently in different subtypes of patients with type 2 diabetes.

The main questions it aims to answer are:

• people with type 2 diabetes belonging to specific subtypes respond better (or worse) to GLP-1RA?

• the beneficial effect of GLP-1RA may last longer in people with type 2 diabetes belonging to specific subtypes?

• what are the clinical characteristics that better explain the efficacy and durability of GLP-1 receptor agonists in type 2 diabetes management?

Clinical data from records of patients attending the diabetes outpatient clinic of our facility will be retrieved to compare the outcomes of GLP-1 receptor agonists in patients belonging to four subtypes of type 2 diabetes.

Clinical Trial Description

Patients with type 2 diabetes are all characterized by hyperglycemia, however their probability to develop micro- and micro-vascular complications. A classification of adult-onset diabetes in 5 subtypes was recently proposed: severe autoimmune diabetes (SAID - including type 1 diabetes and latent autoimmune diabetes in adults LADA), severe insulin resistant diabetes (SIRD), severe insulin deficient diabetes (SIDD), mild age related diabetes (MARD), mild obesity-related diabetes (MOD). This classification has been validated in a multiple populations of patients with recent onset diabetes (within 5 years).

However, this classification requires the measurement of c-peptide/insulinemia or anti- glutamic acid decarboxylase (GAD) antibodies, limiting its applicability in everyday clinical practice. An alternative algorithm requiring easily available clinical characteristics, such as BMI, height, waist circumference, HbA1c, fasting blood glucose, lipid profile, age and age at diagnosis was recently introduced and validated.

In this retrospective observational study, the calculated sample size was of 128 patients, in 4 groups, with alpha 0.05, 1-beta 0.80, effect size 0.3.

The following data will be retrieved for eligible patients: age, sex, diabetes duration, age at diagnosis, antidiabetes therapy, body weight, height, waist circumference, fasting blood glucose, HbA1c, total and HDL and LDL cholesterol, triglycerides, creatinine, microalbuminuria. The algorithm available online (https://uiem.shinyapps.io/diabetes_clusters_app/), will be used to assign enrolled patients to the 4 subtypes of type 2 diabetes (SIDD, SIRD, MARD, MOD).

If available, information regarding micro- and macro-vascular complications of diabetes will be retrieved.

All data will be collected at baseline visit and every follow-up visit (the first follow-up visit should 6-12 months following prescription of a GLP-1 receptor agonist). ;

Related Conditions & MeSH terms

• Diabetes Mellitus
• Diabetes Mellitus, Type 2

• NCT number: NCT06120556
• Study type: Observational
• Source: Azienda Ospedaliero-Universitaria Consorziale Policlinico di Bari
• Status: Completed
• Start date: June 10, 2023
• Completion date: October 31, 2023