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

NCT06120556 | Completed

• 1 other identifier: AOUConsorziale
• Study Type: observational
• Target: 130
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Diabetes Mellitus, Type 2

Keywords

type 2 diabetes; GLP-1 receptor agonists; subtypes; phenotypes

Outcome Measures

Primary Outcomes (1)

• Difference in HbA1c change from baseline (%) among SIDD, SIRD, MARD, MOD subtypes

  Difference in HbA1c change from baseline will be evaluated at first follow-up visit (occurring 6-12 months from GLP-1RA initiation)

Secondary Outcomes (4)

• Difference in time to failure among SIDD, SIRD, MARD, MOD subtypes

  Difference in time to failure will be assessed up to the last available visit (up to 36 months)

• Difference in fasting blood glucose change from baseline (mg/dl) among SIDD, SIRD, MARD, MOD subtypes

  Difference in fasting blood glucose change from baseline (mg/dl) will be evaluated at first follow-up visit (occurring 6-12 months from GLP-1RA initiation)

• Difference in body weight change from baseline (kg) among SIDD, SIRD, MARD, MOD subtypes

  Difference in body weight change from baseline (kg) will be evaluated at first follow-up visit (occurring 6-12 months from GLP-1RA initiation)

• Difference in percentage of patients reaching HbA1c below 7% among SIDD, SIRD, MARD, MOD subtypes

  Difference in percentage of patients reaching HbA1c below 7% will be evaluated at first follow-up visit (occurring 6-12 months from GLP-1RA initiation)

Study Arms (4)

Severe Insulin Resistant Diabetes (SIRD)

Patients with SIRD are characterized by high BMI and high insulin resistance and low HbA1c. These patients likely develop diabetic kidney disease. Defined according to the simplified algorithm proposed by Bello-Chavolla et al. requiring the following data: age at diabetes diagnosis, age, BMI, height, waist circumference, HbA1c, fasting blood glucose, fasting triglycerides, HDL cholesterol

Drug: GLP-1 receptor agonist

Mild Age-Related Diabetes (MARD)

Patients with MARD are characterized by late onset diabetes without extreme features. Defined according to the simplified algorithm proposed by Bello-Chavolla et al. requiring the following data: age at diabetes diagnosis, age, BMI, height, waist circumference, HbA1c, fasting blood glucose, fasting triglycerides, HDL cholesterol

Drug: GLP-1 receptor agonist

Mild Obesity-related Diabetes (MOD)

Patients with MOD are characterized by high BMI without insulin resistance. Defined according to the simplified algorithm proposed by Bello-Chavolla et al. requiring the following data: age at diabetes diagnosis, age, BMI, height, waist circumference, HbA1c, fasting blood glucose, fasting triglycerides, HDL cholesterol

Drug: GLP-1 receptor agonist

Severe Insulin Deficient Diabetes (SIDD)

Patients with SIDD are characterized by high HbA1c and rapid progression to insulin therapy. These patients likely develop retinopathy, even in the first years after diagnosis. Defined according to the simplified algorithm proposed by Bello-Chavolla et al. requiring the following data: age at diabetes diagnosis, age, BMI, height, waist circumference, HbA1c, fasting blood glucose, fasting triglycerides, HDL cholesterol

Drug: GLP-1 receptor agonist

Interventions

GLP-1 receptor agonist DRUG

Patients initiating a GLP-1 receptor agonist (i.e. liraglutide, dulaglutide, semaglutide) will be included in the study.

Mild Age-Related Diabetes (MARD); Mild Obesity-related Diabetes (MOD); Severe Insulin Deficient Diabetes (SIDD); Severe Insulin Resistant Diabetes (SIRD)

Eligibility Criteria

• Age: 50 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All patients who attended the Day Service for diabetes of the Endocrinology Unit of the University Hospital A.O.U. Policlinico di Bari, Puglia, Italy from January 1st 2012 to October 1st 2023 will be consecutively evaluated for inclusion.

You may qualify if:

• Italian patients with type 2 diabetes
• Onset of diabetes at ≥ 50 years
• Diagnosis of type 2 diabetes ≤ 5 years from enrollment
• BMI ≥ 25 kg/m2
• Patients receiving a GLP-1RA prescription for the first time with at least one follow-up visit at 6-12 months from first prescription

You may not qualify if:

• Autoimmune diabetes, monogenic diabetes, secondary diabetes
• History of diabetic ketoacidosis

Sponsors & Collaborators

• Azienda Ospedaliero-Universitaria Consorziale Policlinico di Bari: lead

Study Sites (1)

Azienda Ospedaliero-Universitaria Policlinico Bari

Bari, 70124, Italy

Location

Related Publications (3)

• Ahlqvist E, Storm P, Karajamaki A, Martinell M, Dorkhan M, Carlsson A, Vikman P, Prasad RB, Aly DM, Almgren P, Wessman Y, Shaat N, Spegel P, Mulder H, Lindholm E, Melander O, Hansson O, Malmqvist U, Lernmark A, Lahti K, Forsen T, Tuomi T, Rosengren AH, Groop L. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018 May;6(5):361-369. doi: 10.1016/S2213-8587(18)30051-2. Epub 2018 Mar 5.

  PMID: 29503172 BACKGROUND

• Bello-Chavolla OY, Bahena-Lopez JP, Vargas-Vazquez A, Antonio-Villa NE, Marquez-Salinas A, Fermin-Martinez CA, Rojas R, Mehta R, Cruz-Bautista I, Hernandez-Jimenez S, Garcia-Ulloa AC, Almeda-Valdes P, Aguilar-Salinas CA; Metabolic Syndrome Study Group; Group of Study CAIPaDi. Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach. BMJ Open Diabetes Res Care. 2020 Jul;8(1):e001550. doi: 10.1136/bmjdrc-2020-001550.

  PMID: 32699108 BACKGROUND

• Dennis JM, Shields BM, Henley WE, Jones AG, Hattersley AT. Disease progression and treatment response in data-driven subgroups of type 2 diabetes compared with models based on simple clinical features: an analysis using clinical trial data. Lancet Diabetes Endocrinol. 2019 Jun;7(6):442-451. doi: 10.1016/S2213-8587(19)30087-7. Epub 2019 Apr 29.

  PMID: 31047901 BACKGROUND

MeSH Terms

Conditions

Diabetes Mellitus, Type 2

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases

Study Officials

• Francesco Giorgino, PhD

  University of Bari Aldo Moro

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: October 27, 2023
• First Posted: November 7, 2023
• Study Start: June 10, 2023
• Primary Completion: October 31, 2023
• Study Completion: October 31, 2023
• Last Updated: January 30, 2024

Record last verified: 2024-01

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL
• Time Frame: Beginning 9 months and ending 36 months following article publication.
• Access Criteria: Researchers who provide a methodologically sound proposal.

Locations

IT (1)