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Anti-diabetic drugs and weight loss in patients with type 2 diabetes
Open accessAbstract
Introduction Obesity is frequently a comorbidity of type 2 diabetes. Even modest weight loss can significantly improve glucose homeostasis and lessen cardiometabolic risk factors in patients with type 2 diabetes, but lifestyle-based weight loss strategies are not long-term effective. There is an increasing need to consider pharmacological approaches to assist weight loss in the so called diabesity syndrome. Aim of this review is to analyze the weight-loss effect of non-insulin glucose lowering drugs in patients with type 2 diabetes.Material and methods A systematic analysis of the literature on the effect of non-insulin glucose lowering drugs on weight loss in patients with type 2 diabetes was performed. For each class of drugs, the following parameters were analyzed: kilograms lost on average, effect on body mass index and body composition.Results Our results suggested that anti-diabetic drugs can be stratified into 3 groups based on their efficacy in weight loss: metformin, acarbose, empagliflozin and exenatide resulted in a in a mild weight loss (less than 3.2% of initial weight); canagliflozin, ertugliflozin, dapagliflozin and dulaglutide induces a moderate weight loss (between 3.2% and 5%); liraglutide, semaglutide and tirzepatide resulted in a strong weight loss (greater than 5%).Conclusions This study shows that new anti-diabetic drugs, particularly GLP1-RA and Tirzepatide, are the most effective in inducing weight loss in patients with type 2 diabetes. Interestingly, exenatide appears to be the only GLP1-RA that induces a mild weight loss.
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“In a recent study by Lazzaroni et al., 61 they documented a higher (>5%) reduction in weight among T2D patients who were given liraglutide, semaglutide, and tirzepatide.”
From Anti-inflammatory role of glucagon-like peptide 1 receptor agonists and its clinical implications (2024) · cites this paper as [61]
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“GLP-1 receptor agonists have been demonstrated to have significant benefits in weight reduction and can also lower the risk of major cardiovascular events, all-cause mortality, hospital admission for heart failure, and worsening kidney function.4,5”
From Tirzepatide: Clinical review of the twincretin injectable (2023) · cites this paper as [5]
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Metadata
- Authors
- Lazzaroni, E., Ben Nasr, M., Loretelli, C., Pastore, I., Plebani, L., Lunati, M. E., Vallone, L., Bolla, A. M., Rossi, A., Montefusco, L., Ippolito, E., Berra, C., D’Addio, F., Zuccotti, G. V., & Fiorina, P.
- Affiliations
- ASST Fatebenefratelli Sacco (IT)
- University of Milan (IT)
- MultiMedica (IT)
- Boston Children's Hospital (US)
- Corresponding author
- Fiorina, Paolo
- ORCID
- Venue
- Pharmacological Research
- Publisher
- Elsevier BV
- Published
- 2021-09
- Volume
- 171
- Pages
- 105782
- ISSN
- 1043-6618 (ISSN-L)
- OpenAlex
- W3184250385
- Cited by
- 182
- References
- 75
- Citations by year
- 2026: 25 · 2025: 43 · 2024: 41 · 2023: 47 · 2022: 23 · 2021: 3
- FWCI
- 4.38
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Pharmacological Research (publishedVersion)
- PubMed (publishedVersion)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Pharmacology (medical) › Pharmacology and Obesity Treatment
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- type 2 diabetes, weight loss, antidiabetic drugs, diabesity, obesity, GLP-1 receptor agonists, tirzepatide, exenatide, SGLT2 inhibitors, metformin, acarbose, body mass index, body composition
- MeSH terms
- Glucagon-Like Peptide-1 Receptor, Glucagon-Like Peptide-1 Receptor Agonists, Diabetes Mellitus, Type 2, Gastric Inhibitory Polypeptide, Humans, Hypoglycemic Agents, Obesity, Weight Loss, Glucagon-Like Peptide 1
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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