Comparative Effectiveness of Sodium-Glucose Co-Transporter 2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists in Type 2 Diabetes: Randomised and Real-World Evidence
Sodium-glucose co-transporter 2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) are two of the most recently developed treatment classes in the management of blood-glucose levels in individuals with Type 2 diabetes. While individual treatments have been analysed in randomised controlled trials (RCTs) and observational studies, comparisons of treatments within and between treatment classes are not as well established. In this thesis, using a number of methodological techniques, SGLT-2is and GLP-1RAs were compared for their cardiovascular, cardiometabolic and safety risks in both randomised and observational settings.
Throughout this thesis, network meta-analyses (NMA) techniques were used to assess the eficacy and effectiveness of SGLT-2is and GLP-1RAs in RCTs and observational data, separately. Using the real-world database, the Clinical Practice Research Datalink, the effectiveness of treatments within these classes were considered in a UK healthcare setting. In order to provide a comprehensive overview of treatments, RCT data and observational data were synthesised using an extension of NMA models with a power-prior transformation, which allowed for adjustments to be made for the various sources of information.
Results from this thesis showed both classes of medications improved health outcomes in individuals with Type 2 diabetes in both RCTs and observational studies. Comparisons between treatment groups highlighted the bene?ts of individual treatments for cardiovascular risk, such as hospital admissions due to heart failure, as well as cardiometabolic risk, such as glycated haemoglobin (HbA1c), body weight and blood pressure levels. Assessment of adverse events showed increased risk of genito-mycotic infection with SGLT-2is and increased risk gastro-intestinal side e?ects in GLP-1RAs, in line with their pharmacological mechanisms. These analyses and results can contribute to the growing body of evidence in Type 2 diabetes management, as well as inform clinicians in the most appropriate treatment plan for individualised care in Type 2 diabetes.
Supervisor(s)Laura Gray; Kamlesh Khunti; Francesco Zaccardi
Date of award2023-06-14
Author affiliationDepartment of Health Sciences
Awarding institutionUniversity of Leicester