Using Real-World Data to Examine the Impact of Different Target Populations on the Representativeness of Cardiovascular Outcome Trials of Antidiabetic Drugs

Date of ISAC Approval: 
30/07/2020
Lay Summary: 
Type 2 diabetes is a disease due to high blood sugar resulting in many health problems. Experts look at clinical studies to decide if antidiabetic drugs are effective. However, patients enrolled in these clinical studies may not be similar to individuals who are likely to receive the drug in the real-world. Determining how similar the patients in the clinical studies are to such likely drug users is important to decide if the study results are useful. However, it is unclear who are the ideal group of likely drug users. Using the United Kingdom Clinical Practice Research Datalink, we will identify three groups of likely drug users and examine their similarity with the individuals enrolled in the clinical studies. This study will help experts to find out which group of likely drug users best help determine the real-world usefulness of clinical studies.
Technical Summary: 
Cardiovascular outcome randomized controlled trials (CVOTs) are conducted among patients with type 2 diabetes at high risk of cardiovascular outcomes to evaluate the cardiovascular safety of antidiabetic drugs. However, type 2 diabetes is a heterogenous disease, and multiple clinically relevant subgroups remain underrepresented in these trials. This has resulted in regulatory concerns regarding the applicability of the safety results from the CVOT in the larger population of patients with type 2 diabetes. Simultaneously, this has resulted in a limited incorporation of the trial results in clinical guidelines, as the trials are unable to provide guidance for patients who are not at a high risk of cardiovascular disease. Thus, examining the representativeness of CVOTs to wider populations of drug users in diabetes is of critical importance. To this end, using the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial of liraglutide as an illustrative example, we will examine its representativeness based on three different target populations: all patients with type 2 diabetes, liraglutide users, and liraglutide candidates. Liraglutide candidates are a target population comprising of individuals who are eligible to receive liraglutide according to treatment guidelines. Using the CPRD, we will identify these three target populations. We will then apply the eligibility criteria of the LEADER trial on each target population and determine the percentage of individuals in the target who would be eligible to be included in the LEADER trial. We will use a logistic regression model to calculate the propensity score distance between the entire target population and the individuals within the target who are eligible for the LEADER trial. Together, this study will determine the ideal target populations and the appropriate measures to be used while determining the representativeness of CVOTs.
Health Outcomes to be Measured: 
Percent eligible in the target population after applying the inclusion and exclusion criteria of the LEADER trial.
Collaborators: 

Dr Samy Suissa - Chief Investigator - McGill University
Ms Devin Abrahami - Collaborator - McGill University
Dr Elodie Baumfeld Andre - Collaborator - Roche
Hui (Hoi) Yin - Collaborator - Sir Mortimer B Davis Jewish General Hospital
Dr Laurent Azoulay - Corresponding Applicant - McGill University
Oriana Hoi Yun Yu - Collaborator - Sir Mortimer B Davis Jewish General Hospital
Dr Richeek Pradhan - Collaborator - Sir Mortimer B Davis Jewish General Hospital
Dr Vaishali Sahasrabudhe - Collaborator - Pfizer Ltd - UK