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Identifying Target Populations Using Real-World Data to Guide Antidiabetic Drug Trials

Regulatory agencies have recommended designing more representative trials of anti-diabetic drugs, but this first requires defining clinically relevant target populations of patients who would most benefit from the introduction of a new drug. This study used real-world data to construct three target populations and examined their impact on the representativeness of a large cardiovascular outcome trial on an antidiabetic drug.

Cardiovascular outcome trials and target populations

Cardiovascular outcome trials have provided valuable information on the safety and efficacy of new drugs for the treatment of type 2 diabetes. However, a significant limitation of these trials is their focus on patients at a high risk of cardiovascular complications and, therefore, they underrepresent other important risk groups. Subsequently, the FDA has advocated for a broader approach to assessing antidiabetic drugs and is recommending researchers to design more representative trials.

To facilitate this, researchers need to design clinically relevant target populations who would benefit from the approval of a new antidiabetic drug. According to the FDA, the target populations for a drug trial should consist of individuals who are most likely to use the new drug in the real-world setting. Despite this, there is currently little guidance on how to define such target populations using real-world data.

Previously, researchers defined diabetes target populations as all patients with type 2 diabetes or those who received the drug in the real-world setting. However, the issue arises as these target populations do not necessarily include all patients who would have been eligible to receive the drug based on treatment stage, which is a population of patients that most closely aligns with the FDAs definition of a representative target population. Defining a target population before trial initiation should therefore capture a more representative population.

Defining target populations using real-world data

The researchers behind this study evaluated the impact of three different target populations on trial representativeness using the illustrative example of the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial. All of the patients included in the cohort were at least 40 years of age and had at least one year of medical history in the Clinical Practice Research Datalink (CPRD). From their cohort they defined three target populations within a large population-based cohort of patients with type two diabetes as:

  1. All patients with type 2 diabetes regardless of treatment stage.
  2. Patients prescribed the antidiabetic drug – liraglutide – spanning the full market availability of the drug to reduce the influence of transient prescribing trends.
  3. Patients eligible to receive liraglutide according to treatment stage consisting of patients eligible to receive any second-to-fifth-line drug, including liraglutide.


The target population that includes all patients with type 2 diabetes consisted of 279,763 patients. Whereas, the populations including those prescribed liraglutide consisted of 14,421 patients, and those eligible to receive liraglutide consisted of 85,610 patients. The researchers identified several differences across the three target populations. These differences included patients with type 2 diabetes being older, more likely to have well-controlled diabetes, and presented a higher prevalence of macrovascular complications and other comorbidities than the other two target populations. Additionally, the researchers observed that patients prescribed liraglutide were younger, more likely to be obese, and more likely to have uncontrolled diabetes than the other two groups. Finally, those eligible to receive liraglutide were less likely to have a history of myocardial infarction, peripheral arterial disease, nephropathy and other comorbidities.

The researchers applied the LEADER eligibility criteria to the patients identified in each target population, which resulted in the inclusion of 19.1% of patients with type 2 diabetes, 20.7% of patients prescribed liraglutide, and 34.8% of patients eligible to receive liraglutide. The major inclusion criteria of the LEADER trial were uncontrolled diabetes and the presence of cardiovascular complications or risk factors. Whereas the major exclusion criteria were a diagnosis of type 1 diabetes, use of other antidiabetic drugs; patients who intensified treatment within three months of randomization; patients with a history of acute coronary or cerebrovascular events within 14 days of randomization; and history of malignancies.

Overall, the most common reasons for exclusion were well-controlled diabetes, absence of cardiovascular disease or other associated risk factors, use of other antidiabetic drugs and a history of cancer.

Consequences of this study

The researcher’s findings highlight the pitfalls of previously used target populations. Firstly, using all patients with type 2 diabetes as a target population is problematic as it includes all patients regardless of their disease stage. A significant proportion of patients in this target population had well-controlled diabetes and would therefore not have required change to their antidiabetic treatment. This population would also include patients with early- and late-stage diabetes, where liraglutide is not commonly initiated.

Secondly, using patients who have received liraglutide in the real-world setting as a target population for a trial is problematic, as this target population would rely on drugs that are already available on the market for controlling their diabetes. Therefore, it is not feasible to use this target population to design trials of drugs that have not yet been approved by regulatory agencies.

Finally, in contrast to the above target populations, those eligible to receive an antidiabetic drug may be more clinically relevant, as this population is defined by treatment failure and excludes those with well-controlled diabetes as well as those requiring first or last-line therapies. Additionally, by using treatment failure as an entry point, it is possible to establish patient characteristics at the treatment decision point. Moreover, defining such target populations may also help to generate the expected incidence of relevant outcomes, which could help to estimate the sample size requirement and increase the efficiency of trials.

Therefore, before trial investigators recruit patients, they should first define a relevant target population of patients who may use and benefit from the drug being investigated in the real-world setting.


This study proposes a framework by which real-world data can be used before trial recruitment to define target populations, which will help to increase the representativeness of trials. The findings of this study also help to demonstrate why producing more representative trial cohorts is important for increasing efficiency of drug trials. While the researchers behind this study focused on liraglutide, this framework can be applied to other drug classes.

Image credit: jcomp – FreePik

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