Exploring heterogeneous treatment effects for GLP-1 receptor agonists in patients with type 2 diabetes

Understanding treatment effect heterogeneity (TEH) is essential to improve care for patients living with chronic diseases like type 2 diabetes. Individual responses to treatment can vary substantially, and identifying the factors that drive TEH may enable increased personalization of treatment and follow-up. In this study, we conduct an exploratory analysis of TEH for glucagon-like peptide-1 receptor agonists used to treat type 2 diabetes. Endpoints are defined using hemoglobin A1c measurements, body mass index, and blood pressure. We use causal forests to conduct global tests for TEH, estimate variable importances to rank candidate effect modifiers, and estimate the magnitude of heterogeneity. Data from three clinical trials are analyzed: SUSTAIN 6 (subcutaneous semaglutide versus placebo, n=3297), PIONEER 6 (oral semaglutide versus placebo, n=3183), and LEADER (subcutaneous liraglutide versus placebo, n=9340), pooled to 13,670 patients after exclusions. Baseline hemoglobin A1c ranks highest among candidate effect modifiers across methods, and kidney function ranks next in the relative risk causal forest; we discuss their clinical implications. The magnitude estimates, however, show that the variation these covariates jointly explain is small. As such, large covariate-driven heterogeneity can be ruled out in these trials, and the average treatment effect provides a reasonable summary for most patients.