Exploring Heterogeneous Treatment Effects of First-Line Antihypertensive Medications via Target Trials

Presentation Time: 10:45 AM - 11:00 AM

Abstract Keywords: Causal Inference, Precision Medicine, Real-World Evidence Generation, Clinical Decision Support
Primary Track: Applications
Programmatic Theme: Clinical Research Informatics

Personalized treatment for hypertension can potentially improve blood pressure control rates. To overcome limitations of traditional comparative effectiveness trials, we used causal machine learning to identify clinical factors that contribute to heterogeneous treatment effects of antihypertensive medications classes in terms of blood pressure reduction. Additionally, we used trial emulation to quantify heterogeneous treatment effects in different patient populations based on those factors. We found significant variations in certain patient groups for diuretics.

Speaker(s):
Jingzhi Yu, BA
Northwestern University Feinberg School of Medicine

Author(s):
Abel Kho, MD, FACMI - Northwestern University; Norrina Allen, PhD - Northwestern University Feinberg School of Medicine; Luke Rasmussen, MS, FAMIA - Northwestern University; Lucia Petito, PhD - Northwestern University Feinberg School of Medicine;