Causal Inference and Causal Estimands from Target Trial Emulations Using Evidence from Real-World Observational Studies and Clinical Trials

This course will (1) introduce causal principles, causal diagrams and target trial emulation to avoid self-inflicted biases, (2) provide an overview of causal methods for baseline confounding and time-varying confounding, (3) propose appropriate estimands to ensure decision problems are directly addressed when analyzing observational data or data from clinical trials affected by treatment switching, (4) present lessons learned from applied case examples in HTA (5) provide recommendations regarding the use of causal inference methods and estimands and their application in causal modeling, and (6) discuss acceptance and barriers from an HTA agency perspective.