Föreläsningar och seminarier Causal Estimands for Clinical and Regulatory Decision Making

About the speaker: Professor Hernán is the Kolokotrones Professor of Biostatistics and Epidemiology Department of Epidemiology, Director, CAUSALab, Harvard T.H. Chan School of Public Health, and Principal Researcher CAUSALab IMM, Karolinska Institutet

Abstract: The estimand is what we want to estimate. When conducting research for clinical and regulatory purposes, the causal estimand typically involves the causal effect of an intervention. Three frameworks have been proposed to describe the causal estimand in randomized trials and observational studies: PICO, the target trial framework, and the E9 (R1) Addendum of the International Council for Harmonisation (ICH). This talk provides a side-by-side comparison of these three estimand frameworks for causal inference, translate across their terminologies, and highlight their commonalities and peculiarities. For decision makers who ask causal questions, the target trial framework subsumes the other two frameworks by providing the most flexibility and level of detail.

Contact: Anita Berglund, CAUSALab IMM, KI: anita.berglund@ki.se

Supported by funding from the Swedish Research Council