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Activity Number:
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189
- SBR Showcase: Recent Advances in Statistical Methodology for Medical Product Development
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Type:
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Invited
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Date/Time:
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Tuesday, August 10, 2021 : 1:30 PM to 3:20 PM
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Sponsor:
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Statistics in Biopharmaceutical Research Journal
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Abstract #316574
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Title:
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Causal Inference and Estimands in Clinical Trials
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Author(s):
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Ilya Lipkovich* and Bohdana Ratitch and Craig Mallinckrodt
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Companies:
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Eli Lilly and Bayer and Biogen Idec
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Keywords:
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Causal inference;
Estimands;
Intercurrent events;
Potential outcomes
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Abstract:
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The NRC (2010) report on the prevention and treatment of missing data highlighted the need to clearly specify causal estimands. The ICH E9(R1) addendum (2019) was another major step in promoting the use of the causal estimands framework in clinical practice. The language of potential outcomes (PO) is widely accepted in the causal inference literature but is not yet recognized in the clinical trial community and was not used in defining causal estimands in ICH E9(R1). We argue that the use of PO language and solid causal foundation in our thinking and writing can help to further disambiguate estimand definitions. In this presentation, we bridge the gap between the causal inference community and clinical trialists by advancing the use of causal estimands in clinical trial settings. We illustrate how concepts from causal literature, such as POs and dynamic treatment regimens, can facilitate defining and implementing causal estimands for different types of outcomes providing a unifying language for both observational and randomized clinical trials.
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Authors who are presenting talks have a * after their name.
