Using principal stratification in analysis of clinical trials

Abstract

The ICH E9(R1) addendum (2019) proposed principal stratification (PS) as one of five strategies for dealing with intercurrent events. Therefore, understanding the strengths, limitations, and assumptions of PS is important for the broad community of clinical trialists. Many approaches have been developed under the general framework of PS in different areas of research, including experimental and observational studies. These diverse applications have utilized a diverse set of tools and assumptions. Thus, need exists to present these approaches in a unifying manner. The goal of this tutorial is threefold. First, we provide a coherent and unifying description of PS. Second, we emphasize that estimation of effects within PS relies on strong assumptions and we thoroughly examine the consequences of these assumptions to understand in which situations certain assumptions are reasonable. Finally, we provide an overview of a variety of key methods for PS analysis and use a real clinical trial example to illustrate them. Examples of code for implementation of some of these approaches are given in supplemental materials.

References in corpus (5)

• Principal Stratum Strategy: Potential Role in Drug Development
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• Implementation of Tripartite Estimands Using Adherence Causal Estimators Under the Causal Inference Framework
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Cited by in corpus (2)

• Using modified intention-to-treat as a principal stratum estimator for failure to initiate treatment
• Outcomes truncated by death in RCTs: a simulation study on the survivor average causal effect