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For handling intercurrent events in clinical trials, one of the strategies outlined in the ICH E9(R1) addendum targets the hypothetical scenario of non-occurrence of the intercurrent event. While this strategy is often implemented by…

Methodology · Statistics 2024-09-18 Florian Lasch , Lorenzo Guizzaro , Wen Wei Loh

Researchers addressing post-treatment complications in randomized trials often turn to principal stratification to define relevant assumptions and quantities of interest. One approach for estimating causal effects in this framework is to…

Methodology · Statistics 2016-06-09 Avi Feller , Fabrizia Mealli , Luke Miratrix

In clinical trials involving both mortality and morbidity, an active treatment can influence the observed risk of the first non-fatal event either directly, through its effect on the underlying non-fatal event process, or indirectly,…

Methodology · Statistics 2025-11-19 Jiren Sun , Thomas D. Cook

Post-treatment variables often complicate causal inference. They appear in many scientific problems, including noncompliance, truncation by death, mediation, and surrogate endpoint evaluation. Principal stratification is a strategy to…

Methodology · Statistics 2024-04-04 Sizhu Lu , Zhichao Jiang , Peng Ding

Intercurrent events, such as treatment switching, rescue medication, dropout, or truncation by death, frequently complicate intention-to-treat analyses in randomized clinical trials. Existing causal inference frameworks typically target…

Methodology · Statistics 2026-03-12 Georgi Baklicharov , Kelly Van Lancker , Stijn Vansteelandt

Researchers are often interested in treatment effects on outcomes that are only defined conditional on a post-treatment event status. For example, in a study of the effect of different cancer treatments on quality of life at end of…

Causal inference is best understood using potential outcomes. This use is particularly important in more complex settings, that is, observational studies or randomized experiments with complications such as noncompliance. The topic of this…

Statistics Theory · Mathematics 2007-06-13 Donald B. Rubin

The ICH E9(R1) addendum provides guidelines on accounting for intercurrent events in clinical trials using the estimands framework. However, there has been limited attention to the estimands framework for meta-analysis. Using treatment…

Principal stratification is a causal framework to analyze randomized experiments with a post-treatment variable between the treatment and endpoint variables. Because the principal strata defined by the potential outcomes of the…

Statistics Theory · Mathematics 2015-07-22 Zhichao Jiang , Peng Ding , Zhi Geng

Estimands can help to clarify the research questions being addressed in randomised trials. Because the choice of estimand can affect how relevant trial results are to patients and other stakeholders, such as clinicians or policymakers, it…

Intercurrent events, common in clinical trials and observational studies, affect the existence or interpretation of final outcomes. Principal stratification addresses this challenge by defining local average treatment effect estimands…

Methodology · Statistics 2025-09-22 Jiaqi Tong , Brennan Kahan , Michael O. Harhay , Fan Li

In clinical trials, it is often of interest to understand the principal causal effect (PCE), the average treatment effect for a principal stratum (a subset of patients defined by the potential outcomes of one or more post-baseline…

Methodology · Statistics 2022-10-06 Yongming Qu , Ilya Lipkovich , Stephen J. Ruberg

Participants in longitudinal studies on the effects of drug treatment and criminal justice system interventions are at high risk for institutionalization (e.g., spending time in an environment where their freedom to use drugs, commit…

Applications · Statistics 2008-11-13 Beth Ann Griffin , Daniel F. McCaffrey , Andrew R. Morral

When interested in a time-to-event outcome, competing events that prevent the occurrence of the event of interest may be present. In the presence of competing events, various statistical estimands have been suggested for defining the causal…

Methodology · Statistics 2021-09-09 Elisavet Syriopoulou , Sarwar I Mozumder , Mark J Rutherford , Paul C Lambert

Causal inference concerns not only the average effect of the treatment on the outcome but also the underlying mechanism through an intermediate variable of interest. Principal stratification characterizes such a mechanism by targeting…

Methodology · Statistics 2022-03-29 Zhichao Jiang , Shu Yang , Peng Ding

Randomized trials balance all covariates on average and provide the gold standard for estimating treatment effects. Chance imbalances nevertheless exist more or less in realized treatment allocations and intrigue an important question: what…

Methodology · Statistics 2023-07-18 Anqi Zhao , Peng Ding

In clinical trials, principal stratification analysis is commonly employed to address the issue of truncation by death, where a subject dies before the outcome can be measured. However, in practice, many survivor outcomes may remain…

Methodology · Statistics 2025-07-08 Wei Li , Yuan Liu , Shanshan Luo , Zhi Geng

Disruptions in clinical trials may be due to external events like pandemics, warfare, and natural disasters. Resulting complications may lead to unforeseen intercurrent events (events that occur after treatment initiation and affect the…

Applications · Statistics 2024-08-20 Rachael V. Phillips , Mark J. van der Laan

In randomized trials, the per-protocol effect, that is, the effect of being assigned a treatment strategy and receiving treatment according to the assigned strategy, is sometimes thought to reflect the effect of the treatment strategy…

Methodology · Statistics 2025-09-25 Issa J. Dahabreh , Lawson Ung , Miguel A. Hernán , Yu-Han Chiu

Externally controlled trials are crucial in clinical development when randomized controlled trials are unethical or impractical. These trials consist of a full treatment arm with the experimental treatment and a full external control arm.…

Methodology · Statistics 2025-03-11 Chenyin Gao , Xiang Zhang , Shu Yang