Dealing with multiple intercurrent events using hypothetical and treatment policy strategies simultaneously
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866916598490595328 |
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| author | Parra, Camila Olarte Daniel, Rhian M. Bartlett, Jonathan W. |
| author_facet | Parra, Camila Olarte Daniel, Rhian M. Bartlett, Jonathan W. |
| contents | To precisely define the treatment effect of interest in a clinical trial, the ICH E9 estimand addendum describes that relevant so-called intercurrent events should be identified and strategies specified to deal with them. Handling intercurrent events with different strategies leads to different estimands. In this paper, we focus on estimands that involve addressing one intercurrent event with the treatment policy strategy and another with the hypothetical strategy. We define these estimands using potential outcomes and causal diagrams, considering the possible causal relationships between the two intercurrent events and other variables. We show that there are different causal estimand definitions and assumptions one could adopt, each having different implications for estimation, which is demonstrated in a simulation study. The different considerations are illustrated conceptually using a diabetes trial as an example. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_03329 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Dealing with multiple intercurrent events using hypothetical and treatment policy strategies simultaneously Parra, Camila Olarte Daniel, Rhian M. Bartlett, Jonathan W. Methodology To precisely define the treatment effect of interest in a clinical trial, the ICH E9 estimand addendum describes that relevant so-called intercurrent events should be identified and strategies specified to deal with them. Handling intercurrent events with different strategies leads to different estimands. In this paper, we focus on estimands that involve addressing one intercurrent event with the treatment policy strategy and another with the hypothetical strategy. We define these estimands using potential outcomes and causal diagrams, considering the possible causal relationships between the two intercurrent events and other variables. We show that there are different causal estimand definitions and assumptions one could adopt, each having different implications for estimation, which is demonstrated in a simulation study. The different considerations are illustrated conceptually using a diabetes trial as an example. |
| title | Dealing with multiple intercurrent events using hypothetical and treatment policy strategies simultaneously |
| topic | Methodology |
| url | https://arxiv.org/abs/2502.03329 |