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arXiv · 2606.03863

Assessing the Impact of Intercurrent Events on Power and Sample Size for Estimands with Time-to-Event Endpoints

Daniel J Bratton·Fiona Guillard·Sunita Rehal·Thomas Drury
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Abstract

The precise definition of a primary estimand, accounting for intercurrent events (IEs) as per the ICH E9(R1) addendum, is fundamental to the design and interpretation of clinical trials. Conventional power and sample size calculations, however, often do not adequately incorporate the impact of IEs and their corresponding handling strategies, creating a risk of over- or under-powered studies. While simulation-based approaches can address this complexity, they are often computationally intensive and may only explore a limited set of scenarios. In this paper, we introduce a set of formulae for calculating power for estimands with time-to-event endpoints, applied to trials with fixed follow-up durations. We focus on estimands that use treatment policy, hypothetical, composite, or a combination of strategies for handling IEs, under the assumption that IEs occur independently of each other and the primary endpoint. Validation against simulation-based estimates shows strong agreement, and we explore deviations in power estimates in scenarios where outcomes and IEs are dependent. We illustrate the practical application of our approach through a case study in nasal polyposis, examining the sensitivity of sample size requirements to varying IE rates and their impacts on post-IE outcomes. The proposed formulae facilitate rapid and accurate power and assurance calculations, enabling clinical trial designs to be more closely aligned with the estimand of interest.

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Daniel J Bratton, Fiona Guillard, Sunita Rehal, Thomas Drury. 2026-06-02. Assessing the Impact of Intercurrent Events on Power and Sample Size for Estimands with Time-to-Event Endpoints. https://arxiv.org/abs/2606.03863

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