Session (CTI)

Purpose Estimands are now firmly embedded in regulatory guidance and are gaining prominence in HTA, with formal relevance under the EU JCA. Despite this shared framework, challenges remain in translating trial results across decision contexts. Regulatory estimands are typically defined to support benefit–risk assessment under controlled trial conditions, whereas HTA/JCA decision making often require comparative effectiveness aligned with clinical practice. These differing objectives can have implications from trial design to evidence interpretation. A key methodological tension arises between the JCA scope, formulated using a PICO framework, and the estimand attributes required to explicitly address intercurrent events. While PICO specifies population, intervention, comparator, and outcome, it does not fully articulate how events such as treatment discontinuation, switching or subsequent therapies should be handled, whereas estimands require these assumptions to be made explicit. Ultimately, analyses described in the estimand format are required for JCA submission. As such, misalignment between PICOs and estimands can complicate interpretation, limit reuse of regulatory analyses, and reduce the relevance of trial evidence for JCA assessment. Description This workshop aims to compare regulatory and HTA/JCA requirements and their implications for estimand definition; examine how intercurrent events and trial design choices influence the applicability of estimands across decision contexts; and identify practical strategies to improve early alignment and transparency to support JCA relevant comparative effectiveness assessment. The session will feature perspectives from industry, regulatory, academic/HTA and EFPSI with experience in estimands and real-world evidence. With practical examples, speakers will discuss intercurrent event handling, trial design constraints, and considerations when extending the estimand framework beyond clinical trials to JCA. Interactive polling and moderated audience discussion will identify common challenges and actionable approaches to improve alignment, interpretability, and decision relevance across the evidence continuum.