• Moritz Pohl, Lukas Baumann, Rouven Behnisch, Marietta Kirchner, Johannes Krisam, and Anja Sander.
• Institute of Medical Biometry, University Hospital Heidelberg, Heidelberg, Germany.
• Dtsch Arztebl Int. 2021 Dec 27; 118 (51-52): 883-888.

BackgroundClinical trials are of central importance for the evaluation and comparison of treatments. The transparency and intelligibility of the treatment effect under investigation is an essential matter for physicians, patients, and health-care authorities. The estimand framework has been introduced because many trials are deficient in this respect.MethodsIntroduction, definition, and application of the estimand framework on the basis of an example and a selective review of the literature.ResultsThe estimand framework provides a systematic approach to the definition of the treatment effect under investigation in a clinical trial. An estimand consists of five attributes: treatment, population, variable, population-level summary, and handling of intercurrent events. Each of these attributes is defined in an interdisciplinary discussion during the trial planning phase, based on the clinical question being asked. Special attention is given to the handling of intercurrent events (ICEs): these are events-e.g., discontinuation or modification of treatment or the use of emergency medication-that can occur once the treatment has begun and might affect the possibility of observing the endpoints or their interpretability. There are various strategies for the handling of ICEs; these can, for example, also reflect the existing intention-to-treat (ITT) principle. Per-protocol analyses, in contrast, are prone to bias and cannot be represented in a sensible manner by an estimand, although they may be performed as a supplementary analysis. The discussion of potential intercurrent events and how they should appropriately be handled in view of the aim of the trial must already take place in the planning phase.ConclusionUse of the estimand framework should make it easier for both physicians and patients to understand what trials reveal about the efficacy of treatment, and to compare the results of different trials.

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