Key result
Applying the ICH-E9 estimand framework to observational pharmacoepidemiologic studies clarifies research questions and aligns study design with the targeted treatment decision.
Why the study?
The objectives of a pharmacoepidemiologic comparative effectiveness or safety study should ideally dictate its design and data analysis, making estimand definition instrumental.
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Design
Methodological paper applying ICH-E9 R1 estimands to three observational case studies
Defining estimands may clarify objectives in observational pharmacoepidemiologic studies; extends ICH-E9 framework beyond randomized trials.
PURPOSE: Ideally, the objectives of a pharmacoepidemiologic comparative effectiveness or safety study should dictate its design and data analysis. This paper discusses how defining an estimand is instrumental to this process. METHODS: We applied the ICH-E9 (Statistical Principles for Clinical Trials) R1 addendum on estimands - which originally focused on randomized trials - to three examples of observational pharmacoepidemiologic comparative effectiveness and safety studies. Five key elements specify the estimand: the population, contrasted treatments, endpoint, intercurrent events, and population-level summary measure. RESULTS: Different estimands were defined for case studies representing three types of pharmacological treatments: (1) single-dose treatments using a case study about the effect of influenza vaccination versus no vaccination on mortality risk in an adult population of ≥60 years of age; (2) sustained-treatments using a case study about the effect of dipeptidyl peptidase 4 inhibitor versus glucagon-like peptide-1 agonist on hypoglycemia risk in treatment of uncontrolled diabetes; and (3) as needed treatments using a case study on the effect of nitroglycerin spray as-needed versus no nitroglycerin on syncope risk in treatment of stabile angina pectoris. CONCLUSIONS: The case studies illustrated that a seemingly clear research question can still be open to multiple interpretations. Defining an estimand ensures that the study targets a treatment effect that aligns with the treatment decision the study aims to inform. Estimand definitions further help to inform choices regarding study design and data-analysis and clarify how to interpret study findings.
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Luijken et al. (2023) reported a review. Applying the ICH-E9 estimand framework to observational pharmacoepidemiologic studies clarifies research questions and aligns study design with the targeted treatment decision.
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