Implementation of Estimand Framework in U.S. Regulatory Landscape
The regulatory implementation of the Estimand Framework in the U.S. context has evolved over time, addressing issues related to missing data in clinical trials. Starting from the pre-history of missing data recognition to the development of the ICH E9(R1) framework, the focus has been on aligning pl
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Understanding Estimands in Oncology Clinical Trials
The concept of estimands in oncology clinical trials plays a crucial role in defining treatment effects and analyzing overall survival outcomes. This framework aims to enhance transparency, align trial objectives, and strengthen interdisciplinary dialogues. Introduced by the ICH E9(R1) guideline in
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How to Check a Simulation Study: Methods and Considerations
Simulation studies are often used to evaluate statistical methods and study power, but they can sometimes produce misleading results. This work discusses strategies to assess and improve the quality of simulation studies, drawing on experiences and considerations outlined in relevant literature. A s
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Understanding Estimands at ICH for Improved Trial Objectives
Lack of clarity in trial objectives can lead to confusion among developers, decision-makers, patients, and prescribers. Estimands at ICH, presented by Rob Hemmings, address the need to focus on WHAT to estimate rather than just HOW. Patients differ in response to treatment, and multiple treatment ef
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The Right Way to Code Simulation Studies in Stata
Simulation studies in Stata involve using (pseudo) random numbers to generate data from a distribution for studying statistical methods. This process helps to evaluate different scenarios and understand the properties of statistical techniques. Key components like ADEMP (Aims, Data-generating mechan
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