Estimands in Clinical Trials

A Practical Guide

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Springer


Paru le : 2026-01-14



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Description

This book provides a comprehensive, up-to-date, and practical introduction to the estimand framework and its application in clinical trials. Since its introduction by the International Council for Harmonisation (ICH) through the E9(R1) guideline in 2019, the estimand framework has led to a significant shift in the design, conduct, analysis, and interpretation of clinical trials. By explicitly aligning trial objectives with the clinical question of interest—and by carefully accounting for intercurrent events—the framework facilitates greater transparency and interpretability of trial results. In recent years, its adoption has supported improved scientific and regulatory dialogue, more targeted trial designs and analysis methods, and a better understanding of treatment effects across drug development programs.
This book reflects both the conceptual underpinnings of the estimand framework and the growing body of experience gained by the scientific and regulatory community since the release of the ICH E9(R1) guideline. Emphasis is placed on practical implementation across a wide range of clinical and therapeutic settings.  Part I introduces the core concepts of the framework and offers detailed guidance on how to describe estimands in clinical trial protocols and related documents. Part II presents a wide range of case studies from various therapeutic areas to support practical implementation. Part III summarizes estimand-related content from regulatory guidelines across different indications. Part IV describes statistical analysis methods and approaches for handling missing data across continuous, binary, recurrent, and time-to-event endpoints. Part V explores the use of the estimand framework in a variety of clinical trial settings.
Designed for a broad audience of professionals and students involved in clinical research, this book will be particularly valuable for those engaged in the design, conduct, and analysis of clinical trials across the drug development lifecycle. It serves both as a structured introduction for those new to the field and a detailed reference for experienced professionals. Whether for academic study or practical implementation, this book is an essential resource for advancing the estimand framework and promoting more robust, informative clinical trials.
Pages
485 pages
Collection
n.c
Parution
2026-01-14
Marque
Springer
EAN papier
9783032021915
EAN PDF
9783032021922

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
48
Taille du fichier
14305 Ko
Prix
137,14 €
EAN EPUB
9783032021922

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
48
Taille du fichier
4239 Ko
Prix
137,14 €

Jiawei Wei is Senior Director Biostatistician in the Advanced Methodology and Data Science group at Novartis. She brings extensive expertise in the design, planning, and analysis of clinical trials and is an active contributor to multiple estimand working groups. Her main research interests include estimands, missing data, as well as recurrent event data.

Leslie Meng is a Clinical Data Science Chapter Head in Global Biostatistics and Data Sciences at Boehringer Ingelheim. She is an experienced biostatistician in drug development across various therapeutic areas. Her primary research interests focus on estimands and multiple testing methodologies in clinical research.

Frank Bretz is a Distinguished Quantitative Research Scientist at Novartis. He has contributed to methodological advancements in several areas of drug development, including adaptive designs, dose finding, estimands, and multiple testing. He served as a member of the ICH E9(R1) Expert Working Group on Estimands and Sensitivity Analysis in Clinical Trials.

Feng Chen is a professor in the Department of Biostatistics at the School of Public Health, Nanjing Medical University. His primary research interests include clinical trial statistics and regulatory science, theoretical and methodological developments in high-dimensional biological data, and the analysis of dependent data. He serves as the chairperson of the China Clinical Trial Statistics (CCTS) Working Group and has been a statistical consulting expert for the National Medical Products Administration (NMPA) of China.

Jun Wang works at the Center for Drug Evaluation (CDE), part of the National Medical Products Administration (NMPA). He leads and contributes to the development of regulatory guidance in biostatistics and actively promotes the application of innovative trial designs in China. He served as a member of the ICH E9(R1) Expert Working Group on Estimands and Sensitivity Analysis in Clinical Trials

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