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Bethesda North Marriott Hotel and Conference Center

2015 年 04 月 20 日 8:30 上午 - 2015 年 04 月 22 日 4:30 下午

5701 Marinelli Road, , North Bethesda, MD 20852 , USA

DIA/FDA Statistics 2015 Forum

Session 3: Estimands and Sensitivity Analyses

Session Chair(s)

Feng  Li

Feng Li

Lead Mathematical Statistician

FDA/CDER, United States

Frank  Bretz, PHD

Frank Bretz, PHD

Distinguished Quantitative Research Scientist

Novartis , Switzerland

Defining the primary objective of a clinical trial in the presence of non-compliance or non-adherence to the assigned treatment is crucial for the choice of design, the statistical analysis and the interpretation of the results. This raises the need for a structured framework to specify the primary estimand (i.e. "what is to be estimated"). The missing data report released in 2010 by the National Academy of Science, “Prevention and Treatment of Missing Data in Clinical Trials”, recommends explicit specification of a casual estimand in the protocol of a confirmatory trial. This is also reflected by the decision of ICH to amend its E9 guidance in the coming years to discuss estimands and their role in clinical trials. In this session we will discuss a clear definition of estimands and how the choice of an estimand is linked to important considerations around trial design, conduct and analysis.

Speaker(s)

Mouna  Akacha, PHD

Framework for Estimands

Mouna Akacha, PHD

Novartis Pharma AG, Switzerland

Group Head of Statistical Methodology

Bradley  McEvoy

Case Study

Bradley McEvoy

FDA, United States

Mathematical Statistician, Division of Biometrics II, OBS, OTS, CDER

Thomas J. Permutt, PHD

Panelists (joining the Speakers)

Thomas J. Permutt, PHD

FDA, United States

Associate Director for Statistical Science and Policy, OB, OTS, CDER

Christine  Fletcher, MSC

Christine Fletcher, MSC

GlaxoSmithKline, United Kingdom

VP/Head, Speciality and Primary Care Statistics

Stephen  Ruberg, PHD, MS

Stephen Ruberg, PHD, MS

Analytix Thinking, United States

President; Adjunct Professor of Statistics, Purdue University

Daniel O. Scharfstein

Daniel O. Scharfstein

Johns Hopkins University, United States

Associate Professor of Biostatistics

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