December 4-8, 2017 at Atlantic City, New Jersey
The 73rd Deming Conference on Applied Statistics
Sponsored by Metropolitan Section, ASQ and Biopharmaceutical Section, ASA

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12/8/2016 - 12/9/2016 (Thursday and Friday)

Short Course 1: Adaptive designs and multiple testing

Prof. Franz König, Medical University of Vienna
Prof. Martin Posch, Medical University of Vienna
Dr. Frank Bretz, Novartis Pharma AG

Moderator: Ivan Chan
This 2-day course gives an introduction to multiple testing, adaptive design and dose finding methodology and its application in clinical trials. We cover common multiple testing problems including the comparison of several doses with a control, assessing the benefit of a new treatment for more than one endpoint, testing of subgroups, combined non-inferiority and superiority testing, or any combination thereof. Besides more traditional approaches, we introduce graphical methods and show how to construct multiple testing procedures which reflect the often complex contextual relations between hypotheses in clinical trials. In addition to fixed sample tests, we give an introduction to the key principles and statistical methodologies of adaptive designs for clinical trials. Adaptive (flexible) designs allow for mid-course design adaptations based on interim data without compromising the overall type I error rate. Examples of design adaptations are the adjustment of sample sizes or the number and timing of interim analyses. These design parameters may be adapted depending on interim estimates of the variance, the treatment effect and safety parameters. An important field of application of the adaptive design methodology are clinical trials with several treatment arms, where promising treatments can be selected at an interim analysis. Using adaptive multiple test procedures the type I error rate can be controlled even if the selection rule, the number of selected treatments or the final sample sizes are not prefixed. Adaptive multiple testing procedures can also be used in adaptive designs with the option of population enrichment. In such designs a sub population may be selected in an interim analysis and further recruitment of patients is restricted to the selected subgroup.

Another application arises in dose finding studies, where multiplicity due to model uncertainty has to be addressed, e.g. by using MCP-Mod. Finally, we show how the toolbox of multiple testing, adaptive designs and dose finding methodology can be combined to design confirmatory phase II/III trials and several case studies will be discussed.

Day 1: Morning Session: Multiple Testing

  • Introduction to the course
  • Multiple Comparison Procedures (MCP): from Bonferroni to closed testing
  • Graphical approaches to multiple testing

Day 1: Afternoon Session: Adaptive Clinical Trial Designs
  • Group sequential designs
  • Adaptive combination tests
  • Multiple testing in adaptive designs
  • Case Studies

Day 2: Morning Session: Exploratory and confirmatory dose finding

  • Introduction to dose finding
  • MCP-Mod
  • Confirmatory MCP-Mod
  • Adaptive MCP-Mod

Day 2: Afternoon Session:
  • Adaptive Graph Based Methods
  • Regulatory and practical experience with innovative trial designs
  • Questions and conclusions

Papers to familiarize with the topics:

  • Alosh M, Bretz F, Huque M (2014). Advanced multiplicity adjustment methods in clinical trials. Statistics in Medicine, 33(4), 693-713.
  • Bauer P, Bretz F, Dragalin V, Koenig F, Wassmer G. (2016) Twenty-five years of confirmatory adaptive designs: opportunities and pitfalls. Statistics in Medicine 35, 325-347. Free download from
  • Bretz F, Koenig F, Brannath W, Glimm E, Posch M (2009). Adaptive designs for confirmatory clinical trials. Statistics in Medicine, 28(8), 1181-1217.
  • Koenig F, Brannath W, Bretz F, Posch M (2008). Adaptive Dunnett tests for treatment selection. Statistics in Medicine 27,1612–1625.
  • Pinheiro J, Bornkamp B, Glimm E, Bretz F. (2014). Model-based dose finding under model uncertainty using general parametric models. Statistics in Medicine, 33(10), 1646-1661.
  • Posch M, Koenig F, Branson M, Brannath W, Dunger-Baldauf C, Bauer P. (2005) Testing and estimating in flexible group sequential designs with adaptive treatment selection. Statistics in Medicine 24, 3697–3714.
  • Bretz F, Maurer W, Maca J (2014) Graphical Approaches to Multiple Testing. Chapter 14 in: Clinical Trial Biostatistics and Biopharmaceutical Applications (ed: Young and Chen), Taylor & Francis, Boca Raton.

Important Regulatory Guidance Documents:

  • EMA Points to Consider on Multiplicity Issues in Clinical Trials
  • EMA Reflection Paper on Adaptive Design
  • US FDA Draft Guidance on Adaptive Design Clinical Trials for Drugs and Biologics
  • ICH E4 Dose-response information to support drug registration
  • EMA Qualification opinion of MCP-Mod as an efficient statistical methodology for model-based design and analysis of phase-II dose-finding studies under model uncertainty (link to furhter documents )

Franz König is Associate Professor at the Section of Medical Statistics at the Medical University of Vienna, Austria. He regularly serves as member of ethics committees and DSMBs. From 2008 till 2010 he was seconded to the European Medicines Agency as statistical expert. His main research interests are multiple testing and adaptive designs. See .

Martin Posch is professor of Medical Statistics at the Medical University of Vienna, Austria, and head of the Center for Medical Statistics, Informatics and Intelligent Systems. From 2011-2012 he worked as statistical expert at the European Medicines Agency. His research interests are group sequential trials, adaptive designs and multiple testing. See

Dr. Frank Bretz joined Novartis in 2004, where he is currently Global Head of the Statistical Methodology and Consulting group. He has supported the methodological development in various areas of drug development, including dose-finding, multiple comparisons, and adaptive designs. He is an Adjunct Professor at the Hannover Medical School, the Shanghai University of Finance and Economics and the Medical University of Vienna.

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