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Panel forum on multiple comparison procedures: a commentary from a complex trial design and analysis plan
Sue-Jane Wang1, Frank Bretz, Alex Dmitrienko
1U.S. Food and Drug Administration, HFD-700, WO 21, MailStop Room 3562, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA. suejane.wang@fda.hhs.gov
Abstract:
Motivated by a complex study design aiming at a definitive evidential setting, a panel forum among academia, industry, and US regulatory statistical scientists was held at the 7th International Conference on Multiple Comparison Procedures (MCP) to comment on the multiplicity problem. It is well accepted that studywise or familywise, type I error rate control is the norm for confirmatory trials. But, it is an uncharted territory regarding the criteria beyond a single confirmatory trial. The case example describes a Phase III program consisting of two placebo-controlled multiregional clinical trials identical in design intended to support registration for treatment of a chronic condition in the lung. The case presents a sophisticated multiplicity problem in several levels: four primary endpoints, two doses, two studies, two regions with different regulatory requirements, one major protocol amendment on the original statistical analysis plan, which the panelists had a chance to study before the forum took place. There were differences in professional perspectives among the panelists laid out by sections. Nonetheless, irrespective of the amendment, it may be arguable whether the two studies are poolable for the analysis of two primary endpoints prespecified. How should the study finding be reported in a scientific journal if one health authority approves while the other does not? It is tempting to address the Phase III program level multiplicity motivated by the increasing complexity of the partial hypotheses framework posed that are across studies. A novel thinking of the MCP procedures beyond individual-study level (studywise or familywise as predefined) and across multiple-study level (experimentwise and sometimes programwise) will become an important research problem expected to face with scientific and regulatory challenges.
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