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Clinical Trial Design and other Statistical Issues. Mary A. Foulkes, Ph.D. Office of Biostatistics and Epidemiology. Blood Products Advisory Committee March 17, 2005. “Chance favors the prepared mind” Louis Pasteur. Novel Statistical Applications. Usual approach:
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Clinical Trial Design and other Statistical Issues Mary A. Foulkes, Ph.D. Office of Biostatistics and Epidemiology Blood Products Advisory Committee March 17, 2005
Novel Statistical Applications Usual approach: Develop theory/model/method Seek application Critical Path approach: No prior stat approach or existing approximation Develop new or improved theory/model/method
Quantitative Methods • Maximizing efficiency while maintaining reliability • Improved analytic approaches • Flexible study designs • Transparency • Best Practices • Underlying assumptions
CBER Products • Blood, blood products and tissues • Life-saving therapies • Potential to transmit serious disease • Cellular and gene therapies • Vaccines
Study Endpoints • Biomarkers • Intermediate endpoints • Composite endpoints • Multiple endpoints • Assessment scales
Statistics in Manufacturing • Quality control in blood collection • Low volume processing • False positives highly burdensome • Efficiency potential in alternative statistical approaches • Vaccine lot consistency
Flexible Study Design • Initial parameters may be inaccurate • Interim modifications may improve trial ability to answer question • Traditional approaches • Group sequential designs with early stopping for efficacy, harm, futility • Other changes if not influenced by knowledge of interim data • Emerging approaches
Flexible Designs for Biologics • CBER regulates cutting-edge products • May be less information on design parameters, more need for flexibility • Safety concerns • Optimal design approaches?
Trial Design & Analyses • Non-inferiority trials • ICH E10 gives gen’l principles, not specifics • Optimal approach for defining acceptable difference not yet defined • Missing data • No preferred analytic approach • Implications of assumptions
Summary • Quantitative methods are central to many critical path issues • Quantitative methods will be needed to evaluate potential gain from new approaches • Statisticians and Epidemiologists involved in many issues identified by stakeholders