This book provides statisticians with an understanding of the critical challenges currently encountered in oncology trials. Top researchers in academia, government, and the industry present many examples drawn from real trials. The book covers state-of-the-art approaches to the design and analysis of cancer clinical trials, such as adaptive designs, biomarker-based trials, and dynamic treatment regimes. It also explains the importance of the selection of endpoints, use of historical data, multiplicity, analysis of safety data, discovery and validation of predictive signatures, dose-finding, sample size, and non-inferiority designs.
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