Textbook of Clinical Trials in Oncology A Statistical Perspective

There is an increasing need for educational resources for statisticians and investigators. Reflecting this, the goal of this book is to provide readers with a sound foundation in the statistical design, conduct, and analysis of clinical trials. Furthermore, it is intended as a guide for statisticians and investigators with minimal clinical trial experience who are interested in pursuing a career in this area. The advancement in genetic and molecular technologies have revolutionized drug development. In recent years, clinical trials have become increasingly sophisticated as they incorporate genomic studies, and efficient designs (such as basket and umbrella trials) have permeated the field. This book offers the requisite background and expert guidance for the innovative statistical design and analysis of clinical trials in oncology.

Key Features:

• Cutting-edge topics with appropriate technical background
• Built around case studies which give the work a "hands-on" approach
• Real examples of flaws in previously reported clinical trials and how to avoid them
• Access to statistical code on the book?s website
• Chapters written by internationally recognized statisticians from academia and pharmaceutical companies
• Carefully edited to ensure consistency in style, level, and approach
• Topics covered include innovating phase I and II designs, trials in immune-oncology and rare diseases, among many others

The need for this book. Selection of endpoints. Co-primary Endpoints. Surrogate Endpoints. Innovative Phase I. Phase II. Phase II Biomarker, basket trials. Sample Size for phase III. Multi-Arm trials. Non-inferiority trials. Cure Rate. Design and Analysis of Immunotherapy Trials Data Monitoring Superiorirty and Futility Monitoring. Competing Risks. Missing Data. Multiple Comparison. Biomarker-based clinical trials. Adaptive designs. Trials designs for rare diseases in oncology. Prognostic Models. Validation Approaches. Identification of Predictive Markers. Subgroup Analysis. Statistical Issues in Genomic Studies. Developing and Validation of Signature

Susan Halabi, Ph.D. is Professor of Biostatistics and Bioinformatics, Duke University, USA. She has extensive experience in the design and analysis of clinical trials in oncology. Dr. Halabi is a fellow of the American Statistical Association, the Society of Clinical Trials, and the American Society of Clinical Oncology. She serves on the Oncologic Drugs Advisory Committee for the Food and Drug Administration.

Stefan Michiels, Ph.D. is Head of the Oncostat team of the Center for research in epidemiology and population health (INSERM U1018, University Paris-Saclay, University Paris-Sud) at Gustave Roussy, Villejuif, France. His areas of expertise are clinical trials, meta-analyses and prediction models in oncology. Stefan is the currently the chair of the biostatisticians at Unicancer, a French collaborative cancer clinical trials group. Stefan holds a PhD in Biostatistics from the School of Public Health at the University Paris-Sud and Master Degrees in Statistics and in Applied Mathematics from the University of Leuven. His previous positions include the Université Libre de Bruxelles- Institut Jules Bordet (Belgium), the National Cancer Institute (France) and the University of Leuven (Belgium). He is currently member of the editorial board of the Journal of the National Cancer Institute and Annals of Oncology.