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Genomic Clinical Trials and Predictive Medicine

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ISBN-10: 1107401356

ISBN-13: 9781107401358

Edition: 2012

Authors: Richard M. Simon

List price: $25.99
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Description:

Genomics is majorly impacting therapeutics development in medicine. This book contains up-to-date information on the use of genomics in the design and analysis of therapeutic clinical trials with a focus on novel approaches that provide a reliable basis for identifying which patients are most likely to benefit from each treatment. It is oriented to both clinical investigators and statisticians. For clinical investigators, it includes background information on clinical trial design and statistical analysis. For statisticians and others who want to go deeper, it covers state-of-the-art adaptive designs and the development and validation of probabilistic classifiers. The author describes the…    
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Book details

List price: $25.99
Copyright year: 2012
Publisher: Cambridge University Press
Publication date: 1/7/2013
Binding: Paperback
Pages: 150
Size: 6.89" wide x 9.69" long x 0.39" tall
Weight: 0.682
Language: English

Dr Richard M. Simon is chief of the Biometric Research Branch of the National Cancer Institute, where he is chief statistician for the Division of Cancer Treatment and Diagnosis. He is the lead author of the textbook Design and Analysis of DNA Microarray Experiments and has more than 450 publications. Simon has been influential in promoting excellence in clinical trial design and analysis. He has served on the Oncologic Advisory Committee of the US Food and Drug Administration and is a frequent advisor to government, academic and industry organizations involved with developing improved treatments and diagnostics for patients with cancer. In 1998 Dr Simon established the Molecular Statistics…    

Clinical trial basics
Actionable prognostic biomarkers
Phase II designs
Enrichment designs
Including both test positive and test negative patients
Adaptive threshold design
Multiple predictive biomarkers predictive analysis of clinical trials
Prospective - retrospective design
Statistics background
Prognostic classifiers based on high dimensional data