This book focuses on novel approaches that provide a reliable basis for identifying what kinds of patients are likely to benefit from the each new treatment.
This book focuses on novel approaches that provide a reliable basis for identifying what kinds of patients are likely to benefit from the each new treatment.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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 and Bioinformatics Section of the National Cancer Institute, a multidisciplinary group of scientists developing and applying methods for the application of genomics to cancer therapeutics. He is the architect of BRB-ArrayTools software for the analysis of microarray expression and copy number data.
Inhaltsangabe
1. Clinical trial basics 2. Actionable prognostic biomarkers 3. Phase II designs 4. Enrichment designs 5. Including both test positive and test negative patients 6. Adaptive threshold design 7. Multiple predictive biomarkers predictive analysis of clinical trials 8. Prospective - retrospective design Appendix A. Statistics background Appendix B. Prognostic classifiers based on high dimensional data.
1. Clinical trial basics 2. Actionable prognostic biomarkers 3. Phase II designs 4. Enrichment designs 5. Including both test positive and test negative patients 6. Adaptive threshold design 7. Multiple predictive biomarkers predictive analysis of clinical trials 8. Prospective - retrospective design Appendix A. Statistics background Appendix B. Prognostic classifiers based on high dimensional data.
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