Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R

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Jianrong Wu

Statistical Methods for Survival Trial Design

With Applications to Cancer Clinical Trials Using R

Jianrong Wu

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English

Chapman & Hall/CRC
18 December 2020

Clinical trials; Medical genetics; Oncology; Probability & statistics

Series: Chapman & Hall/CRC Biostatistics Series

Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R provides a thorough presentation of the principles of designing and monitoring cancer clinical trials in which time-to-event is the primary endpoint. Traditional cancer trial designs with time-to-event endpoints are often limited to the exponential model or proportional hazards model. In practice, however, those model assumptions may not be satisfied for long-term survival trials.

This book is the first to cover comprehensively the many newly developed methodologies for survival trial design, including trial design under the Weibull survival models; extensions of the sample size calculations under the proportional hazard models; and trial design under mixture cure models, complex survival models, Cox regression models, and competing-risk models. A general sequential procedure based on the sequential conditional probability ratio test is also implemented for survival trial monitoring. All methodologies are presented with sufficient detail for interested researchers or graduate students.

By: Jianrong Wu
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 453g
ISBN: 9780367734329
ISBN 10: 036773432X
Series: Chapman & Hall/CRC Biostatistics Series
Pages: 257
Publication Date: 18 December 2020
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Jianrong (John) Wu is a professor in the Division of Cancer Biostatistics, Department of Biostatistics, Markey Cancer Center, University of Kentucky. He has more than 15 years’ experience of designing and conducting cancer clinical trials at St. Jude Children’s Research Hospital and has developed several novel statistical methods for designing phase II and phase III survival trials.

Reviews for Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R

""". . . this book provides a comprehensive introduction to statistical methods in cancer of sample size calculations and survival clinical trial designs from the classical techniques to the newly proposed formulae such as the mixture cure model and a group sequential trial design. This book has a vast list of citations and is an excellent reference for statisticians performing oncology research in the pharmaceutical industry or in other settings, and for graduate students in biostatistics or in related fields."" ~ Journal of Biopharmaceutical Statistics ""I would recommend this book for those that are starting to work with this kind of trial design and would like to have a good overview and source of knowledge for some not so common methods for more complex cancer trial designs, including simple formulae to implement in R to calculate sample sizes."" ~David Manteigas, ISCB Newsletter "". . . this book provides a comprehensive introduction to statistical methods in cancer of sample size calculations and survival clinical trial designs from the classical techniques to the newly proposed formulae such as the mixture cure model and a group sequential trial design. This book has a vast list of citations and is an excellent reference for statisticians performing oncology research in the pharmaceutical industry or in other settings, and for graduate students in biostatistics or in related fields."" ~ Journal of Biopharmaceutical Statistics ""I would recommend this book for those that are starting to work with this kind of trial design and would like to have a good overview and source of knowledge for some not so common methods for more complex cancer trial designs, including simple formulae to implement in R to calculate sample sizes."" ~David Manteigas, ISCB Newsletter"