Survival Analysis Using Primary and Surrogate Endpoints PDF Download
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Author: Gail E. Tudor
Publisher:
ISBN:
Category : Biometry
Languages : en
Pages : 104
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Book Description
Author: Gail E. Tudor
Publisher:
ISBN:
Category : Biometry
Languages : en
Pages : 104
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Book Description
Author: Geert Molenberghs
Publisher: Springer Science & Business Media
ISBN: 9780387202778
Category : Mathematics
Languages : en
Pages : 440
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Book Description
Covers the latest research on a sensitive and controversial topic in a professional and well researched manner. Provides practical outlook as well as model guidelines and software tools that should be of interest to people who use the software tools described and those who do not. Related title by Co-author Geert Molenbergh has sold more than 3500 copies world wide. Provides dual viewpoints: from scientists in the industry as well as regulatory authorities.
Author: Tomasz Burzykowski
Publisher: Springer Science & Business Media
ISBN: 0387270809
Category : Medical
Languages : en
Pages : 417
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Book Description
Covers the latest research on a sensitive and controversial topic in a professional and well researched manner. Provides practical outlook as well as model guidelines and software tools that should be of interest to people who use the software tools described and those who do not. Related title by Co-author Geert Molenbergh has sold more than 3500 copies world wide. Provides dual viewpoints: from scientists in the industry as well as regulatory authorities.
Author: Stephanie Green
Publisher: CRC Press
ISBN: 1439814481
Category : Mathematics
Languages : en
Pages : 266
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Book Description
The third edition of the bestselling Clinical Trials in Oncology provides a concise, nontechnical, and thoroughly up-to-date review of methods and issues related to cancer clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the pitfalls inherent in these processes. In addition, the book has been restructured to have separate chapters and expanded discussions on general clinical trials issues, and issues specific to Phases I, II, and III. New sections cover innovations in Phase I designs, randomized Phase II designs, and overcoming the challenges of array data. Although this book focuses on cancer trials, the same issues and concepts are important in any clinical setting. As always, the authors use clear, lucid prose and a multitude of real-world examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Armed with Clinical Trials in Oncology, Third Edition, clinicians and statisticians can avoid the many hazards that can jeopardize the success of a trial.
Author: Takeshi Emura
Publisher: Springer
ISBN: 9811335168
Category : Medical
Languages : en
Pages : 118
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Book Description
This book introduces readers to advanced statistical methods for analyzing survival data involving correlated endpoints. In particular, it describes statistical methods for applying Cox regression to two correlated endpoints by accounting for dependence between the endpoints with the aid of copulas. The practical advantages of employing copula-based models in medical research are explained on the basis of case studies. In addition, the book focuses on clustered survival data, especially data arising from meta-analysis and multicenter analysis. Consequently, the statistical approaches presented here employ a frailty term for heterogeneity modeling. This brings the joint frailty-copula model, which incorporates a frailty term and a copula, into a statistical model. The book also discusses advanced techniques for dealing with high-dimensional gene expressions and developing personalized dynamic prediction tools under the joint frailty-copula model. To help readers apply the statistical methods to real-world data, the book provides case studies using the authors’ original R software package (freely available in CRAN). The emphasis is on clinical survival data, involving time-to-tumor progression and overall survival, collected on cancer patients. Hence, the book offers an essential reference guide for medical statisticians and provides researchers with advanced, innovative statistical tools. The book also provides a concise introduction to basic multivariate survival models.
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309157277
Category : Medical
Languages : en
Pages : 335
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Book Description
Many people naturally assume that the claims made for foods and nutritional supplements have the same degree of scientific grounding as those for medication, but that is not always the case. The IOM recommends that the FDA adopt a consistent scientific framework for biomarker evaluation in order to achieve a rigorous and transparent process.
Author: David Machin
Publisher: John Wiley & Sons
ISBN: 0470870419
Category : Medical
Languages : en
Pages : 278
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Book Description
Well received in its first edition, Survival Analysis: A Practical Approach is completely revised to provide an accessible and practical guide to survival analysis techniques in diverse environments. Illustrated with many authentic examples, the book introduces basic statistical concepts and methods to construct survival curves, later developing them to encompass more specialised and complex models. During the years since the first edition there have been several new topics that have come to the fore and many new applications. Parallel developments in computer software programmes, used to implement these methodologies, are relied upon throughout the text to bring it up to date.
Author: Jianrong Wu
Publisher: CRC Press
ISBN: 0429892934
Category : Mathematics
Languages : en
Pages : 243
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Book Description
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.
Author: Ariel Alonso
Publisher: CRC Press
ISBN: 1482249375
Category : Mathematics
Languages : en
Pages : 396
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Book Description
An important factor that affects the duration, complexity and cost of a clinical trial is the endpoint used to study the treatment’s efficacy. When a true endpoint is difficult to use because of such factors as long follow-up times or prohibitive cost, it is sometimes possible to use a surrogate endpoint that can be measured in a more convenient or cost-effective way. This book focuses on the use of surrogate endpoint evaluation methods in practice, using SAS and R.
Author: Alison L. Pedley
Publisher:
ISBN:
Category :
Languages : en
Pages : 210
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Book Description
Abstract: A two-sample Z test of proportions is often performed in randomized clinical trials designed to assess the superiority of an experimental treatment to a control with respect to a long-term dichotomous primary endpoint, such as 1-year mortality. Due to the staggered entry of participants across the trial's recruitment period, only a portion of enrolled participants have complete follow- up data available at the time of an interim analysis. Typically, the interim evaluation of trial hypotheses is performed using the same test statistic as the test statistic planned for the final analysis. However, application of the Z test of proportions at interim analysis results in a potentially substantial reduction to the number of participants that are able to contribute to the analysis. In this dissertation, methodology for the use of the log-rank test, which incorporates data of all enrolled participants regardless of the amount of time each has been followed, in the interim analysis of trials with a dichotomous final primary endpoint is developed and evaluated. Although the overall power and type I error rates of the newly proposed methodology and the standard methodology are comparable under the assumption of proportional hazards and event rates less than 50%, the efficiency of using the log-rank test during the interim analysis was realized in terms of an increased probability of early trial termination for overwhelming efficacy resulting in potential for shorter trials and smaller sized trials. Methodology for using the log-rank test was also developed for and applied to trials incorporating an adaptation for sample size re-estimation at interim based on the conditional power of achieving a significant result by the end of the trial. In the context of sample size re-estimation, the use of the log-rank test not only increased the probability of declaring superiority of the experimental treatment over the control at the time of interim analysis, but increased the overall power. Regardless of whether or not sample size re-estimation is used, greater efficiency is attained when the log-rank test is performed at interim analysis as the differential between the percentages of subjects enrolled and with complete follow-up at interim analysis increases.
