Springer Series in Pharmaceutical Statistics - Böcker

This book addresses the most important aspects of how to plan and evaluate clinical trials with a composite primary endpoint to guarantee a clinically meaningful and valid interpretation of the results. Composite endpoints are often used as primary efficacy variables for clinical trials, particularly in the fields of oncology and cardiology. These endpoints combine several variables of interest within a single composite measure, and as a result, all variables that are of major clinical relevance can be considered in the primary analysis without the need to adjust for multiplicity. Moreover, composite endpoints are intended to increase the size of the expected effects thus making clinical trials more powerful. The book offers practical advice for statisticians and medical experts involved in the planning and analysis of clinical trials. For readers who are mainly interested in the application of the methods, all the approaches are illustrated with real-world clinical trial examples, and the software codes required for fast and easy implementation are provided. The book also discusses all the methods in the context of relevant guidelines related to the topic. To benefit most from the book, readers should be familiar with the principles of clinical trials and basic statistical methods.

This book offers an overview of the statistical methods used in clinical and observational vaccine studies. Pursuing a practical rather than theoretical approach, it presents a range of real-world examples with SAS codes, making the application of the methods straightforward. This revised edition has been significantly expanded to reflect the current interest in this area. It opens with two introductory chapters on the immunology of vaccines to provide readers with the necessary background knowledge. It then continues with an in-depth exploration of the analysis of immunogenicity data. Discussed are, amongst others, maximum likelihood estimation for censored antibody titers, ANCOVA for antibody values, analysis of data of equivalence, and non-inferiority immunogenicity studies. Other topics covered include fitting protection curves to data from vaccine efficacy studies, and the analysis of vaccine safety data.In addition, the book features four new chapters on vaccine field studies: an introductory one, one on randomized vaccine efficacy studies, one on observational vaccine effectiveness studies, and one on the meta-analysis of vaccine efficacy studies. The book offers useful insights for statisticians and epidemiologists working in the pharmaceutical industry or at vaccines institutes, as well as graduate students interested in pharmaceutical statistics.

This book offers an overview of the statistical methods used in clinical and observational vaccine studies. Pursuing a practical rather than theoretical approach, it presents a range of real-world examples with SAS codes, making the application of the methods straightforward. This revised edition has been significantly expanded to reflect the current interest in this area. It opens with two introductory chapters on the immunology of vaccines to provide readers with the necessary background knowledge. It then continues with an in-depth exploration of the analysis of immunogenicity data. Discussed are, amongst others, maximum likelihood estimation for censored antibody titers, ANCOVA for antibody values, analysis of data of equivalence, and non-inferiority immunogenicity studies. Other topics covered include fitting protection curves to data from vaccine efficacy studies, and the analysis of vaccine safety data.In addition, the book features four new chapters on vaccine field studies: an introductory one, one on randomized vaccine efficacy studies, one on observational vaccine effectiveness studies, and one on the meta-analysis of vaccine efficacy studies. The book offers useful insights for statisticians and epidemiologists working in the pharmaceutical industry or at vaccines institutes, as well as graduate students interested in pharmaceutical statistics.

This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious.

This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious.

This book provides an extensive overview of the principles and methods of sample size calculation and recalculation in clinical trials. Blinded sample size recalculation procedures for internal pilot study designs are considered, as well as methods for sample size reassessment in adaptive designs that use unblinded data from interim analyses.

This book provides an extensive overview of the principles and methods of sample size calculation and recalculation in clinical trials. Blinded sample size recalculation procedures for internal pilot study designs are considered, as well as methods for sample size reassessment in adaptive designs that use unblinded data from interim analyses.

This book focuses on important decision points and evidence needed for making decisions at these points during the development of a new drug.

This book focuses on important decision points and evidence needed for making decisions at these points during the development of a new drug.

This book provides an up-to-date review of the general principles and techniques of confirmatory adaptive designs, a generalization of group sequential designs. With these designs, interim analyses are performed in order to stop a trial prematurely under control of the Type I error rate. In adaptive designs, it is also permissible to perform a data-driven change of relevant aspects of the study design at interim stages. This includes, for example, a sample-size reassessment, a treatment-arm selection, or a selection of a pre-specified sub-population.First introduced in the 1990s, this popular adaptive methodology has become the focus of intense discussion and is still a rapidly growing field of statistical research. The book describes adaptive design methodology at an elementary level, while also considering design and planning issues. It also looks at methods for analyzing an adaptively planned trial, such as estimation methods and methods for determining an overall p-value. Part I provides the group sequential preliminaries required to understand and apply the adaptive design methodology supplied in Parts II and III. Many examples are included that illustrate the practical applications of the techniques. An overview of recent developments is given and, new to this edition, detailed descriptions of the R commands used for the calculations are provided. The R package rpact, which is available on CRAN, allows for the recalculation of most tables and results presented in the monograph. The required knowledge of R has been kept to a minimum, and an online Shiny app has been made available for rpact. Primarily written for applied statisticians from academia and industry who are interested in confirmatory adaptive designs, the text is also suitable for an advanced statistical course for applied statisticians or clinicians with a sound statistical background.

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This book addresses the most important aspects of how to plan and evaluate clinical trials with a composite primary endpoint to guarantee a clinically meaningful and valid interpretation of the results. Composite endpoints are often used as primary efficacy variables for clinical trials, particularly in the fields of oncology and cardiology. These endpoints combine several variables of interest within a single composite measure, and as a result, all variables that are of major clinical relevance can be considered in the primary analysis without the need to adjust for multiplicity. Moreover, composite endpoints are intended to increase the size of the expected effects thus making clinical trials more powerful. The book offers practical advice for statisticians and medical experts involved in the planning and analysis of clinical trials. For readers who are mainly interested in the application of the methods, all the approaches are illustrated with real-world clinical trial examples, and the software codes required for fast and easy implementation are provided. The book also discusses all the methods in the context of relevant guidelines related to the topic. To benefit most from the book, readers should be familiar with the principles of clinical trials and basic statistical methods.

This book provides an up-to-date review of the general principles of and techniques for confirmatory adaptive designs.