Introduction to Statistical Methods for Clinical Trials

ISBN-13: 9781584880271 / Angielski / Twarda / 2007 / 464 str.

Chappell Chappell; Richard Chappell; Kyungmann Kim

Opis

Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials."

Spis treści

PREFACE
Introduction to Clinical Trials
History and Background
Ethics of Clinical Research
Types of Research Design and Types of Trials
The Need for Clinical Trials
The Randomization Principle
Timing of a Clinical Trial
Trial Organization
Protocol and Manual of Operations
Regulatory Issues
Overview of the Book
Defining the Question
Statistical Framework
Elements of Study Question
Outcome or Response Measures
The Surrogate Outcome
Composite Outcomes
Summary
Problems
Study Design
Early Phase Trials
Phase III/IV Trials
Non-Inferiority Designs
Screening, Prevention, and Therapeutic Designs
Adaptive Designs
Conclusions
Problems
Sample Size
Sample Size versus Information
A General Setup for Frequentist Designs
Loss to Follow-up and Non-Adherence
Survival Data
Clustered Data
Tests for Interaction
Equivalence/Non-Inferiority Trials
Other Considerations
Problems
Randomization
The Role of Randomization
Fixed Randomization Procedures
Treatment- and Response-Adaptive Randomization Procedures
Covariate-Adaptive Randomization Procedures
Summary and Recommendations
Problems
Data Collection and Quality Control
Planning for Collection of Clinical Trial Data
Categories of Clinical Data
Data Quality Control
Conclusions
Survival Analysis
Background
Estimation of Survival Distributions
Comparison of Survival Distributions
Regression Models
Composite Outcomes
Summary
Problems
Longitudinal Data
A Clinical Longitudinal Data Example
The Subject-Specific Model
Two-Stage Estimation
The Random-Effects, Subject-Specific Model
The Population-Average (Marginal) Model
Restricted Maximum Likelihood Estimation (REML)
Standard Errors
Testing
Additional Levels of Clustering
Generalized Estimating Equations for Non-Normal Data
Missing Data
Summary
Quality of Life
Defining QoL
Types of QoL Assessments
Selecting a QoL Instrument
Developing a QoL Instrument
Quality of Life Data
Analysis of QoL Data
Summary
Data Monitoring and Interim Analysis
Data and Safety Monitoring
Examples
The Repeated Testing Problem
Group Sequential Tests
Triangular Test
Curtailment Procedures
Inference Following Sequential Tests
Discussion
Problems
Selected Issues in the Analysis
Bias in the Analysis of Clinical Trial Data
Choice of Analysis Population
Missing Data
Subgroup Analyses
Multiple Testing Procedures
Summary
Problems
Closeout and Reporting
Closing out a Trial
Reporting Trial Results
Problems
Appendix: Delta Method, Maximum Likelihood Theory, and Information
Delta Method
Asymptotic Theory for Likelihood-Based Inference
Hypothesis Testing
Computing the MLE
Information
Brownian Motion
REFERENCES
INDEX

O autorze

Thomas D. Cook, David L. DeMets