Description
Taylor & Francis Ltd Introduction To Statistical Methods For Clinical Trials 2007 Edition by Thomas D. Cook, David L. Demets
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. 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