2nd Edition

Introduction to Randomized Controlled Clinical Trials

By John N.S. Matthews Copyright 2006
    302 Pages 50 B/W Illustrations
    by Chapman & Hall

    302 Pages
    by Chapman & Hall

    Evidence from randomized controlled clinical trials is widely accepted as the only sound basis for assessing the efficacy of new medical treatments. Statistical methods play a key role in all stages of these trials, including their justification, design, and analysis. This second edition of Introduction to Randomized Controlled Clinical Trials provides a concise presentation of the principles applied in this area. It details the concepts behind randomization and methods for designing and analyzing trials and also includes information on meta-analysis and specialized designs, such as cross-over trials, cluster-randomized designs, and equivalence studies.

    This latest edition features new and revised references, examples, exercises, and a new chapter dedicated to binary outcomes and survival analysis. It also presents numerous examples taken from the medical literature, contains exercises at the end of each chapter, and offers solutions in an appendix. The author uses Minitab and R software throughout the text for implementing the methods that are presented.

    Comprehensive and accessible, Introduction to Randomized Controlled Clinical Trials is well-suited for those familiar with elementary statistical ideas and methods who want to further their knowledge of the subject.

    WHAT IS A RANDOMIZED CONTROLLED TRIAL?
    Definition and Key Features
    Historical Context and the Nature of RCTS
    Structure and Justification of RCTs
    Exercises

    BIAS
    What is meant by bias in RCTs?
    Types of Bias
    Exercises

    HOW MANY PATIENTS DO I NEED?
    Criteria for Sample Size Calculations
    Hypothesis Tests
    Sample Size for a Normally Distributed Variable
    Sample Size for a Binary Variable
    General Remarks About Sample Size Calculations
    Exercises

    METHODS OF ALLOCATION
    Simple Randomization
    Random Permuted Blocks
    Biased Coin Designs and Urn Schemes
    Unequal Randomization
    Stratification
    Minimization
    Exercises

    ASSESSMENT, BLINDING AND PLACEBOS
    Double and Single Blindness
    Placebos
    Practical Considerations
    Exercises

    ANALYSIS OF RESULTS
    Example
    Use of Confidence Intervals
    Baselines: Uses and Abuses
    Analysis of Covariance
    Exercises

    FURTHER ANALYSIS: BINARY AND SURVIVAL DATA
    Binary Data: An Example and a Statistical Model
    Point Estimates and Hypothesis Tests
    Interval Estimates for the Binary Case
    Adjusting Binary Outcomes for Baseline Observations
    Survival Analysis
    Analyses Using Randomization Models
    Exercises

    MONITORING ACCUMULATING DATA
    Motivation and Problems with Repeated Analysis of Data
    Sequential and Group-Sequential Methods
    Other Approaches to Accumulating Data
    Data Monitoring Committees
    Exercises
    SUBGROUPS AND MULTIPLE OUTCOMES
    The Role of Sub-groups in Randomized Clinical Trials
    Methods for Comparing Sub-groups
    Methods of Selecting Sub-groups
    Qualitative Interactions
    Multiple outcomes
    Correction of P-values
    Some Alternative Methods for Multiple Outcomes
    Exercises

    PROTOCOLS AND PROTOCOL DEVIATIONS
    Protocols: Their Nature and Role
    Protocol Deviation
    Analysis by Intention-to-Treat
    Exercises

    SOME SPECIAL DESIGNS: CROSSOVERS, EQUIVALENCE AND CLUSTERS
    Crossover Trials and Parallel Group Trials
    The AB/BA Design
    Analysis of AB/BA Design for Continuous Outcomes
    The Issue of Carryover
    Equivalence Trials
    Cluster Randomized Trials
    Exercises

    META-ANALYSES OF CLINICAL TRIALS
    What Are Meta-Analyses and Why Are They Needed?
    Some Methodology for Meta-Analysis
    Some Graphical Methods for Meta-Analysis
    Some General Issues in Meta-Analysis
    Exercises

    FURTHER READING
    SOLUTIONS TO EXERCISES
    REFERENCES

    "…this book is very well presented and … is extremely pleasant and enjoyable to read. Both the statistical concepts and medical examples are very well explained. I highly recommend this book as a course text and as an excellent reference book for anyone interested in clinical trials. A copy of it should certainly appear in every university library."
    Journal of Applied Statistics, 2007

    "…a very welcome revision. The author has drawn upon his experiences to provide a valuable account of the important statistical underpinnings of the randomized clinical trial. … written primarily for students of statistics … highly desirable … ideal for its intended audience."
    —Susan Todd, The University of Reading, UK

    "…The second edition builds upon the first by adding a chapter on binary and survival data and updating the chapter on balancing treatment allocations. Whether you might need to introduce a novice to the unique principles and pitfalls of clinical trials or remind an experienced statistician of their importance, this book would serve your purpose admirably. Moreover, as an experienced clinical trialist, I found it to be an excellent reminder of the statistical principles and concepts that underlie the day-to-day rules of our profession. … Throughout, the author discusses principles, concepts and applications with a clarity that will be truly appreciated by those trained in mathematics. Each chapter focuses on a key challenge in the analysis of clinical trials and its associated statistical implications. … Overall, the choice of chapter topics is comprehensive and well chosen. … This text is definitely a handy reference-certainly worthwhile for a statistically conversant audience who are lacking in clinical trials experience. Such an audience will find this book educational and the author's concise style, an easy read. I would definitely recommend it for the bookshelf of anyone working in clinical trials."
    —Karen Kesler, Journal of Biopharmaceutical Statistics, Issue 5, 2007