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.
Table of Contents
WHAT IS A RANDOMIZED CONTROLLED TRIAL?
Definition and Key Features
Historical Context and the Nature of RCTS
Structure and Justification of RCTs
What is meant by bias in RCTs?
Types of Bias
HOW MANY PATIENTS DO I NEED?
Criteria for Sample Size Calculations
Sample Size for a Normally Distributed Variable
Sample Size for a Binary Variable
General Remarks About Sample Size Calculations
METHODS OF ALLOCATION
Random Permuted Blocks
Biased Coin Designs and Urn Schemes
ASSESSMENT, BLINDING AND PLACEBOS
Double and Single Blindness
ANALYSIS OF RESULTS
Use of Confidence Intervals
Baselines: Uses and Abuses
Analysis of Covariance
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
Analyses Using Randomization Models
MONITORING ACCUMULATING DATA
Motivation and Problems with Repeated Analysis of Data
Sequential and Group-Sequential Methods
Other Approaches to Accumulating Data
Data Monitoring Committees
SUBGROUPS AND MULTIPLE OUTCOMES
The Role of Sub-groups in Randomized Clinical Trials
Methods for Comparing Sub-groups
Methods of Selecting Sub-groups
Correction of P-values
Some Alternative Methods for Multiple Outcomes
PROTOCOLS AND PROTOCOL DEVIATIONS
Protocols: Their Nature and Role
Analysis by Intention-to-Treat
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
Cluster Randomized Trials
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
SOLUTIONS TO EXERCISES
"…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