Introduction to Statistical Methods for

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 Trialspresents 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 anemerging 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.

List of figures	p. xi
List of tables	p. xv
Preface	p. xix
Author Attribution	p. xxiii
Introduction to Clinical Trials	p. 1
History and Background	p. 3
Ethics of Clinical Research	p. 5
Types of Research Design and Types of Trials	p. 9
The Need for Clinical Trials	p. 15
The Randomization Principle	p. 18
Timing of a Clinical Trial	p. 18
Trial Organization	p. 20
Protocol and Manual of Operations	p. 22
Regulatory Issues	p. 22
Overview of the Book	p. 26
Defining the Question	p. 29
Statistical Framework	p. 31
Elements of Study Question	p. 40
Outcome or Response Measures	p. 44
The Surrogate Outcome	p. 56
Composite Outcomes	p. 64
Summary	p. 73
Problems	p. 73
Study Design	p. 75
Early Phase Trials	p. 76
Phase III/IV Trials	p. 85
Non-inferiority Designs	p. 101
Screening, Prevention, and Therapeutic Designs	p. 106
Adaptive Designs	p. 109
Conclusions	p. 112
Problems	p. 112
Sample Size	p. 115
Sample Size versus Information	p. 116
A General Setup for Frequentist Designs	p. 118
Loss to Follow-up and Non-adherence	p. 122
Survival Data	p. 124
Clustered Data	p. 134
Tests for Interaction	p. 136
Equivalence/Non-inferiority Trials	p. 137
Other Considerations	p. 138
Problems	p. 139
Randomization	p. 141
The Role of Randomization	p. 141
Fixed Randomization Procedures	p. 148
Treatment- and Response-Adaptive Randomization Procedures	p. 155
Covariate-Adaptive Randomization Procedures	p. 161
Summary and Recommendations	p. 165
Problems	p. 168
Data Collection and Quality Control	p. 171
Planning for Collection of Clinical Trial Data	p. 172
Categories of Clinical Data	p. 185
Data Quality Control	p. 194
Conclusions	p. 199
Survival Analysis	p. 201
Background	p. 201
Estimation of Survival Distributions	p. 203
Comparison of Survival Distributions	p. 213
Regression Models	p. 219
Composite Outcomes	p. 227
Summary	p. 228
Problems	p. 229
Longitudinal Data	p. 231
A Clinical Longitudinal Data Example	p. 232
The Subject-specific Model	p. 234
Two-stage Estimation	p. 237
The Random-effects, Subject-specific Model	p. 242
The Population-average (Marginal) Model	p. 246
Restricted Maximum Likelihood Estimation (REML)	p. 252
Standard Errors	p. 253
Testing	p. 255
Additional Levels of Clustering	p. 258
Generalized Estimating Equations for Non-normal Data	p. 260
Missing Data	p. 263
Summary	p. 264
Quality of Life	p. 267
Defining QoL	p. 268
Types of QoL Assessments	p. 268
Selecting a QoL Instrument	p. 271
Developing a QoL Instrument	p. 273
Quality of Life Data	p. 273
Analysis of QoL Data	p. 275
Summary	p. 286
Data Monitoring and Interim Analysis	p. 289
Data and Safety Monitoring	p. 290
Examples	p. 292
The Repeated Testing Problem	p. 293
Group Sequential Tests	p. 299
Triangular Test	p. 311
Curtailment Procedures	p. 315
Inference Following Sequential Tests	p. 322
Discussion	p. 329
Problems	p. 336
Selected Issues in the Analysis	p. 339
Bias in the Analysis of Clinical Trial Data	p. 339
Choice of Analysis Population	p. 340
Missing Data	p. 354
Subgroup Analyses	p. 364
Multiple Testing Procedures	p. 370
Summary	p. 375
Problems	p. 376
Closeout and Reporting	p. 377
Closing Out a Trial	p. 377
Reporting Trial Results	p. 378
Problems	p. 392
Delta Method, Maximum Likelihood Theory, and Information	p. 393
Delta Method	p. 393
Asymptotic Theory for Likelihood Based Inference	p. 393
Hypothesis Testing	p. 395
Computing the MLE	p. 399
Information	p. 400
Brownian Motion	p. 403
References	p. 405
Index	p. 427
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Introduction to Statistical Methods for Clinical Trials

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