Design and Analysis of Clinical Trials: Concepts and Methodologies, Second Edition
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SHEIN-CHUNG CHOW, PhD, is currently Vice President of Biostatistics and Clinical Data Management for Millennium Pharmaceuticals, Inc., in Cambridge, Massachusetts.

JEN-PEI LIU, PhD, is currently Professor of Statistics for the National Cheng kung University in Tainan, Taiwan, and an investigator for the National Health Research Institutes in Taipei, Taiwan. Both authors have extensive background experience in industry and academia, and, collectively, have published well over a dozen books in their respective fields of study.



Preface to the First Edition.

1. Introduction.

1.1 What are Clinical Trials?

1.2 History of Clinical Trials.

1.3 Regulatory Process and Requirements.

1.4 Investigational New Drug Application.

1.5 New Drug Application.

1.6 Clinical Development and Practice.

1.7 Aims and Structure of the Book.

2. Basic Statistical Concepts.

2.1 Introduction.

2.2 Uncertainty and Probability.

2.3 Bias and Variability.

2.4 Confounding and Interaction.

2.5 Descriptive and Inferential Statistics.

2.6 Hypothesis Testing and p-Values.

2.7 Clinical Significance and Clinical Equivalence.

2.8 Reproducibility and Generalizability.

3. Basic Design Considerations.

3.1 Introduction.

3.2 Goals of Clinical Trials.

3.3 Target Population and Patient Selection.

3.4 Selection of Controls.

3.5 Statistical Considerations.

3.6 Other Issues.

3.7 Discussion.

4. Randomization and Blinding.

4.1 Introduction.

4.2 Randomization Models.

4.3 Randomization Methods.

4.4 Implementation of Randomization.

4.5 Generalization of Controlled Randomized Trials.

4.6 Blinding.

4.7 Discussion.

5. Designs for Clinical Trials.

5.1 Introduction.

5.2 Parallel Group Designs.

5.3 Cluster Randomized Designs.

5.4 Crossover Designs.

5.5 Titration Designs.

5.6 Enrichment Designs.

5.7 Group Sequential Designs.

5.8 Placebo-Challenging Design.

5.9 Blinded Reader Designs.

5.10 Discussion.

6. Designs for Cancer Clinical Trials.

6.1 Introduction.

6.2 General Considerations for Phase I Cancer Clinical Trials.

6.3 Single-Stage Up-and-Down Phase I Designs.

6.4 Two-Stage Up-and-Down Phase I Designs.

6.5 Continual Reassessment Method Phase I Designs.

6.6 Optimal/Flexible Multiple-Stage Designs.

6.7 Randomized Phase II Designs.

6.8 Discussion.

7. Classification of Clinical Trials.

7.1 Introduction.

7.2 Multicenter Trial.

7.3 Superiority Trials.

7.4 Active Control and Equivalence/Noninferiority Trials.

7.5 Dose-Response Trials.

7.6 Combination Trials.

7.7 Bridging Studies.

7.8 Vaccine Clinical Trials.

7.9 Discussion.

8. Analysis of Continuous Data.

8.1 Introduction.

8.2 Estimation.

8.3 Test Statistics.

8.4 Analysis of Variance.

8.5 Analysis of Covariance.

8.6 Nonparametrics.

8.7 Repeated Measures.

8.8 Discussion.

9. Analysis of Categorical Data.

9.1 Introduction.

9.2 Statistical Inference for One Sample.

9.3 Inference of Independent Samples.

9.4 Ordered Categorical Data.

9.5 Combining Categorical Data.

9.6 Model-Based Methods.

9.7 Repeated Categorical Data.

9.8 Discussion.

10. Censored Data and Interim Analysis.

10.1 Introduction.

10.2 Estimation of the Survival Function.

10.3 Comparison between Survival Functions.

10.4 Cox’s Proportional Hazard Model.

10.5 Calendar Time and Information Time.

10.6 Group Sequential Methods.

10.7 Discussion.

11. Sample Size Determination.

11.1 Introduction.

11.2 Basic Concept.

11.3 Two Samples.

11.4 Multiple Samples.

11.5 Censored Data.

11.6 Dose-Response Studies.

11.7 Crossover Designs.

11.8 Equivalence and Noninferiority Trials.

11.9 Multiple-Stage Design in Cancer Trials.

11.10 Comparing Variabilities.

11.11 Discussion.

12. Issues in Efficacy Evaluation.

12.1 Introduction.

12.2 Baseline Comparison.

12.3 Intention-to-Treat Principle and Efficacy Analysis.

12.4 Adjustment for Covariates.

12.5 Multicenter Trials.

12.6 Multiplicity.

12.7 Data Monitoring.

12.8 Use of Genetic Information for Evaluation of Efficacy.

12.9 Sample Size Re-estimation.

12.10 Discussion.

13. Safety Assessment.

13.1 Introduction.

13.2 Extent of Exposure.

13.3 Coding of Adverse Events.

13.4 Analysis of Adverse Events.

13.5 Analysis of Laboratory Data.

13.6 Discussion.

14. Preparation and Implementation of a Clinical Protocol.

14.1 Introduction.

14.2 Structure and Components of a Protocol.

14.3 Points to Be Considered and Common Pitfalls during Development and Preparation of a Protocol.

14.4 Common Departures for Implementation of a Protocol.

14.5 Monitoring, Audit, and Inspection, 617

14.6 Quality Assessment of a Clinical Trial.

14.7 Discussion.

15. Clinical Data Management.

15.1 Introduction.

15.2 Regulatory Requirements.

15.3 Development of Case Report Forms.

15.4 Database Development.

15.5 Data Entry, Query, and Correction.

15.6 Data Validation and Quality.

15.7 Database Lock, Archive, and Transfer.

15.8 Discussion.





"It stands ready to satisfy the appetite of any pharmaceutical scientist with a respectable statistical appetite." (Journal of Clinical Research, June 2008)

"Biostatisticians, applied statisticians, and clinical scientists will find this book very valuable, and it is suitable for a graduate level clinical trial course." (Journal of Statistical Computation and Simulation, September 2005)

"…a comprehensive introduction…highly recommended…" (Statistical Methods in Medical Research, Vol. 14, 2005)

"…I will find this book a handy resource for future consulting with medical researchers." (Journal of the American Statistical Association, June 2005)

"…the authors have done a commendable job of blending large amounts of statistical and regulatory information in a way that is easy to comprehend and directly applicable…" (Clinical Chemistry, April 2005)

"…provides a comprehensive overview of the rather general area of clinical trials…an essential reference text." (Journal of Applied Statistics, Vol.32, No.3, April 2005)

"Numerous real-life examples and illustrations form clinical case studies are included…" (Zentralblatt Math, Vol.1050, 2005)

"…certainly comprehensive...should be a standard reference for both clinical scientists and biostatisticians…" (Technometrics, February 2005)