Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs

Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs

by N. Balakrishnan
Released February 2014
Publisher(s): Wiley
ISBN: 9781118304730

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Book description

A complete guide to the key statistical concepts essential for the design and construction of clinical trials

As the newest major resource in the field of medical research, Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs presents a timely and authoritative reviewof the central statistical concepts used to build clinical trials that obtain the best results. The referenceunveils modern approaches vital to understanding, creating, and evaluating data obtained throughoutthe various stages of clinical trial design and analysis.

Accessible and comprehensive, the first volume in a two-part set includes newly-written articles as well as established literature from the Wiley Encyclopedia of Clinical Trials. Illustrating a variety of statistical concepts and principles such as longitudinal data, missing data, covariates, biased-coin randomization, repeated measurements, and simple randomization, the book also provides in-depth coverage of the various trial designs found within phase I-IV trials. Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs also features:

  • Detailed chapters on the type of trial designs, such as adaptive, crossover, group-randomized, multicenter, non-inferiority, non-randomized, open-labeled, preference, prevention, and superiority trials

  • Over 100 contributions from leading academics, researchers, and practitioners

  • An exploration of ongoing, cutting-edge clinical trials on early cancer and heart disease, mother-to-child human immunodeficiency virus transmission trials, and the AIDS Clinical Trials Group

    • Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs is an excellent reference for researchers, practitioners, and students in the fields of clinicaltrials, pharmaceutics, biostatistics, medical research design, biology, biomedicine, epidemiology,and public health.

    Table of contents

    1. Cover
    2. Half Title page
    3. Title page
    4. Copyright page
    5. Contributors
    6. Preface
    7. Chapter 1: Absolute Risk Reduction
      1. 1.1 Introduction
      2. 1.2 Preliminary Issues
      3. 1.3 Point and Interval Estimates for a Single Proportion
      4. 1.4 An Unpaired Difference of Proportions
      5. 1.5 Number Needed to Treat
      6. 1.6 A Paired Difference of Proportions
      7. References
      8. Further Reading
    8. Chapter 2: Accelerated Approval
      1. 2.1 Introduction
      2. 2.2 Accelerated Development Versus Expanded Access in the U.S.A.
      3. 2.3 Sorting the Terminology—Which FDA Initiatives Do What?
      4. 2.4 Accelerated Approval Regulations: 21 C.F.R. 314.500, 314.520, 601.40
      5. 2.5 Stages of Drug Development and FDA Initiatives
      6. 2.6 Accelerated Approval Regulations: 21 CFR 314.500, 314.520, 601.40
      7. 2.7 Accelerated Approval with Surrogate Endpoints
      8. 2.8 Accelerated Approval with Restricted Distribution
      9. 2.9 Phase IV Studies/Post Marketing Surveillance
      10. 2.10 Benefit Analysis for Accelerated Approvals Versus Other Illnesses
      11. 2.11 Problems, Solutions, and Economic Incentives
      12. 2.12 Future Directions
      13. References
      14. Further Reading
    9. Chapter 3: AIDS Clinical Trials Group (ACTG)
      1. 3.1 Introduction
      2. 3.2 A Brief Primer on HIV/AIDS
      3. 3.3 ACTG Overview
      4. 3.4 ACTG Scientific Activities
      5. 3.5 Development of Potent Antiretroviral Therapy (ART)
      6. 3.6 Expert Systems and Infrastructure
      7. References
    10. Chapter 4: Algorithm-Based Designs
      1. 4.1 Phase I Dose-Finding Studies
      2. 4.2 Accelerated Designs
      3. 4.3 Model-Based Approach in the Estimation of MTD
      4. 4.4 Exploring Algorithm-Based Designs with Prespecified Targeted Toxicity Levels
      5. References
    11. Chapter 5: Alpha-Spending Function
      1. 5.1 Introduction
      2. 5.2 Alpha Spending Function Motivation
      3. 5.3 The Alpha Spending Function
      4. 5.4 Application of the Alpha Spending Function
      5. 5.5 Confidence Intervals and Estimation
      6. 5.6 Trial Design
      7. 5.7 Conclusions
      8. References
      9. Further Reading
    12. Chapter 6: Application of New Designs in Phase I Trials
      1. 6.1 Introduction
      2. 6.2 Objectives of a Phase I Trial
      3. 6.3 Standard Designs and Their Shortcomings
      4. 6.4 Some Novel Designs
      5. 6.5 Discussion
      6. References
      7. Further Reading
    13. Chapter 7: ASCOT Trial
      1. 7.1 Introduction
      2. 7.2 Objectives
      3. 7.3 Study Design
      4. 7.4 Results
      5. 7.5 Discussion and Conclusions
      6. References
    14. Chapter 8: Benefit/Risk Assessment in Prevention Trials
      1. 8.1 Introduction
      2. 8.2 Types of B/RAs Performed in Prevention Trials
      3. 8.3 Alternative Structures of the Benefit/Risk Algorithm used in Prevention Trials
      4. 8.4 Methodological and Practical Issues with B/RA in Prevention Trials
      5. References
    15. Chapter 9: Biased Coin Randomization
      1. 9.1 Randomization Strategies for Overall Treatment Balance
      2. 9.2 The Biased Coin Randomization Procedure
      3. 9.3 Properties
      4. 9.4 Extensions to the Biased Coin Randomization
      5. 9.5 Adaptive Biased Coin Randomization
      6. 9.6 Urn Models
      7. 9.7 Treatment Balance for Covariates
      8. 9.8 Application of Biased Coin Designs to Response-Adaptive Randomization
      9. References
    16. Chapter 10: Biological Assay, Overview
      1. 10.1 Introduction
      2. 10.2 Direct Dilution Assays
      3. 10.3 Indirect Dilution Assays
      4. 10.4 Indirect Quantal Assays
      5. 10.5 Stochastic Approximation in Bioassay
      6. 10.6 Radioimmunoassay
      7. 10.7 Dosimetry and Bioassay
      8. 10.8 Semiparametrics in Bioassays
      9. 10.9 Nonparametrics in Bioassays
      10. 10.10 Bioavailability and Bioequivalence Models
      11. 10.11 Pharmacogenomics in Modern Bioassays
      12. 10.12 Complexities in Bioassay Modeling and Analysis
      13. References
      14. Further Reading
    17. Chapter 11: Block Randomization
      1. 11.1 Introduction
      2. 11.2 Simple Randomization
      3. 11.3 Restricted Randomization Through the Use of Blocks
      4. 11.4 Schemes Using a Single Block for the Whole Trial
      5. 11.5 Use of Unequal and Variable Block Sizes
      6. 11.6 Inference and Analysis Following Blocked Randomization
      7. 11.7 Miscellaneous Topics Related to Blocked Randomization
      8. References
      9. Further Reading
    18. Chapter 12: Censored Data
      1. 12.1 Introduction
      2. 12.2 Independent Censoring
      3. 12.3 Likelihoods: Noninformative Censoring
      4. 12.4 Other Kinds of Incomplete Observation
      5. References
    19. Chapter 13: Clinical Data Coordination
      1. 13.1 Introduction
      2. 13.2 Study Initiation
      3. 13.3 Study Conduct
      4. 13.4 Study Closure
      5. 13.5 Summary
      6. References
    20. Chapter 14: Clinical Data Management
      1. 14.1 Introduction
      2. 14.2 How Has Clinical Data Management Evolved?
      3. 14.3 Electronic Data Capture
      4. 14.4 Regulatory Involvement with Clinical Data Management
      5. 14.5 Professional Societies
      6. 14.6 Look to the Future
      7. 14.7 Conclusion
      8. References
    21. Chapter 15: Clinical Significance
      1. 15.1 Introduction
      2. 15.2 Historical Background
      3. 15.3 Article Outline
      4. 15.4 Design and Methodology
      5. 15.5 Examples
      6. 15.6 Recent Developments
      7. 15.7 Concluding Remarks
      8. References
    22. Chapter 16: Clinical Trial Misconduct
      1. 16.1 The Scope of this Article
      2. 16.2 Why Does Research Misconduct Matter?
      3. 16.3 Early Cases
      4. 16.4 Definition
      5. 16.5 Intent
      6. 16.6 What Scientific Misconduct was Not
      7. 16.7 The Process
      8. 16.8 The Past Decade
      9. 16.9 Lessons from the U.S. Experience
      10. 16.10 Outside the United States
      11. 16.11 Scientific Misconduct During Clinical Trials
      12. 16.12 Audit
      13. 16.13 Causes
      14. 16.14 Prevalence
      15. 16.15 Peer Review and Misconduct
      16. 16.16 Retractions
      17. 16.17 Prevention
      18. References
    23. Chapter 17: Clinical Trials, Early Cancer and Heart Disease
      1. 17.1 Introduction
      2. 17.2 Developments in Clinical Trials at the National Cancer Institute (NCI)
      3. 17.3 Developments in Clinical Trials at the National Heart, Lung, and Blood Institute (NHLBI)
      4. References
    24. Chapter 18: Cluster Randomization
      1. 18.1 Introduction
      2. 18.2 Examples of Cluster Randomization Trials
      3. 18.3 Principles of Experimental Design
      4. 18.4 Experimental and Quasi-Experimental Designs
      5. 18.5 The Effect of Failing to Replicate
      6. 18.6 Sample Size Estimation
      7. 18.7 Cluster Level Analyses
      8. 18.8 Individual Level Analyses
      9. 18.9 Incorporating Repeated Assessments
      10. 18.10 Study Reporting
      11. 18.11 Meta-Analysis
      12. References
    25. Chapter 19: Coherence in Phase I Clinical Trials
      1. 19.1 Introduction
      2. 19.2 Coherence: Definitions and Organization
      3. 19.3 Coherent Designs
      4. 19.4 Compatible Initial Design
      5. 19.5 Group Coherence
      6. 19.6 Real-Time Coherence
      7. 19.7 Discussion
      8. References
    26. Chapter 20: Compliance and Survival Analysis
      1. 20.1 Compliance: Cause and Effect
      2. 20.2 All-or-Nothing Compliance
      3. 20.3 More General Exposure Patterns
      4. 20.4 Other Structural Modeling Options
      5. References
    27. Chapter 21: Composite Endpoints in Clinical Trials
      1. 21.1 Introduction
      2. 21.2 The Rationale for Composite Endpoints
      3. 21.3 Formulation of Composite Endpoints
      4. 21.4 Examples
      5. 21.5 Interpreting Composite Endpoints
      6. 21.6 Conclusions
      7. References
    28. Chapter 22: Confounding
      1. 22.1 Introduction
      2. 22.2 Confounding as a Bias in Effect Estimation
      3. 22.3 Confounding and Noncollapsibility
      4. 22.4 Confounding in Experimental Design
      5. References
    29. Chapter 23: Control Groups
      1. 23.1 Introduction
      2. 23.2 History
      3. 23.3 Ethics
      4. 23.4 Types of Control Groups: Historical Controls
      5. 23.5 Types of Control Groups: Randomized Controls
      6. 23.6 Conclusion
      7. References
    30. Chapter 24: Coronary Drug Project
      1. 24.1 Introduction
      2. 24.2 Objectives
      3. 24.3 Study Design and Methods
      4. 24.4 Results
      5. 24.5 Conclusions and Lessons Learned
      6. References
      7. Further Reading
    31. Chapter 25: Covariates
      1. 25.1 Universal Character of Covariates
      2. 25.2 Use of Covariates in Clinical Trials
      3. 25.3 Continuous Covariates: Categorization or Functional Form?
      4. 25.4 Reporting and Summary Assessment of Prognostic Markers
      5. References
    32. Chapter 26: Crossover Design
      1. 26.1 Introduction
      2. 26.2 The Two-Period, Two-Treatment Design
      3. 26.3 Higher Order Designs
      4. 26.4 Model-Based Analyses
      5. References
    33. Chapter 27: Crossover Trials
      1. 27.1 Introduction
      2. 27.2 2 × 2 Crossover Trial
      3. 27.3 Higher-Order Designs for Two Treatments
      4. 27.4 Designs for Three or More Treatments
      5. 27.5 Analysis of Continuous Data
      6. 27.6 Analysis of Discrete Data
      7. 27.7 Concluding Remarks
      8. References
    34. Chapter 28: Diagnostic Studies
      1. 28.1 Introduction
      2. 28.2 Diagnostic Studies
      3. 28.3 Reliability
      4. 28.4 Validity
      5. References
      6. Further Reading
    35. Chapter 29: DNA Bank
      1. 29.1 Definition and Objectives of DNA Biobanks
      2. 29.2 Types of DNA Biobanks
      3. 29.3 Types of Samples Stored
      4. 29.4 Quality Assurance and Quality Control in DNA Biobanks
      5. 29.5 Ethical Issues
      6. 29.6 Current Biobank Initiatives
      7. 29.7 Conclusions
      8. References
    36. Chapter 30: Up-and-Down and Escalation Designs
      1. 30.1 Introduction
      2. 30.2 Up-and-Down Designs
      3. 30.3 Escalation Designs
      4. 30.4 Comparing U&D, Escalation and Model-Based Designs
      5. References
      6. Further Reading
    37. Chapter 31: Dose Ranging Crossover Designs
      1. 31.1 Introduction
      2. 31.2 Titration Designs and Extension Studies
      3. 31.3 Randomized Designs
      4. 31.4 Discussion and Conclusion
      5. References
      6. Further Reading
    38. Chapter 32: Flexible Designs
      1. 32.1 Introduction
      2. 32.2 The General Framework
      3. 32.3 Conditional Power and Sample Size Reassessment
      4. 32.4 Extending the Flexibility to the Choice of the Number of Stages
      5. 32.5 Selection of the Test Statistics
      6. 32.6 More General Adaptations and Multiple Hypotheses Testing
      7. 32.7 An Example
      8. 32.8 Conclusion
      9. References
    39. Chapter 33: Gene Therapy
      1. 33.1 Introduction
      2. 33.2 Requirements for Successful Therapeutic Intervention
      3. 33.3 Pre-Clinical Research
      4. 33.4 Translational Challenges of Gene Therapy Trials
      5. 33.6 Lessons Learned
      6. 33.7 The Way Forward
      7. References
      8. Further Reading
    40. Chapter 34: Global Assessment Variables
      1. 34.1 Introduction
      2. 34.2 Scientific Questions for Multiple Outcomes
      3. 34.3 General Comments on the GST
      4. 34.4 Recoding Outcome Measures
      5. 34.5 Types of Global Statistical Tests (GSTs)
      6. 34.6 Other Considerations
      7. 34.7 Other Methods
      8. 34.8 Examples of the Application of GST
      9. 34.9 Conclusions
      10. References
    41. Chapter 35: Good Clinical Practice (GCP)
      1. 35.1 Introduction
      2. 35.2 Human Rights and Protections
      3. 35.3 Informed Consent
      4. 35.4 Investigational Protocol
      5. 35.5 Investigator’s Brochure
      6. 35.6 Investigational New Drug Application
      7. 35.7 Production of the Investigational Drug
      8. 35.8 Clinical Testing
      9. 35.9 Sponsors
      10. 35.10 Contract Research Organization
      11. 35.11 Monitors
      12. 35.12 Investigators
      13. 35.13 Documentation
      14. 35.14 Clinical Holds
      15. 35.15 Inspections/Audits
      16. References
      17. Further Reading
    42. Chapter 36: Group-Randomized Trials
      1. 36.1 Introduction
      2. 36.2 Group-Randomized Trials in Context
      3. 36.3 The Development of Group- Randomized Trials in Public Health
      4. 36.4 The Range of GRTs in Public Health
      5. 36.5 Current Design and Analytic Practices in GRTs in Public Health
      6. 36.6 The Future of Group-Randomized Trials
      7. 36.7 Planning a New Group-Randomized Trial
      8. References
    43. Chapter 37: Group Sequential Designs
      1. 37.1 Introduction
      2. 37.2 Classical Designs
      3. 37.3 The α-Spending Function Approach
      4. 37.4 Point Estimates and Confidence Intervals
      5. 37.5 Supplements
      6. References
    44. Chapter 38: Hazard Ratio
      1. 38.1 Introduction
      2. 38.2 Definitions
      3. 38.3 Illustration of Hazard Rate, Hazard Ratio and Risk Ratio
      4. 38.4 Example on the Use and Usefulness of Hazard Ratios
      5. 38.5 Ad-hoc Estimator of the Hazard Ratio
      6. 38.6 Confidence Interval of the Ad-hoc Estimator
      7. 38.7 Ad-hoc Estimator Stratified for the Covariate Renal Function
      8. 38.8 Properties of the Ad-hoc Estimator
      9. 38.9 Class of Generalized Rank Estimators of the Hazard Ratio
      10. 38.10 Estimation of the Hazard Ratio with Cox’s Proportional Hazards Model
      11. 38.11 Discussion
      12. Further Reading
      13. References
    45. Chapter 39: Large Simple Trials
      1. 39.1 Large, Simple Trials
      2. 39.2 Small but Clinically Important Objective
      3. 39.3 Eligibility
      4. 39.4 Randomized Assignment
      5. 39.5 Outcome Measures
      6. 39.6 Conclusions
      7. References
      8. Further Reading – Selected Examples of Large, Simple Trials
    46. Chapter 40: Longitudinal Data
      1. 40.1 Definition
      2. 40.2 Longitudinal Data from Clinical Trials
      3. 40.3 Advantages
      4. 40.4 Challenges
      5. 40.5 Analysis of Longitudinal Data
      6. References
      7. Further Reading
    47. Chapter 41: Maximum Duration and Information Trials
      1. 41.1 Introduction
      2. 41.2 Two Paradigms: Duration versus Information
      3. 41.3 Sequential Studies: Maximum Duration versus Information Trials
      4. 41.4 An Example of a Maximum Information Trial
      5. References
    48. Chapter 42: Missing Data
      1. 42.1 Introduction
      2. 42.2 Methods in Common Use
      3. 42.3 An Alternative Approach to Incomplete Data
      4. 42.4 Illustration: Orthodontic Growth Data
      5. 42.5 Inverse Probability Weighting
      6. 42.6 Multiple Imputation
      7. 42.7 Sensitivity Analysis
      8. 42.8 Conclusion
      9. References
    49. Chapter 43: Mother to Child Human Immunodeficiency Virus Transmission Trials
      1. 43.1 Introduction
      2. 43.2 The Pediatric Aids Clinical Trials Group 076 Trial
      3. 43.3 Results
      4. 43.4 The European Mode of Delivery Trial
      5. 43.5 The HIV Network for Prevention Trials 012 Trial
      6. 43.6 The Mashi Trial
      7. References
      8. Further Reading
    50. Chapter 44: Multiple Testing in Clinical Trials
      1. 44.1 Introduction
      2. 44.2 Concepts of Error Rates
      3. 44.3 Union-Intersection Testing
      4. 44.4 Closed Testing
      5. 44.5 Partition Testing
      6. References
      7. Further Reading
    51. Chapter 45: Multicenter Trials
      1. 45.1 Definitions
      2. 45.2 History
      3. 45.3 Examples
      4. 45.4 Organizational and Operational Features
      5. 45.5 Strengths
      6. 45.6 Counts
      7. Readings
      8. References
    52. Chapter 46: Multiple Endpoints
      1. 46.1 Introduction
      2. 46.2 Multiple Testing Methods
      3. 46.3 Multivariate Global Tests
      4. 46.4 Conclusions
      5. References
    53. Chapter 47: Multiple Risk Factor Intervention Trial
      1. 47.1 Introduction
      2. 47.2 Trial Design
      3. 47.3 Trial Screening and Execution
      4. 47.4 Findings at the End of Intervention
      5. 47.5 Long-Term Follow-Up
      6. 47.6 Epidemiologic Findings from Long-Term Follow-up of 361,662 MRFIT Screenees
      7. 47.7 Conclusions
      8. References
      9. Further Reading
    54. Chapter 48: N-of-1 Randomized Trials
      1. 48.1 Introduction
      2. 48.2 Goal of N-of-1 Studies
      3. 48.3 Requirements
      4. 48.4 Design Choices and Details for N-of-1 Studies
      5. 48.5 Statistical Issues
      6. 48.6 Other Issues
      7. 48.7 Conclusions
      8. References
    55. Chapter 49: Noninferiority Trial
      1. 49.1 Introduction
      2. 49.2 Essential Elements of Noninferiority Trial Design
      3. 49.3 Objectives of Noninferiority Trials
      4. 49.4 Measure of Treatment Effect
      5. 49.5 Noninferiority Margin
      6. 49.6 Statistical Testing for Noninferiority
      7. 49.7 Medication Nonadherence and Misclassification/Measurement Error
      8. 49.8 Testing Superiority and Noninferiority
      9. 49.9 Conclusion
      10. References
    56. Chapter 50: Nonrandomized Trials
      1. 50.1 Introduction
      2. 50.2 Randomized vs. Nonrandomized Clinical Trials
      3. 50.3 Control Groups in Nonrandomized Trials
      4. 50.4 Statistical Methods in Design and Analyses
      5. 50.5 Conclusion and Discussion
      6. References
    57. Chapter 51: Open-Labeled Trials
      1. 51.1 Introduction
      2. 51.2 The Importance of Blinding
      3. 51.3 Reasons Why Trials Might Have to be Open-Label
      4. 51.4 When Open-Label Trials Might be Desirable
      5. 51.5 Concluding Comments
      6. References
      7. Further Reading
    58. Chapter 52: Optimizing Schedule of Administration in Phase I Clinical Trials
      1. 52.1 Introduction
      2. 52.2 Motivating Example
      3. 52.3 Design Issues
      4. 52.4 Trial Conduct
      5. 52.5 Extensions and Related Research
      6. References
    59. Chapter 53: Partially Balanced Designs
      1. 53.1 Introduction
      2. 53.2 Association Schemes
      3. 53.3 Partially Balanced Incomplete Block Designs
      4. 53.4 Generalizations of PBIBDs and Related Ideas
      5. References
    60. Chapter 54: Phase I/II Clinical Trials
      1. 54.1 Introduction
      2. 54.2 Traditional Approach
      3. 54.3 Recent Developments
      4. 54.4 Illustrations
      5. References
    61. Chapter 55: Phase II/III Trials
      1. 55.1 Introduction
      2. 55.2 Description and Legal Basis
      3. 55.3 Better Dose-Response Studies with Phase 2/3 Designs
      4. 55.4 Principles of Phase 2/3 Designs
      5. 55.5 Inferential Difficulties
      6. 55.6 Summary
      7. References
      8. Further Reading
    62. Chapter 56: Phase I Trials
      1. 56.1 Introduction
      2. 56.2 Phase I in Healthy Volunteers
      3. 56.3 Phase I in Cancer Patients
      4. 56.4 Perspectives in the Future of Cancer Phase I Trials
      5. 56.5 Discussion
      6. References
    63. Chapter 57: Phase II Trials
      1. 57.1 Introduction
      2. 57.2 Proof-of-Concept (Phase IIa) Trials
      3. 57.3 Dose-Ranging (Phase IIb) Trials
      4. 57.4 Efficacy Endpoints
      5. 57.5 Oncology Phase II Trials
      6. References
      7. Further Reading
    64. Chapter 58: Phase III Trials
      1. 58.1 Introduction
      2. 58.2 Research Methodology in Phase III
      3. 58.3 Type of Design
      4. 58.4 Discussion
      5. References
    65. Chapter 59: Phase IV Trials
      1. 59.1 Introduction
      2. 59.2 Definitions and Context
      3. 59.3 Different Purposes for Phase IV Trials
      4. 59.4 Essential and Desirable Features of Phase IV Trials
      5. 59.5 Examples of Phase IV Studies
      6. 59.6 Conclusion
      7. References
      8. Further Reading
    66. Chapter 60: Phase I Trials in Oncology
      1. 60.1 Introduction
      2. 60.2 Dose-Limiting Toxicity
      3. 60.3 Starting Dose
      4. 60.4 Dose Level Selection
      5. 60.5 Study Design and General Considerations
      6. 60.6 Traditional, Standard, or 3 + 3 Design
      7. 60.7 Continual Reassessment Method and Other Designs that Target the MTD
      8. 60.8 Start-Up Rule
      9. 60.9 Phase I Trials with Long Follow-Up
      10. 60.10 Phase I Trials with Multiple Agents
      11. 60.11 Phase I Trials with the MTD Defined using Toxicity Grades
      12. References
      13. Further Reading
    67. Chapter 61: Placebos
      1. 61.1 History of Placebo
      2. 61.2 Definitions
      3. 61.3 Magnitude of the Placebo Effect
      4. 61.4 Influences on the Placebo Effect
      5. 61.5 Ethics of Employing Placebo in Research
      6. 61.6 Guidelines for the Use of Placebos in Research
      7. 61.7 Innovations to Improve Research Involving Placebo
      8. 61.8 Summary
      9. References
    68. Chapter 62: Planning a Group-Randomized Trial
      1. 62.1 Introduction
      2. 62.2 The Research Question
      3. 62.3 The Research Team
      4. 62.4 The Research Design
      5. 62.5 Potential Design Problems and Methods to Avoid Them
      6. 62.6 Potential Analytic Problems and Methods to Avoid Them
      7. 62.7 Variables of Interest and Their Measures
      8. 62.8 The Intervention
      9. 62.9 Power
      10. 62.10 Summary
      11. References
    69. Chapter 63: Postmenopausal Estrogen/Progestin Interventions Trial (PEPI)
      1. 63.1 Introduction
      2. 63.2 Design and Objectives
      3. 63.3 Study Design
      4. 63.4 Outcomes
      5. 63.5 Results
      6. 63.6 Conclusions
      7. References
      8. Further Reading
    70. Chapter 64: Preference Trials
      1. 64.1 Introduction
      2. 64.2 Potential Effects of Preference
      3. 64.3 The Patient Preference Design
      4. 64.4 Advantages and Disadvantages of the Patient Preference Design
      5. 64.5 Alternative Designs
      6. 64.6 Discussion
      7. References
      8. Further Reading
    71. Chapter 65: Prevention Trials
      1. 65.1 Introduction
      2. 65.2 Role Among Possible Research Strategies
      3. 65.3 Prevention Trial Planning and Design
      4. 65.4 Conduct, Monitoring, and Analysis
      5. References
    72. Chapter 66: Primary Efficacy Endpoint
      1. 66.1 Defining the Primary Endpoint
      2. 66.2 Fairness of Endpoints
      3. 66.3 Specificity of the Primary Endpoint
      4. 66.4 Composite Primary Endpoints
      5. 66.5 Missing Primary Endpoint Data
      6. 66.6 Censored Primary Endpoints
      7. 66.7 Surrogate Primary Endpoints
      8. 66.8 Multiple Primary Endpoints
      9. 66.9 Secondary Endpoints
      10. References
      11. Further Reading
    73. Chapter 67: Prognostic Variables in Clinical Trials
      1. 67.1 Introduction
      2. 67.2 A General Theory of Prognostic Variables
      3. 67.3 Valid Covariates and Recognizable Subsets
      4. 67.4 Stratified Randomization and Analysis
      5. 67.5 Statistical Importance of Prognostic Factors
      6. References
    74. Chapter 68: Randomization Procedures
      1. 68.1 Basics
      2. 68.2 General Classes of Randomization: Complete versus Imbalance-Restricted Procedures
      3. 68.3 Procedures for Imbalance-Restricted Randomization
      4. 68.4 Randomization-Based Analysis and the Validation Transformation
      5. 68.5 Conclusions
      6. References
    75. Chapter 69: Randomization Schedule
      1. 69.1 Introduction
      2. 69.2 Preparing the Schedule
      3. 69.3 Schedules for Open-Label Trials
      4. 69.4 Schedules to Mitigate Loss of Balance in Treatment Assignments Because of Incomplete Blocks
      5. 69.5 Issues Related to the use of Randomization Schedule
      6. 69.6 Summary
      7. References
      8. Further Reading
    76. Chapter 70: Repeated Measurements
      1. 70.1 Introduction and Case Study
      2. 70.2 Linear Models for Gaussian Data
      3. 70.3 Models for Discrete Outcomes
      4. 70.4 Design Considerations
      5. 70.5 Concluding Remarks
      6. References
    77. Chapter 71: Simple Randomization
      1. 71.1 Introduction
      2. 71.2 Concept of Randomization
      3. 71.3 Why is Randomization Needed?
      4. 71.4 Methods: Simple Randomization
      5. 71.5 Advantages and Disadvantages of Randomization
      6. 71.6 Other Randomization Methods
      7. 71.7 Stratified Randomization
      8. References
      9. Further Reading
    78. Chapter 72: Subgroups
      1. 72.1 Introduction
      2. 72.2 The General Problem
      3. 72.3 Definitions
      4. 72.4 Subgroup Effects and Interactions
      5. 72.5 Tests of Interactions and the Problem of Power
      6. 72.6 Subgroups and the Problem of Multiple Comparisons
      7. 72.7 Demographic Subgroups
      8. 72.8 Physiological Subgroups
      9. 72.9 Target Subgroups
      10. 72.10 Improper Subgroups
      11. 72.11 Summary
      12. References
    79. Chapter 73: Superiority Trials
      1. 73.1 Introduction
      2. 73.2 Clinicians Ask One-Sided Questions, and Want Immediate Answers
      3. 73.3 But Traditional Statistics Is Two-Sided
      4. 73.4 The Consequences of Two-Sided Answers to One-Sided Questions
      5. 73.5 The Fallacy of the “Negative” Trial
      6. 73.6 The Solution Lies in Employing One-Sided Statistics
      7. 73.7 Examples of Employing One-Sided Statistics
      8. 73.8 One-Sided Statistical Analyses Need to be Specified Ahead of Time
      9. 73.9 A Graphic Demonstration of Superiority and Noninferiority
      10. 73.10 How to Think about and Incorporate Minimally Important Differences
      11. 73.11 Incorporating Confidence Intervals for Treatment Effects
      12. 73.12 Why We Should Never Label an “Indeterminate” Trial Result as “Negative” or as Showing “No Effect”
      13. 73.13 How Does a Treatment Become “Established Effective Therapy”?
      14. 73.14 Most Trials are Too Small to Declare a Treatment “Established Effective Therapy”
      15. 73.15 How Do We Achieve a Superiority Result?
      16. 73.16 Superiority and Noninferiority Trials when Established Effective Therapy Already Exists
      17. 73.17 Exceptions to the Rule that It Is Always Unethical to Substitute Placebos for Established Effective Therapy
      18. 73.18 When a Promising New Treatment Might be Added to Established Effective Therapy
      19. 73.19 Using Placebos in a Trial Should Not Mean the Absence of Treatment
      20. 73.20 Demonstrating Trials of Promising New Treatments Against (or in Addition to) Established Effective Therapy
      21. 73.21 Why We Almost Never Find, and Rarely Seek, True “Equivalence”
      22. 73.22 The Graphical Demonstration of “Superiority” and “Noninferiority”
      23. 73.23 Completing the Circle: Converting One-Sided Clinical Thinking into One-Sided Statistical Analysis
      24. 73.24 A Final Note on Superiority and Noninferiority Trials of “Me-Too” Drugs
      25. References
      26. Further Reading
    80. Chapter 74: Surrogate Endpoints
      1. 74.1 Introduction
      2. 74.2 Illustrations
      3. 74.3 Validation of Surrogates
      4. 74.4 Auxiliary Variables
      5. 74.5 Conclusions
      6. References
    81. Chapter 75: TNT Trial
      1. 75.1 Introduction
      2. 75.2 Objectives
      3. 75.3 Study Design
      4. 75.4 Results
      5. 75.5 Conclusions
      6. References
      7. Further Reading
    82. Chapter 76: UGDP Trial
      1. 76.1 Introduction
      2. 76.2 Design and Chronology
      3. 76.3 Results
      4. 76.4 Conclusion and Discussion
      5. References
    83. Chapter 77: Women’s Health Initiative Hormone Therapy Trials
      1. 77.1 Introduction
      2. 77.2 Objectives
      3. 77.3 Study Design
      4. 77.4 Results
      5. 77.5 Conclusions
      6. References
    84. Chapter 78: Women’s Health Initiative Dietary Modification Trial: Update and Application of Biomarker Calibration to Self-Report Measures of Diet and Physical Activity
      1. 78.1 Rationale for Biomarker Calibration of Self-Report Measures of Diet
      2. 78.2 Nutrient Biomarker Study Energy and Protein Calibration
      3. 78.3 Measurement Error Properties of 4DFR, 24HR, and FFQ
      4. 78.4 Calibration of Self-Report Measures of Physical Activity
      5. 78.5 Psychosocial Measures and Biomarker-Calibrated Intake
      6. 78.6 Calibrated Energy, Protein, Protein Density, and Cardiovascular Disease Incidence
      7. 78.7 Diabetes and Calibrated Consumption
      8. 78.8 Cancer and Calibrated Intake
      9. 78.9 Associations Between Protein Intake, Frailty, and Renal Function
      10. 78.10 Summary and Future Directions
      11. References
    85. Index

    Product information

    • Title: Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs
    • Author(s): N. Balakrishnan
    • Release date: February 2014
    • Publisher(s): Wiley
    • ISBN: 9781118304730