Methods and applications of statistics in clinical trials. Volume 1, concepts, principles, trials, and design

Content: Contributors xxiii Preface xxix 1 Absolute Risk Reduction 1 1.1 Introduction 1 1.2 Preliminary Issues 1 1.3 Point and Interval Estimates for a Single Proportion 2 1.4 An Unpaired Difference of Proportions 5 1.5 Number Needed to Treat 8 1.6 A Paired Difference of Proportions 10 References 11 Further Reading 12 2 Accelerated Approval 14 2.1 Introduction 14 2.2 Accelerated Development Versus Expanded Access in the U.S.A 14 2.3 Sorting the Terminology-Which FDA Initiatives Do What? 15 2.4 Accelerated Approval Regulations: 21 C.F.R. 314.500, 314.520, 601.40 16 2.5 Stages of Drug Development and FDA Initiatives 16 2.6 Accelerated Approval Regulations: 21 CFR 314.500, 314.520, 601.40 17 2.7 Accelerated Approval with Surrogate Endpoints 18 2.8 Accelerated Approval with Restricted Distribution 20 2.9 Phase IV Studies/Post Marketing Surveillance 20 2.10 Benefit Analysis for Accelerated Approvals Versus Other Illnesses 21 2.11 Problems, Solutions, and Economic Incentives 22 2.12 Future Directions 24 References 25 Further Reading 26 3 AIDS Clinical Trials Group (ACTG) 27 3.1 Introduction 27 3.2 A Brief Primer on HIV/AIDS 27 3.3 ACTG Overview 28 3.4 ACTG Scientific Activities 29 3.5 Development of Potent Antiretroviral Therapy (ART) 29 3.6 Expert Systems and Infrastructure 36 References 37 4 Algorithm-Based Designs 40 4.1 Phase I Dose-Finding Studies 40 4.2 Accelerated Designs 43 4.3 Model-Based Approach in the Estimation of MTD 46 4.4 Exploring Algorithm-Based Designs With Prespecified Targeted Toxicity Levels 48 References 51 5 Alpha-Spending Function 53 5.1 Introduction 53 5.2 Alpha Spending Function Motivation 54 5.3 The Alpha Spending Function 56 5.4 Application of the Alpha Spending Function 57 5.5 Confidence Intervals and Estimation 59 5.6 Trial Design 59 5.7 Conclusions 61 References 61 Further Reading 63 6 Application of New Designs in Phase I Trials 65 6.1 Introduction 65 6.2 Objectives of a Phase I Trial 65 6.3 Standard Designs and Their Shortcomings 66 6.4 Some Novel Designs 67 6.5 Discussion 72 References 72 Further Reading 73 7 ASCOT Trial 74 7.1 Introduction 74 7.2 Objectives 74 7.3 Study Design 74 7.4 Results 75 7.5 Discussion and Conclusions 77 References 78 8 Benefit/Risk Assessment in Prevention Trials 80 8.1 Introduction 80 8.2 Types of B/RAs Performed in Prevention Trials 81 8.3 Alternative Structures of the Benefit/Risk Algorithm used in Prevention Trials 82 8.4 Methodological and Practical Issues with B/RA in Prevention Trials 84 References 87 9 Biased Coin Randomization 90 9.1 Randomization Strategies for Overall Treatment Balance 90 9.2 The Biased Coin Randomization Procedure 91 9.3 Properties 92 9.4 Extensions to the Biased Coin Randomization 92 9.5 Adaptive Biased Coin Randomization 94 9.6 Urn Models 99 9.7 Treatment Balance for Covariates 102 9.8 Application of Biased Coin Designs to Response-Adaptive Randomization 103 References 104 10 Biological Assay, Overview 106 10.1 Introduction 106 10.2 Direct Dilution Assays 108 10.3 Indirect Dilution Assays 109 10.4 Indirect Quantal Assays 113 10.5 Stochastic Approximation in Bioassay 116 10.6 Radioimmunoassay 117 10.7 Dosimetry and Bioassay 118 10.8 Semiparametrics in Bioassays 119 10.9 Nonparametrics in Bioassays 119 10.10 Bioavailability and Bioequivalence Models 120 10.11 Pharmacogenomics in Modern Bioassays 121 10.12 Complexities in Bioassay Modeling and Analysis 122 References 122 Further Reading 124 11 Block Randomization 125 11.1 Introduction 125 11.2 Simple Randomization 125 11.3 Restricted Randomization Through the Use of Blocks 126 11.4 Schemes Using a Single Block for the Whole Trial 130 11.5 Use of Unequal and Variable Block Sizes 131 11.6 Inference and Analysis Following Blocked Randomization 134 11.7 Miscellaneous Topics Related to Blocked Randomization 135 References 136 Further Reading 138 12 Censored Data 139 12.1 Introduction 139 12.2 Independent Censoring 140 12.3 Likelihoods: Noninformative Censoring 143 12.4 Other Kinds of Incomplete Observation 143 References 141 13 Clinical Data Coordination 146 13.1 Introduction 146 13.2 Study Initiation 147 13.3 Study Conduct 151 13.4 Study Closure 158 13.5 Summary 161 References 162 14 Clinical Data Management 164 14.1 Introduction 164 14.2 How Has Clinical Data Management Evolved? 165 14.3 Electronic Data Capture 166 14.4 Regulatory Involvement with Clinical Data Management 167 14.5 Professional Societies 167 14.6 Look to the Future 168 14.7 Conclusion 169 References 169 15 Clinical Significance 170 15.1 Introduction 170 15.2 Historical Background 170 15.3 Article Outline 171 15.4 Design and Methodology 171 15.5 Examples 181 15.6 Recent Developments 181 15.7 Concluding Remarks 185 References 185 16 Clinical Trial Misconduct 191 16.1 The Scope of this Article 191 16.2 Why Does Research Misconduct Matter? 191 16.3 Early Cases 192 16.4 Definition 193 16.5 Intent 194 16.6 What Scientific Misconduct was Not 194 16.7 The Process 194 16.8 The Past Decade 195 16.9 Lessons from the U.S. Experience 196 16.10 Outside the United States 197 16.11 Scientific Misconduct During Clinical Trials 198 16.12 Audit 198 16.13 Causes 199 16.14 Prevalence 200 16.15 Peer Review and Misconduct 200 16.16 Retractions 201 16.17 Prevention 201 References 202 17 Clinical Trials, Early Cancer and Heart Disease 205 17.1 Introduction 205 17.2 Developments in Clinical Trials at the National Cancer Institute (NCI) 205 17.3 Developments in Clinical Trials at the National Heart, Lung, and Blood Institute (NHLBI) 209 References 213 18 Cluster Randomization 216 18.1 Introduction 216 18.2 Examples of Cluster Randomization Trials 217 18.3 Principles of Experimental Design 218 18.4 Experimental and Quasi-Experimental Designs 219 18.5 The Effect of Failing to Replicate 220 18.6 Sample Size Estimation 221 18.7 Cluster Level Analyses 222 18.8 Individual Level Analyses 223 18.9 Incorporating Repeated Assessments 225 18.10 Study Reporting 226 18.11 Meta-Analysis 227 References 228 19 Coherence in Phase I Clinical Trials 230 19.1 Introduction 230 19.2 Coherence: Definitions and Organization 230 19.3 Coherent Designs 232 19.4 Compatible Initial Design 233 19.5 Group Coherence 234 19.6 Real-Time Coherence 235 19.7 Discussion 238 References 238 20 Compliance and Survival Analysis 240 20.1 Compliance: Cause and Effect 240 20.2 All-or-Nothing Compliance 241 20.3 More General Exposure Patterns 242 20.4 Other Structural Modeling Options 242 References 244 21 Composite Endpoints in Clinical Trials 246 21.1 Introduction 246 21.2 The Rationale for Composite Endpoints 246 21.3 Formulation of Composite Endpoints 247 21.4 Examples 248 21.5 Interpreting Composite Endpoints 250 21.6 Conclusions 251 References 251 22 Confounding 252 22.1 Introduction 252 22.2 Confounding as a Bias in Effect Estimation 252 22.3 Confounding and Noncollapsibility 258 22.4 Confounding in Experimental Design 260 References 261 23 Control Groups 263 23.1 Introduction 263 23.2 History 263 23.3 Ethics 264 23.4 Types of Control Groups: Historical Controls 266 23.5 Types of Control Groups: Randomized Controls 268 23.6 Conclusion 271 References 271 24 Coronary Drug Project 273 24.1 Introduction 273 24.2 Objectives 273 24.3 Study Design and Methods 273 24.4 Results 275 24.5 Conclusions and Lessons Learned 281 References 282 Further Reading 284 25 Covariates 285 25.1 Universal Character of Covariates 285 25.2 Use of Covariates in Clinical Trials 286 25.3 Continuous Covariates: Categorization or Functional Form? 293 25.4 Reporting and Summary Assessment of Prognostic Markers 295 References 296 26 Crossover Design 300 26.1 Introduction 300 26.2 The Two-Period, Two-Treatment Design 301 26.3 Higher Order Designs 304 26.4 Model-Based Analyses 307 References 308 27 Crossover Trials 310 27.1 Introduction 310 27.2 2 x 2 Crossover Trial 312 27.3 Higher-Order Designs for Two Treatments 312 27.4 Designs for Three or More Treatments 312 27.5 Analysis of Continuous Data 314 27.6 Analysis of Discrete Data 315 27.7 Concluding Remarks 317 References 317 28 Diagnostic Studies 320 28.1 Introduction 320 28.2 Diagnostic Studies 320 28.3 Reliability 324 28.4 Validity 331 References 338 Further Reading 339 29 DNA Bank 340 29.1 Definition and Objectives of DNA Biobanks 340 29.2 Types of DNA Biobanks 343 29.3 Types of Samples Stored 344 29.4 Quality Assurance and Quality Control in DNA Biobanks 345 29.5 Ethical Issues 346 29.6 Current Biobank Initiatives 348 29.7 Conclusions 350 References 350 30 Up-and-Down and Escalation Designs 353 30.1 Introduction 353 30.2 Up-and-Down Designs 353 30.3 Escalation Designs 357 30.4 Comparing U&D, Escalation and Model-Based Designs 359 References 359 Further Reading 361 31 Dose Ranging Crossover Designs 362 31.1 Introduction 362 31.2 Titration Designs and Extension Studies 369 31.3 Randomized Designs 373 31.4 Discussion and Conclusion 376 References 379 Further Reading 382 32 Flexible Designs 383 32.1 Introduction 383 32.2 The General Framework 384 32.3 Conditional Power and Sample Size Reassessment 387 32.4 Extending the Flexibility to the Choice of the Number of Stages 392 32.5 Selection of the Test Statistic 393 32.6 More General Adaptations and Multiple Hypotheses Testing 393 32.7 An Example 395 32.8 Conclusion 395 References 396 33 Gene Therapy 399 33.1 Introduction 399 33.2 Requirements for Successful Therapeutic Intervention 399 33.3 Pre-Clinical Research 402 33.4 Translational Challenges of Gene Therapy Trials 404 33.5 Clinical Trials * 407 33.6 Lessons Learned 408 33.7 The Way Forward 411 References 411 Further Reading 422 34 Global Assessment Variables 423 34.1 Introduction 423 34.2 Scientific Questions for Multiple Outcomes 423 34.3 General Comments on the GST 424 34.4 Recoding Outcome Measures 424 34.5 Types of Global Statistical Tests (GSTs) 425 34.6 Other Considerations 428 34.7 Other Methods 430 34.8 Examples of the Application of GST 434 34.9 Conclusions 435 References 435 35 Good Clinical Practice (GCP) 438 35.1 Introduction 438 35.2 Human Rights and Protections 438 35.3 Informed Consent 439 35.4 Investigational Protocol 439 35.5 Investigator's Brochure 440 35.6 Investigational New Drug Application 440 35.7 Production of the Investigational Drug 440 35.8 Clinical Testing 441 35.9 Sponsors 442 35.10 Contract Research Organization 444 35.11 Monitors 444 35.12 Investigators 444 35.13 Documentation 444 35.14 Clinical Holds 445 35.15 Inspections/Audits 446 References 446 Further Reading 446 36 Group-Randomized Trials 448 36.1 Introduction 448 36.2 Group-Randomized Trials in Context 449 36.3 The Development of Group-Randomized Trials in Public Health 450 36.4 The Range of GRTs in Public Health 451 36.5 Current Design and Analytic Practices in GRTs in Public Health 452 36.6 The Future of Group-Randomized Trials 453 36.7 Planning a New Group-Randomized Trial 456 References 462 37 Group Sequential Designs 467 37.1 Introduction 467 37.2 Classical Designs 469 37.3 The a-Spending Function Approach 474 37.4 Point Estimates and Confidence Intervals 477 37.5 Supplements 478 References 479 38 Hazard Ratio 483 38.1 Introduction 483 38.2 Definitions 483 38.3 Illustration of Hazard Rate, Hazard Ratio and Risk Ratio 484 38.4 Example on the Use and Usefulness of Hazard Ratios 486 38.5 Ad-hoc Estimator of the Hazard Ratio 486 38.6 Confidence Interval of the Ad-hoc Estimator 487 38.7 Ad-hoc Estimator Stratified for the Covariate Renal Function 491 38.8 Properties of the Ad-hoc Estimator 493 38.9 Class of Generalized Rank Estimators of the Hazard Ratio 493 38.10 Estimation of the Hazard Ratio with Cox's Proportional Hazards Model 494 38.11 Discussion 497 Further Reading 499 References 499 39 Large Simple Trials 500 39.1 Large, Simple Trials 500 39.2 Small but Clinically Important Objective 500 39.3 Eligibility 502 39.4 Randomized Assignment 502 39.5 Outcome Measures 504 39.6 Conclusions 506 References 506 Further Reading 508 40 Longitudinal Data 510 40.1 Definition 510 40.2 Longitudinal Data from Clinical Trials 510 40.3 Advantages 512 40.4 Challenges 512 40.5 Analysis of Longitudinal Data 513 References 514 Further Reading 514 41 Maximum Duration and Information Trials 515 41.1 Introduction 515 41.2 Two Paradigms: Duration versus Information 516 41.3 Sequential Studies: Maximum Duration versus Information Trials 516 41.4 An Example of a Maximum Information Trial 519 References 521 42 Missing Data 522 42.1 Introduction 522 42.2 Methods in Common Use 524 42.3 An Alternative Approach to Incomplete Data 525 42.4 Illustration: Orthodontic Growth Data 527 42.5 Inverse Probability Weighting 531 42.6 Multiple Imputation 531 42.7 Sensitivity Analysis 532 42.8 Conclusion 533 References 533 43 Mother to Child Human Immunodeficiency Virus Transmission Trials 536 43.1 Introduction 536 43.2 The Pediatric Aids Clinical Trials Group 076 Trial 538 43.3 Results 538 43.4 The European Mode of Delivery Trial 540 43.5 The HIV Network for Prevention Trials 012 Trial 541 43.6 The Mashi Trial 544 References 545 Further Reading 549 44 Multiple Testing in Clinical Trials 550 44.1 Introduction 550 44.2 Concepts of Error Rates 551 44.3 Union-Intersection Testing 552 44.4 Closed Testing 553 44.5 Partition Testing 555 References 556 Further Reading 557 45 Multicenter Trials 558 45.1 Definitions 558 45.2 History 560 45.3 Examples 561 45.4 Organizational and Operational Features 563 45.5 Strengths 564 45.6 Counts 565 Readings 569 References 569 46 Multiple Endpoints 570 46.1 Introduction 570 46.2 Multiple Testing Methods 571 46.3 Multivariate Global Tests 573 46.4 Conclusions 574 References 575 47 Multiple Risk Factor Intervention Trial 577 47.1 Introduction 577 47.2 Trial Design 577 47.3 Trial Screening and Execution 579 47.4 Findings at the End of Intervention 580 47.5 Long-Term Follow-Up 581 47.6 Epidemiologie Findings from Long-Term Follow-up of 361,662 MRFIT Screenees 582 47.7 Conclusions 583 References 583 Further Reading 586 48 N-of-1 Randomized Trials 587 48.1 Introduction 587 48.2 Goal of N-of-1 Studies 587 48.3 Requirements 588 48.4 Design Choices and Details for N-of-1 Studies 589 48.5 Statistical Issues 592 48.6 Other Issues 593 48.7 Conclusions 596 References 596 49 Noninferiority Trial 598 49.1 Introduction 598 49.2 Essential Elements of Noninferiority Trial Design 598 49.3 Objectives of Noninferiority Trials 600 49.4 Measure of Treatment Effect 600 49.5 Noninferiority Margin 601 49.6 Statistical Testing for Noninferiority 603 49.7 Medication Nonadherence and Misclassificat ion/Measurement Error 604 49.8 Testing Superiority and Noninferiority 605 49.9 Conclusion 605 References 605 50 Nonrandomized Trials 609 50.1 Introduction 609 50.2 Randomized vs. Nonrandomized Clinical Trials 609 50.3 Control Groups in Nonrandomized Trials 611 50.4 Statistical Methods in Design and Analyses 613 50.5 Conclusion and Discussion 616 References 617 51 Open-Labeled Trials 619 51.1 Introduction 619 51.2 The Importance of Blinding 619 51.3 Reasons Why Trials Might Have to be Open-Label 622 51.4 When Open-Label Trials Might be Desirable 623 51.5 Concluding Comments 623 References 623 Further Reading 624 52 Optimizing Schedule of Administration in Phase I Clinical Trials 625 52.1 Introduction 625 52.2 Motivating Example 627 52.3 Design Issues 627 52.4 Trial Conduct 631 52.5 Extensions and Related Research 632 References 632 53 Partially Balanced Designs 635 53.1 Introduction 635 53.2 Association Schemes 635 53.3 Partially Balanced Incomplete Block Designs 641 53.4 Generalizations of PBIBDs and Related Ideas 648 References 655 54 Phase I/II Clinical Trials 658 54.1 Introduction 658 54.2 Traditional Approach 659 54.3 Recent Developments 660 54.4 Illustrations 663 References 665 55 Phase II/III Trials 667 55.1 Introduction 667 55.2 Description and Legal Basis 668 55.3 Better Dose-Response Studies with Phase 2/3 Designs 672 55.4 Principles of Phase 2/3 Designs 673 55.5 Inferential Difficulties 676 55.6 Summary 678 References 679 Further Reading 680 56 Phase I Trials 682 56.1 Introduction 682 56.2 Phase I in Healthy Volunteers 683 56.3 Phase I in Cancer Patients 684 56.4 Perspectives in the Future of Cancer Phase I Trials 687 56.5 Discussion 688 References 688 57 Phase II Trials 692 57.1 Introduction 692 57.2 Proof-of-Concept (Phase Ha) Trials 693 57.3 Dose-Ranging (Phase lib) Trials 695 57.4 Efficacy Endpoints 697 57.5 Oncology Phase II Trials 697 References 697 Further Reading 699 58 Phase III Trials 700 58.1 Introduction 700 58.2 Research Methodology in Phase III 700 58.3 Type of Design 706 58.4 Discussion 708 References 709 59 Phase IV Trials 711 59.1 Introduction 711 59.2 Definitions and Context 711 59.3 Different Purposes for Phase IV Trials 712 59.4 Essential and Desirable Features of Phase IV Trials 715 59.5 Examples of Phase IV Studies 715 59.6 Conclusion 717 References 717 Further Reading 718 60 Phase I Trials in Oncology 719 60.1 Introduction 719 60.2 Dose-Limiting Toxicity 719 60.3 Starting Dose 720 60.4 Dose Level Selection 720 60.5 Study Design and General Considerations 720 60.6 Traditional, Standard, or 3 + 3 Design 721 60.7 Continual Reassessment Method and Other Designs that Target the MTD722 60.8 Start-Up Rule 722 60.9 Phase I Trials with Long Follow-Up 722 60.10 Phase I Trials with Multiple Agents 723 60.11 Phase I Trials with the MTD Defined using Toxicity Grades 723 References 723 Further Reading 724 61 Placebos 725 61.1 History of Placebo 725 61.2 Definitions 725 61.3 Magnitude of the Placebo Effect 726 61.4 Influences on the Placebo Effect 727 61.5 Ethics of Employing Placebo in Research 728 61.6 Guidelines for the Use of Placebos in Research 729 61.7 Innovations to Improve Research Involving Placebo 731 61.8 Summary 732 References 732 62 Planning a Group-Randomized Trial 736 62.1 Introduction 736 62.2 The Research Question 736 62.3 The Research Team 737 62.4 The Research Design 737 62.5 Potential Design Problems and Methods to Avoid Them 738 62.6 Potential Analytic Problems and Methods to Avoid Them 739 62.7 Variables of Interest and Their Measures 739 62.8 The Intervention 740 62.9 Power 742 62.10 Summary 742 References 743 63 Postmenopausal Estrogen/Progestin Interventions Trial (PEPI) 744 63.1 Introduction 744 63.2 Design and Objectives 744 63.3 Study Design 746 63.4 Outcomes 747 63.5 Results 749 63.6 Conclusions 753 References 754 Further Reading 756 64 Preference Trials 759 64.1 Introduction 759 64.2 Potential Effects of Preference 759 64.3 The Patient Preference Design 761 64.4 Advantages and Disadvantages of the Patient Preference Design 761 64.5 Alternative Designs 764 64.6 Discussion 767 References 768 Further Reading 769 65 Prevention Trials 770 65.1 Introduction 770 65.2 Role Among Possible Research Strategies 771 65.3 Prevention Trial Planning and Design 773 65.4 Conduct, Monitoring, and Analysis 775 References 776 66 Primary Efficacy Endpoint 779 66.1 Defining the Primary Endpoint 779 66.2 Fairness of Endpoints 780 66.3 Specificity of the Primary Endpoint 782 66.4 Composite Primary Endpoints 782 66.5 Missing Primary Endpoint Data 784 66.6 Censored Primary Endpoints 784 66.7 Surrogate Primary Endpoints 785 66.8 Multiple Primary Endpoints 786 66.9 Secondary Endpoints 786 References 786 Further Reading 788 67 Prognostic Variables in Clinical Trials 789 67.1 Introduction 789 67.2 A General Theory of Prognostic Variables 791 67.3 Valid Covariates and Recognizable Subsets 792 67.4 Stratified Randomization and Analysis 793 67.5 Statistical Importance of Prognostic Factors 795 References 797 68 Randomization Procedures 799 68.1 Basics 799 68.2 General Classes of Randomization: Complete Versus Imbalance-Restricted Procedures 800 68.3 Procedures for Imbalance-Restricted Randomization 801 68.4 Randomization-Based Analysis and the Validation Transformation 809 68.5 Conclusions 810 References 810 69 Randomization Schedule 813 69.1 Introduction 813 69.2 Preparing the Schedule 814 69.3 Schedules for Open-Label Trials 817 69.4 Schedules to Mitigate Loss of Balance in Treatment Assignments Because of Incomplete Blocks 818 69.5 Issues Related to the use of Randomization Schedule 822 69.6 Summary 824 References 825 Further Reading 826 70 Repeated Measurements 827 70.1 Introduction and Case Study 827 70.2 Linear Models for Gaussian Data 828 70.3 Models for Discrete Outcomes 831 70.4 Design Considerations 836 70.5 Concluding Remarks 837 References 838 71 Simple Randomization 841 71.1 Introduction 841 71.2 Concept of Randomization 841 71.3 Why is Randomization Needed? 842 71.4 Methods: Simple Randomization 842 71.5 Advantages and Disadvantages of Randomization 845 71.6 Other Randomization Methods 846 71.7 Stratified Randomization 846 References 849 Further Reading 849 72 Subgroups 850 72.1 Introduction 850 72.2 The General Problem 851 72.3 Definitions 851 72.4 Subgroup Effects and Interactions 852 72.5 Tests of Interactions and the Problem of Power 853 72.6 Subgroups and the Problem of Multiple Comparisons 856 72.7 Demographic Subgroups 858 72.8 Physiological Subgroups 861 72.9 Target Subgroups 861 72.10 Improper Subgroups 863 72.11 Summary 865 References 865 73 Superiority Trials 867 73.1 Introduction 867 73.2 Clinicians Ask One-Sided Questions, and Want Immediate Answers 867 73.3 But Traditional Statistics Is Two-Sided 867 73.4 The Consequences of Two-Sided Answers to One-Sided Questions 868 73.5 The Fallacy of the "Negative" Trial 868 73.6 The Solution Lies in Employing One-Sided Statistics 868 73.7 Examples of Employing One-Sided Statistics 868 73.8 One-Sided Statistical Analyses Need to be Specified Ahead of Time 869 73.9 A Graphic Demonstration of Superiority and Noninferiority 869 73.10 How to Think about and Incorporate Minimally Important Differences 870 73.11 Incorporating Confidence Intervals for Treatment Effects 871 73.12 Why We Should Never Label an "Indeterminate" Trial Result as "Negative" or as Showing "No Effect" 871 73.13 How Does a Treatment Become "Established Effective Therapy"? 872 73.14 Most Trials are Too Small to Declare a Treatment "Established Effective Therapy" 872 73.15 How Do We Achieve a Superiority Result? 872 73.16 Superiority and Noninferiority Trials when Established Effective Therapy Already Exists 872 73.17 Exceptions to the Rule that It Is Always Unethical to Substitute Placebos for Established Effective Therapy 873 73.18 When a Promising New Treatment Might be Added to Established Effective Therapy 873 73.19 Using Placebos in a Trial Should Not Mean the Absence of Treatment 874 73.20 Demonstrating Trials of Promising New Treatments Against (or in Addition to) Established Effective Therapy 874 73.21 Why We Almost Never Find, and Rarely Seek, True "Equivalence" 874 73.22 The Graphical Demonstration of "Superiority" and "Noninferiority" 876 73.23 Completing the Circle: Converting One-Sided Clinical Thinking into One-Sided Statistical Analysis 876 73.24 A Final Note on Superiority and Noninferiority Trials of "Me-Too" Drugs 877 References 877 Further Reading 877 74 Surrogate Endpoints 878 74.1 Introduction 878 74.2 Illustrations 879 74.3 Validation of Surrogates 880 74.4 Auxiliary Variables 883 74.5 Conclusions 884 References 885 75 TNT Trial 887 75.1 Introduction 887 75.2 Objectives 887 75.3 Study Design 887 75.4 Results 888 75.5 Conclusions 892 References 892 Further Reading 893 76 UGDP Trial 894 76.1 Introduction 894 76.2 Design and Chronology 895 76.3 Results 906 76.4 Conclusion and Discussion 909 References 914 77 Women's Health Initiative Hormone Therapy Trials 918 77.1 Introduction 918 77.2 Objectives 918 77.3 Study Design 918 77.4 Results 919 77.5 Conclusions 927 References 928 78 Women's Health Initiative Dietary Modification Trial 931 78.1 Rationale for Biomarker Calibration of Self-Report Measures of Diet 931 78.2 Nutrient Biomarker Study Energy and Protein Calibration 932 78.3 Measurement Error Properties of 4DFR, 24HR, and FFQ 933 78.4 Calibration of Self-Report Measures of Physical Activity 933 78.5 Psychosocial Measures and Biomarker-Calibrated Intake 936 78.6 Calibrated Energy, Protein, Protein Density, and Cardiovascular Disease Incidence 937 78.7 Diabetes and Calibrated Consumption 938 78.8 Cancer and Calibrated Intake 940 78.9 Associations Between Protein Intake, Frailty, and Renal Function 940 78.10 Summary and Future Directions 941 References 943 Index 945