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