Multiple analyses in clinical trials: fundamentals for investigators
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York ; Berlin ; Heidelberg ; Hong Kong ; London ; Milan
Springer
2003
|
| Schriftenreihe: | Statistics for biology and health
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XXIII, 436 S. graph. Darst. : 24 cm |
| ISBN: | 038700727X |
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| 650 | 4 | |a Clinical trials | |
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Datensatz im Suchindex
| _version_ | 1804132787262849024 |
|---|---|
| adam_text | Contents
Blossoms on a Healthy Plant 1
Epidemiology and Biostatistics 1
Association and Causation 2
The Central Core of Epidemiology 3
Scurvy 4
Cholera 5
Causality and Common Sense 6
Biostatisticians and Sampling Error 7
Cooperation Between the Disciplines 7
The Eye of the Beholder 10
Controversy 1: Biased by Nature? 10
The Supremacy of Mathematics? 12
Hammer Blows 13
The Rise and Decline of Significance Testing 14
Advice to the Physician Scientist 17
References 18
Chapter 1. Fundamentals of Clinical Trial Design 21
1.1 The Definition of a Clinical Trial 21
1.2 Principles of Randomization 22
1.2.1 Random Selection of Subjects from the Population 22
1.2.2 Random Allocation of Therapy 23
1.2.3 Stratified Randomization 25
1.3 The Use of Blinding 25
1.3.1 Single Blinded Trials 26
1.3.2 Double Blind Studies 27
1.3.3 Arthroscopy and the Art of the Double Blind 28
1.4 Interim Monitoring of Clinical Trials 30
xl
1.4.1 The Need for Trial Monitoring 30
1.4.2 Test Statistic Trajectories 31
1.4.3 Group Sequential Procedures 37
1.4.4 Stochastic Curtailment 39
1.5 Intention to Treat Analyses 39
1.6 Measures of Effect 40
1.7 The Goal of Statistical Hypothesis Testing 41
1.8 Sampling Error and Significance Testing 42
1.9 Statistical Power 43
1.10 Sample Size Computations 44
1.11 Analysis 44
References 45
Chapter 2. Multiple Analyses and the Random Experiment 47
2.1 Introduction 49
2.1.1 Advisory Committee Discussions 50
2.2 Prevalent Perceptions 50
2.3 Calling Your Shot 51
2.3.1 Vesnarinone 52
2.3.2 Losartan 54
2.3.3 Amlodipine 55
2.3.4 Carvedilol 56
2.3.5 Experimental Inconsistencies 58
2.4 Samples as Reflections 59
2.5 Representative Samples That Mislead? 60
2.6 Estimators 63
2.7 Random Experiments 64
2.7.1 What Is a Random Protocol? 64
2.7.2 Crippled Estimators in Random Experiments 65
2.7.3 Untrustworthy 65
2.8 Collecting the Entire Population 66
2.9 Regulatory Example 67
2.10 Additional Comments 68
2.10.1 Don t Rush to Judgment 68
2.10.2 Random Research in Extremis 69
2.10.3 Requirements of Investigators and Readers 69
2.11 Conclusions 70
Problems 70
References 71
Chapter 3. The Lure and Complexity of Multiple Analyses 75
3.1 Definition of Multiple Analyses 75
3.2 Why Do Multiple Analyses? 76
3.2.1 Logistical Efficiency 77
3.2.2 Epidemiologic Strength 77
3.2.3 The Need to Explore 79
3.3 Hypothesis Testing in Multiple Analyses 80
3.3.1 Nominal P Values 80
3.3.2 The Error of Interest: Familywise Error 81
3.3.3 Initial Computations for£ 82
3.3.4 FDA and Strength of Evidence 84
3.4 Is Tight Control of the FWER Necessary? 85
3.5 Community Protection 86
3.6 Efficacy and Drug Labels 89
3.7 The Bonferroni Inequality 90
3.8 Who Was Bonferroni? 93
3.9 Alternative Approaches 94
3.9.1 Sequentially Rejective Procedures 94
3.9.2 Who Chooses the a Level Threshold? 95
3.9.3 Resampling P Values 98
3.10 Conclusions 99
Problems 100
References 101
Chapter 4. Multiple Analyses and Multiple Endpoints 105
4.1 Introduction 105
4.2 Important Assumptions 106
4.3 Clinical Trial Result Descriptors 106
4.3.1 Positive and Negative Trials 106
4.3.2 Null Results Versus Uninformative Results 107
4.4 The Strategy for Multiple Endpoint Analysis 108
4.5 Tactic 1: Triage the Endpoints 110
4.5.1 The Process of Endpoint Triage Ill
4.5.2 An Example of the Endpoint Triage Process Ill
4.5.3 Other Motivations for Triaging Endpoints 112
4.5.4 Endpoint Triaging and Labeling Indications 113
4.6 Endpoint Descriptors 113
4.6.1 Primary Endpoints 114
4.6.2 Secondary Endpoints 115
4.6.3 Exploratory Endpoints 116
4.6.4 Choose Wisely 119
4.6.5 Planning Well to Learn Well 119
4.7 Mapping Out the Manuscript 121
4.7.1 The Design Manuscript 121
4.7.2 Laying Out the Manuscripts 122
4.8 Multiple Primary Endpoint Interpretations 124
4.9 Tactic 2: Differential a Allocation 126
4.9.1 Differential a Rate Allocation 127
4.9.2 Clinical Decisions in Allocating a 130
4.9.3 Example 1: Different Community Standards 131
4.9.4 Example 2: The Underpowered Environment 135
4.9.5 Example 3: Efficacy Reconsideration 139
4.9.6 Example 4: Multiple Endpoints 143
4.10 Multiple Analyses 145
4.10.1 Example 146
4.11 Theory Versus Reality 148
Problems 152
References 153
Chapter 5. Introduction to Multiple Dependent Analyses 1 155
5.1 Rationale for Dependent Testing 155
5.1.1 Review 155
5.2 The Notion of Dependent Analyses 156
5.2.1 The Nature of Relationships 156
5.2.2 Endpoint Coincidence and Correlation 158
5.2.3 Surrogate Endpoint Definition 162
5.3 Literature Review 163
5.3.1 Tukey s Procedure and Related Ad Hoc Computations 163
5.4 Hypothesis Test Dependency: Notation 166
5.5 The Independence Scenario 167
5.6 Demonstration of Perfect Dependence 169
5.7 Scenario Contrasts 171
5.8 Creation of the Dependency Parameter 172
5.9 Solving for a2 as a Function of D 176
5.10 Example 1: Implantable Cardiac Devices 177
5.11 Example 2: The CURE Trial 181
5.12 Example 3: Paroxysmal Atrial Fibrillation 183
5.13 Choosing the Dependency Parameter 187
5.13.1 Overestimation of Dependency Parameter 187
5.13.2 Guides to Choosing the Dependency Parameter 188
5.14 Hyperdependent Analyses 191
5.14.1 Hyperdependence as a Disadvantage 191
5.14.2 Hyperdependence as an Advantage 193
Problems 195
References 196
Chapter 6. Multiple Dependent Analyses II 199
6.1 Three Multidependent Analyses 199
6.1.1 Example of Dependency Among Three Endpoints 202
6.2 The Solution for Four Dependent Analyses 205
6.3 K Multidependent Analyses 206
6.4 Conservative Dependence 207
6.5 Generalization of the Bonferroni Inequality 209
6.6 Subclass Dependence 210
6.6.1 Solutions for Two Subclasses 210
6.6.2 Therapy for CHF 212
6.7 Conclusions 216
Problems 217
References 218
Chapter 7. Introduction to Composite Endpoints 219
7.1 Introduction 219
7.2 Definitions and Motivations 220
7.3 Notation 220
7.4 Motivations for Combined Endpoints 220
7.4.1 Epidemiologic Considerations 221
7.4.2 Sample Size Concerns 221
7.4.3 Improved Resolving Power 223
7.5 Properties of Combined Endpoints 225
7.6 Component Endpoint Coherence 225
7.7 Coincidence 225
7.8 Mutual Exclusivity and Disparate Events 227
7.9 The Problem with Mutual Exclusivity 228
7.10 Balancing the Separation 229
7.11 Component Endpoint Equivalence 230
7.12 Therapy Homogeneity 232
7.13 Composite Endpoint Measurement Rules 234
7.14 Prospective Identification 234
7.15 Combined Endpoint Ascertainment 235
7.16 Conclusions 236
Problems 237
References 237
Chapter 8. Multiple Analyses and Composite Endpoints 239
8.1 Examples of Composite Endpoint Use 239
8.2 Lipid Research Clinics 240
8.3UKPDS 241
8.4 HOPE 245
8.5 Principles of Combined Endpoint Use 247
8.6 a Allocation and Combined Endpoints 249
8.6.1 Familywise Error Control Procedures 249
8.6.2 Multiple Analyses and Composite Endpoint Distress 249
8.7 Example 1: Design for a Heart Failure Trial 251
8.8 Composite Endpoints: Diabetes Mellitus 256
8.9 Soft Components 261
8.10 Conclusions 263
Problems 264
References 264
Chapter 9. Introduction to Subgroup Analyses 267
9.1 Introduction 267
9.2 Definitions and Basic Concepts 268
9.2.1 Subgroups Versus Subgroup Strata 268
9.3 Interpretation Difficulties 269
9.4 Random Subgroups 269
9.5 Stratified Randomization 271
9.6 Proper Versus Improper Subgroups 274
9.7 Intention to Treat Versus As Treated 278
9.8 Example 1: Diabetes Mellitus in SAVE 279
9.9 Subgroup Result Depiction 281
Problems 283
References 284
Chapter 10. Subgroups II: Effect Domination and Controversy 287
10.1 Effect Domination Principle 287
10.2 Assessment of Subgroup Effects 288
10.2.1 Effect Modification and Interaction Analyses 288
10.2.2 Within Stratum Effects 290
10.3 Problematic Subgroup Analyses 291
10.4 The MERIT Trial 292
10.5 Ethnicity and ACE i therapy 295
10.6 The NETT Study 298
10.7 The Difficulties Continue 300
Problems 301
References 301
Chapter 11. Subgroups III: Confirmatory Analyses 303
11.1 Introduction 303
11.2 Focus on Stratum Specific Effects 304
11.3 Confirmatory Analyses Requisites 305
11.4 Incorporating Subgroup Dependency 305
11.4.1 Therapy Homogeneity in Subgroup Evaluations 307
11.5 Subgroup Stratum Specific Endpoints 310
11.5.1 Choosing the Subcohort Endpoints 311
11.5.2 Example 311
11.5.3 Dependency Parameter s Minimal Impact 316
11.6 Differential Event Rate 316
11.6.1 Event Rate Differences 318
11.7 Differential Efficacy 322
11.7.1 The Relationship Between Efficacy and Sample Size 322
11.7.2 Choosing an Efficacy Level 324
11.7.3 Matching Clinical and Statistical Significance 327
11.7.4 Example 328
11.8 The Differential Use of Event Precision 332
11.8.1 Sample Sizes for Continuous Endpoints 332
11.8.2 Cohort Dependent Precision 333
11.9 Conclusions 335
Problems 337
Note 337
References 339
Chapter 12. Multiple Analyses and Multiple Treatment Arms 341
12.1 Introduction and Assumptions 341
12.2 Literature Review 342
12.3 Treatment Versus Treatment 343
12.4 Dose Response Effects 350
12.5 Conclusions 356
References 357
Chapter 13. Combining Multiple Analyses 359
13.1 Introduction 359
13.2 Creating a Multiple Analysis Environment 360
13.3 Composite Endpoints Within Subgroups 363
13.4 Majority Subgroups in Clinical Trials 366
13.5 Atherosclerotic Disease Trial Designs 370
13.6 Multiple Treatment Groups Revisited 375
References 378
Chapter 14. Conclusions: The Two Front War 379
14.1 Compromise and Sampling Error 379
14.2 The Handcuffs 381
References 384
Appendix A. Case Reports and Causality 385
A.I Causality Tenets 387
A.2 Do Case Reports Prove Causality? 390
References 392
Appendix B. Estimation in Random Research 393
B.I Introduction 393
B.2 Dichotomous Clinical Events 394
B.2.1 Event Rate for the Fixed Research Paradigm 394
B.2.2 Event Rates in Random Research 397
B.3 Hypothesis Testing 401
Appendix C. Relevant Code of Federal Regulations 403
C.I Indications for Prescritpion Drugs 403
C.2 Adequate and Well Controlled Trials 404
Appendix D. Sample Size Primer 409
D.I General Discussion of Sample Size 409
D.2 Derivation of Sample Size 412
D.3 Example 414
References 415
Appendix E. Additional Dependent Hypothesis Testing Results 417
E.I Derivation of Dependence for K = 4 417
E.2 Induction Arguments 419
E.3 Additional Recursive Relationships 423
References 429
Index 431
|
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| illustrated | Illustrated |
| indexdate | 2024-07-09T19:58:22Z |
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| isbn | 038700727X |
| language | English |
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| spelling | Moyé, Lemuel A. 1952- Verfasser (DE-588)122260651 aut Multiple analyses in clinical trials fundamentals for investigators Lemuel A. Moyé New York ; Berlin ; Heidelberg ; Hong Kong ; London ; Milan Springer 2003 XXIII, 436 S. graph. Darst. : 24 cm txt rdacontent n rdamedia nc rdacarrier Statistics for biology and health Literaturangaben Analyse multivariée Biologie gtt Geneeskunde gtt Statistische analyse gtt Études cliniques Études cliniques - Méthodes statistiques Medizin Clinical Trials as Topic methods Clinical trials Clinical trials Statistical methods Multivariate Analysis Multivariate analysis Research Design Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Klinisches Experiment (DE-588)4164223-5 gnd rswk-swf Klinisches Experiment (DE-588)4164223-5 s Multivariate Analyse (DE-588)4040708-1 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012819228&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Moyé, Lemuel A. 1952- Multiple analyses in clinical trials fundamentals for investigators Analyse multivariée Biologie gtt Geneeskunde gtt Statistische analyse gtt Études cliniques Études cliniques - Méthodes statistiques Medizin Clinical Trials as Topic methods Clinical trials Clinical trials Statistical methods Multivariate Analysis Multivariate analysis Research Design Multivariate Analyse (DE-588)4040708-1 gnd Klinisches Experiment (DE-588)4164223-5 gnd |
| subject_GND | (DE-588)4040708-1 (DE-588)4164223-5 |
| title | Multiple analyses in clinical trials fundamentals for investigators |
| title_auth | Multiple analyses in clinical trials fundamentals for investigators |
| title_exact_search | Multiple analyses in clinical trials fundamentals for investigators |
| title_full | Multiple analyses in clinical trials fundamentals for investigators Lemuel A. Moyé |
| title_fullStr | Multiple analyses in clinical trials fundamentals for investigators Lemuel A. Moyé |
| title_full_unstemmed | Multiple analyses in clinical trials fundamentals for investigators Lemuel A. Moyé |
| title_short | Multiple analyses in clinical trials |
| title_sort | multiple analyses in clinical trials fundamentals for investigators |
| title_sub | fundamentals for investigators |
| topic | Analyse multivariée Biologie gtt Geneeskunde gtt Statistische analyse gtt Études cliniques Études cliniques - Méthodes statistiques Medizin Clinical Trials as Topic methods Clinical trials Clinical trials Statistical methods Multivariate Analysis Multivariate analysis Research Design Multivariate Analyse (DE-588)4040708-1 gnd Klinisches Experiment (DE-588)4164223-5 gnd |
| topic_facet | Analyse multivariée Biologie Geneeskunde Statistische analyse Études cliniques Études cliniques - Méthodes statistiques Medizin Clinical Trials as Topic methods Clinical trials Clinical trials Statistical methods Multivariate Analysis Multivariate analysis Research Design Multivariate Analyse Klinisches Experiment |
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