Statistical Issues in Drug Development The revised third edition of Statistical Issues in Drug Development delivers an insightful treatment of the intersection between statistics and the life sciences. The book offers readers new discussions of crucial topics, including cluster randomization, historical controls, responder analysis, studies in children, post-hoc tests, estimands, publication bias, the replication crisis, and many more.
This work presents the major statistical issues in drug development in a way that is accessible and comprehensible to life scientists working in the field, and takes pains not to gloss over significant disagreements in the field of statistics, while encouraging communication between the statistical and life sciences disciplines. In addition to new material on topics like invalid inversion, severity, random effects in network meta-analysis, and explained variation, readers will benefit from the inclusion of:
- A thorough introduction to basic topics in drug development and statistics, including the role played by statistics in drug development
- An exploration of the four views of statistics in drug development, including the historical, methodological, technical, and professional
- An examination of debatable and controversial topics in drug development, including the allocation of treatments to patients in clinical trials, baselines and covariate information, and the measurement of treatment effects
Perfect for life scientists and other professionals working in the field of drug development, Statistical Issues in Drug Development is the ideal resource for anyone seeking a one-stop reference to enhance their understanding of the use of statistics during drug development.
Table of Contents:
Preface to the Third Edition
Preface to the Second Edition xiii
Preface to the First Edition xvii
Acknowledgements xxi
1 Introduction 1
1.1 Drug development 1
1.2 The role of statistics in drug development 2
1.3 The object of this book 3
1.4 The author’s knowledge of statistics in drug development 4
1.5 The reader and his or her knowledge of statistics 4
1.6 How to use the book 5
References 6
Part 1 Four Views of Statistics in Drug Development: Historical, Methodological, Technical and Professional 9
2 A Brief and Superficial History of Statistics for Drug Developers 11
2.1 Introduction 11
2.2 Early Probabilists 12
2.3 James Bernoulli (1654–1705) 13
2.4 John Arbuthnott (1667–1753) 14
2.5 The mathematics of probability in the late 17th, the 18th and early 19th centuries 14
2.6 Thomas Bayes (1701–1761) 15
2.7 Adolphe Quetelet (1796–1874) 16
2.8 George Biddell Airy (1801-1892)
2.9 Francis Galton (1822–1911) 16
2.10 Karl Pearson (1857–1936) 17
2.11 ‘Student’ (1876–1937) 17
2.12 R.A. Fisher (1890–1962) 17
2.13 Modern mathematical statistics 18
2.14 Medical statistics 19
2.15 Statistics in clinical trials today 20
2.16 The current debate 21
2.17 A living science 21
2.18 Further reading 23
References 23
3 Design and Interpretation of Clinical Trials as Seen by a Statistician 27
3.1 Prefatory warning 27
3.2 Introduction 27
3.3 Defining effects 28
3.4 Practical problems in using the counterfactual argument 28
3.5 Regression to the mean 29
3.6 Control in clinical trials 33
3.7 Randomization 34
3.8 Blinding 36
3.9 Using concomitant observations 37
3.10 Measuring treatment effects 38
3.11 Data generation models 39
3.12 In conclusion 41
3.13 Further reading 41
References 41
4 Probability, Bayes, P-values, Tests of Hypotheses and Confidence Intervals 43
4.1 Introduction 43
4.2 An example 44
4.3 Odds and sods 44
4.4 The Bayesian solution to the example 45
4.5 Why don’t we regularly use the Bayesian approach in clinical trials? 46
4.6 A frequentist approach 47
4.7 Hypothesis testing in controlled clinical trials 48
4.8 Significance tests and P-values 49
4.9 Confidence intervals and limits and credible intervals 50
4.10 Some Bayesian criticism of the frequentist approach 51
4.11 Decision theory 51
4.12 Conclusion 52
4.13 Further reading 52
References 53
5 The Work of the Pharmaceutical Statistician 55
5.1 Prefatory remarks 55
5.2 Introduction 56
5.3 In the beginning 57
5.4 The trial protocol 57
5.5 The statistician’s role in planning the protocol 58
5.6 Sample size determination 59
5.7 Other important design issues 60
5.8 Randomization 60
5.9 Data collection preview 61
5.10 Performing the trial 61
5.11 Data analysis preview 61
5.12 Analysis and reporting 62
5.13 Other activities 63
5.14 Statistical research 63
5.15 Further reading 64
References 65
Part 2 Statistical Issues: Debatable and Controversial Topics in Drug Development 67
6 Allocating Treatments to Patients in Clinical Trials 69
6.1 Background 69
6.2 Issues 71
References 87
6.A Technical appendix 88
7 Baselines and Covariate Information 95
7.1 Background 95
7.2 Issues 98
References 108
7.A Technical appendix 109
8 The Measurement of Treatment Effects 113
8.1 Background 113
8.2 Issues 114
References 129
8.A Technical appendix 130
9 Demographic Subgroups: Representation and Analysis 133
9.1 Background 133
9.2 Issues 134
References 144
9.A Technical appendix 145
10 Multiplicity 149
10.1 Background 149
10.2 Issues 150
References 161
10.A Technical appendix 162
11 Intention to Treat, Missing Data and Related Matters 165
11.1 Background 165
11.2 Issues 167
References 178
11.A Technical appendix 180
12 One-sided and Two-sided Tests and other Issues to Do with Significance and P-values 183
12.1 Background 183
12.2 Issues 184
References 192
13 Determining the Sample Size 195
13.1 Background 195
13.2 Issues 198
References 211
14 Multicentre Trials 213
14.1 Background 213
14.2 Issues 213
References 230
14.A Technical appendix 231
15 Active Control Equivalence Studies 235
15.1 Background 235
15.2 Issues 237
References 247
15.A Technical appendix 249
16 Meta-Analysis 251
16.1 Background 251
16.2 Issues 253
References 268
16.A Technical appendix 270
17 Cross-over Trials 273
17.1 Background 273
17.2 Issues 275
References 284
18 n-of-1 Trials 287
18.1 Background 287
18.2 Issues 289
References 293
19 Sequential Trials 295
19.1 Background 295
19.2 Issues 302
References 313
20 Dose-finding 317
20.1 Background 317
20.2 Issues 319
References 334
21 Concerning Pharmacokinetics and Pharmacodynamics 337
21.1 Background 337
21.2 Issues 343
References 358
22 Bioequivalence Studies 361
22.1 Background 361
22.2 Issues 362
References 379
23 Safety Data, Harms, Drug Monitoring and Pharmaco-epidemiology 383
23.1 Background 383
23.2 Issues 388
References 403
24 Pharmaco-economics and Portfolio Management 405
24.1 Background 405
24.2 Issues 407
References 429
25 Concerning Pharmacogenetics, Pharmacogenomics and Related Matters 433
25.1 Background 433
25.2 Issues 437
References 450
25.A Technical appendix 451
Glossary 453
Index 483
About the Author :
Professor Stephen Senn (MSc, PhD, CStat) is a statistical consultant, researcher and blogger. He has extensive experience in both academia and industry, and is recognized worldwide for his studies in statistical methodology applied to drug development.
Professor Senn has been the recipient of national and international awards, including the 1st George C Challis award for Biostatistics at the University of Florida, and the Bradford Hill Medal of the Royal Statistical Society. He is a Fellow of the Royal Society of Edinburgh and an honorary life member of Statisticians in the Pharmaceutical Industry (PSI) and the International Society for Clinical Biostatistics (ISCB) and has honorary professorships in statistics at The University of Sheffield and the University of Edinburgh.
