Description

Book Synopsis
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 b

    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

Statistical Issues in Drug Development

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    £78.80

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    RRP £82.95 – you save £4.15 (5%)

    Order before 4pm today for delivery by Thu 6 Aug 2026.

    A Hardback by Stephen S. Senn

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      View other formats and editions of Statistical Issues in Drug Development by Stephen S. Senn

      Publisher: John Wiley & Sons Inc
      Publication Date: Publication Date: 24/06/2021
      ISBN13: 9781119238577, 978-1119238577
      ISBN10: 1119238579

      Description

      Book Synopsis
      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 b

        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

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