statistical issues in drug development - buch.de · in a particular practical field within each...

Statistical Issues in DrugDevelopment

Second Edition

Stephen Senn

Department of StatisticsUniversity of Glasgow, UK

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Statistical Issuesin Drug Development

Statistics in Practice

Advisory Editor

Stephen SennUniversity of Glasgow, UK

Founding Editor

Vic BarnettNottingham Trent University, UK

Statistics in Practice is an important international series of texts which provide detailedcoverage of statistical concepts, methods and worked case studies in specific fields ofinvestigation and study.

With sound motivation and many worked practical examples, the books show indown-to-earth terms how to select and use an appropriate range of statistical techniquesin a particular practical field within each title’s special topic area.

The books provide statistical support for professionals and research workers across arange of employment fields and research environments. Subject areas covered includemedicine and pharmaceutics; industry, finance and commerce; public services; the earthand environmental sciences, and so on.

The books also provide support to students studying statistical courses applied to theabove areas. The demand for graduates to be equipped for the work environment hasled to such courses becoming increasingly prevalent at universities and colleges.

It is our aim to present judiciously chosen and well-written workbooks to meeteveryday practical needs. Feedback of views from readers will be most valuable tomonitor the success of this aim.

A complete list of titles in this series appears at the end of the volume.

Statistical Issues in DrugDevelopment

Second Edition

Stephen Senn

Department of StatisticsUniversity of Glasgow, UK

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Contents

Preface to the Second Edition xiii

Preface to the First Edition xvii

Acknowledgements xxi

1 Introduction 11.1 Drug development 11.2 The role of statistics in drug development 21.3 The object of this book 31.4 The author’s knowledge of statistics in drug development 41.5 The reader and his or her knowledge of statistics 41.6 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 112.1 Introduction 112.2 Early Probabilists 122.3 James Bernoulli (1654–1705) 132.4 John Arbuthnott (1667–1753) 142.5 The mathematics of probability in the late 17th, the 18th and early

19th centuries 142.6 Thomas Bayes (1701–1761) 152.7 Adolphe Quetelet (1796–1874) 162.8 Francis Galton (1822–1911) 162.9 Karl Pearson (1857–1936) 172.10 ‘Student’ (1876–1937) 172.11 R.A. Fisher (1890–1962) 172.12 Modern mathematical statistics 182.13 Medical statistics 192.14 Statistics in clinical trials today 202.15 The current debate 212.16 A living science 212.17 Further reading 23

References 23

viii Contents

3 Design and Interpretation of Clinical Trials as Seen by a Statistician 273.1 Prefatory warning 273.2 Introduction 273.3 Defining effects 283.4 Practical problems in using the counterfactual argument 283.5 Regression to the mean 293.6 Control in clinical trials 333.7 Randomization 343.8 Blinding 363.9 Using concomitant observations 373.10 Measuring treatment effects 383.11 Data generation models 393.12 In conclusion 413.13 Further reading 41

References 41

4 Probability, Bayes, P-values, Tests of Hypotheses and ConfidenceIntervals 434.1 Introduction 434.2 An example 444.3 Odds and sods 444.4 The Bayesian solution to the example 454.5 Why don’t we regularly use the Bayesian approach in

clinical trials? 464.6 A frequentist approach 474.7 Hypothesis testing in controlled clinical trials 484.8 Significance tests and P-values 494.9 Confidence intervals and limits and credible intervals 504.10 Some Bayesian criticism of the frequentist approach 514.11 Decision theory 514.12 Conclusion 524.13 Further reading 52

References 53

5 The Work of the Pharmaceutical Statistician 555.1 Prefatory remarks 555.2 Introduction 565.3 In the beginning 575.4 The trial protocol 575.5 The statistician’s role in planning the protocol 585.6 Sample size determination 595.7 Other important design issues 605.8 Randomization 605.9 Data collection preview 615.10 Performing the trial 615.11 Data analysis preview 615.12 Analysis and reporting 625.13 Other activities 63

Contents ix

5.14 Statistical research 635.15 Further reading 64

References 65

Part 2 Statistical Issues: Debatable and Controversial Topics inDrug Development 67

6 Allocating Treatments to Patients in Clinical Trials 696.1 Background 696.2 Issues 71

References 876.A Technical appendix 88

7 Baselines and Covariate Information 957.1 Background 957.2 Issues 98


8 The Measurement of Treatment Effects 1138.1 Background 1138.2 Issues 114


9 Demographic Subgroups: Representation and Analysis 1339.1 Background 1339.2 Issues 134


10 Multiplicity 14910.1 Background 14910.2 Issues 150


11 Intention to Treat, Missing Data and Related Matters 16511.1 Background 16511.2 Issues 167


12 One-sided and Two-sided Tests and other Issues to Do withSignificance and P-values 18312.1 Background 18312.2 Issues 184

References 192

x Contents

13 Determining the Sample Size 19513.1 Background 19513.2 Issues 198

References 211

14 Multicentre Trials 21314.1 Background 21314.2 Issues 213


15 Active Control Equivalence Studies 23515.1 Background 23515.2 Issues 237


16 Meta-Analysis 25116.1 Background 25116.2 Issues 253


17 Cross-over Trials 27317.1 Background 27317.2 Issues 275

References 284

18 n-of-1 Trials 28718.1 Background 28718.2 Issues 289

References 293

19 Sequential Trials 29519.1 Background 29519.2 Issues 302

References 313

20 Dose-finding 31720.1 Background 31720.2 Issues 319

References 334

21 Concerning Pharmacokinetics and Pharmacodynamics 33721.1 Background 33721.2 Issues 343

References 358

Contents xi

22 Bioequivalence Studies 36122.1 Background 36122.2 Issues 362

References 379

23 Safety Data, Harms, Drug Monitoring and Pharmaco-epidemiology 38323.1 Background 38323.2 Issues 388

References 403

24 Pharmaco-economics and Portfolio Management 40524.1 Background 40524.2 Issues 407

References 429

25 Concerning Pharmacogenetics, Pharmacogenomics and RelatedMatters 43325.1 Background 43325.2 Issues 437


Glossary 453

Index 483

Preface to the Second Edition

There have been many developments since the first edition of this book and it washigh time for a second. My own period working in the pharmaceutical industry is nowa distant memory but the ten years working as an academic since the first editionhas had its compensations. I have been fortunate enough to be able to consult formany pharmaceutical companies during this time and this has certainly widened myappreciation of the work that statisticians do within the industry and the problemsthey face.

Alas, this appreciation is not shared by all. Many take it as almost axiomatic thatstatistical analysis carried out within the pharmaceutical industry is necessarily inferiorto that carried out elsewhere. Indeed, one medical journal has even gone so far as tomake it a requirement for publication that analyses from the pharmaceutical industryshould be confirmed by an academic statistician, a policy which is as impractical as itis illogical.

Two related developments since the first edition, one of which is personal, are highlyrelevant. The first is that I have been honoured to succeed Vic Barnett as an editor forWiley’s Statistics in Practice series, in which this book appears. The second is that theseries itself, so ably founded by Vic and Helen Ramsey, has been growing steadily andsince the first edition now has attracted a number of further volumes that are highlyrelevant to this one. The chapters that have particularly benefited are listed with therelevant references as follows.

Chapter 6 Allocating treatments to patients in clinical trials (Berger, 2005)Chapter 7 Baselines and covariate information (Berger, 2005)Chapter 11 Intention to treat, missing data and related matters (Molenberghs

and Kenward, 2007)Chapter 16 Meta-analysis (Whitehead, 2002)Chapter 19 Sequential trials (Ellenberg, et al., 2003)Chapter 20 Dose-finding (Chevret, 2006)Chapter 22 Bioequivalence studies (Hauschke, et al., 2007)Chapter 23 Safety data, harms, drug-monitoring and pharmacoepidemiology

(Lui, 2004)Chapter 24 Pharmacoeconomics and portfolio management (Parmigiani,

2002, Willan and Briggs, 2006)

Also extremely useful are two books on Bayesian methods (O’Hagan et al., 2006,Spiegelhalter et al., 2003) and Brown and Prescott’s book on mixed models (Brown andPrescott, 2006), which is already in a second edition. The books on survival analysis and

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