临床试验统计学：第4版

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"《统计学在临床试验中的应用》第四版是一本专注于统计分析在临床试验中最相关方面的书籍。它旨在为学生、医生和研究人员提供更全面的指南和参考文本，同时保持前两版实用的统计问题解决方法。本书适用于设计和分析临床数据的研究者，并用于编写最终报告。" 《统计学在临床试验中的应用》第四版是作者TON J. CLEOPHAS、AEILKO H. ZWINDERMAN、TOINE F. CLEOPHAS和EUGENE P. CLEOPHAS合作的成果，他们分别在统计学、临床药理学、生物统计学和流行病学等领域具有深厚的专业背景。本书延续了前两版的实用风格，但内容更加丰富，以满足读者更广泛的需求。临床试验是评估新药物或治疗方法安全性和有效性的关键步骤，而统计学在其中扮演着至关重要的角色。本书深入浅出地介绍了如何运用统计学方法来设计试验、收集数据、分析结果并解释这些结果对临床决策的影响。内容可能涵盖以下关键知识点： 1. **试验设计**：包括随机化、对照组的选择、样本量的确定、分层抽样等，这些都是确保试验结果可靠性和可比性的重要因素。 2. **数据收集与管理**：讨论了如何有效地记录和管理临床试验数据，以及数据质量控制的重要性。 3. **统计分析方法**：涵盖了描述性统计（如均值、中位数、标准差）、推断性统计（如假设检验、置信区间、p值）、回归分析、生存分析等，这些都是临床试验数据分析的基础。 4. **疗效评估**：介绍如何通过统计方法评估治疗效果，如风险比、优势比、风险差异等指标。 5. **偏差和偏倚控制**：探讨如何识别和控制潜在的试验偏差，以提高研究的可信度。 6. **报告撰写**：指导如何将统计分析的结果清晰、准确地体现在临床试验报告中，以便同行评审和监管机构理解。 7. **伦理考虑**：强调了临床试验中的伦理原则，如知情同意、保护受试者权益等。 8. **统计软件的应用**：可能包含如何使用R、SAS、SPSS等统计软件进行数据分析的实际操作指导。通过学习本书，读者不仅能掌握统计学的基本原理，还能学会如何将这些原理应用于实际的临床试验中，从而提高研究质量和效率。对于从事医药研究、临床医生和统计分析师来说，这是一本非常有价值的参考资料。

TABLE OF CONTENTS

xvi

9. Limitations of statistics 533

10. Conclusions 534

11. References 535

CHAPTER 47 / BIAS DUE TO CONFLICTS OF INTERESTS, SOME

GUIDELINES

1. Introduction 537

2. The randomized controlled clinical trial as the gold standard 537

3. Need for circumspection recognized 538

4. The expanding commend of the pharmaceutical industry over clinical trials 538

5. Flawed procedures jeopardizing current clinical trials 539

6. The good news 540

7. Further solutions to the dilemma between sponsored research and the 540

independence of science

8. Conclusions 542

9. References 542

APPENDIX 545

INDEX 553

xvii

The European Interuniversity Diploma of Pharmaceutical Medicine is a

postacademic course of 2-3 years sponsored by the Socrates program of the

European Community. The office of this interuniversity project is in Lyon and the

lectures are given there. The European Community has provided a building and will

remunerate lecturers. The institute which provides the teaching is called the

European College of Pharmaceutical Medicine, and is affiliated with 15 universities

throughout Europe, whose representatives constitute the academic committee. This

committee supervises educational objectives. Start lectures February 2000.

There are about 20 modules for the first two years of training, most of which are

concerned with typically pharmacological and clinical pharmacological matters

including pharmacokinetics, pharmacodynamics, phase III clinical trials, reporting,

communication, ethics and, any other aspects of drug development. Subsequent

training consists of practice training within clinical research organisations,

universities, regulatory bodies etc., and finally of a dissertation. The diploma, and

degree are delivered by the Claude Bernard University in Lyon as well as the other

participating universities.

The module “Statistics applied to clinical trials” will be taught in the form of a 3 to

6 day yearly course given in Lyon and starting February 2000. Lecturers have to

submit a document of the course (this material will be made available to students).

Three or 4 lecturers are requested to prepare detailed written material for students

as well as to prepare examination of the students. The module is thus an important

part of a postgraduate course for physicians and pharmacists for the purpose of

obtaining the European diploma of pharmaceutical medicine. The diploma should

make for leading positions in pharmaceutical industry, academic drug research, as

well as regulatory bodies within the EC. This module is mainly involved in the

statistics of randomized clinical trials.

The chapters 1-9, 11, 17, 18 of this book are based on the module “Medical

statistics applied to clinical trials” and contain material that should be mastered by

the students before their exams. The remaining chapters are capita selecta intended

for excellent students and are not included in the exams.

The authors believe that this book is innovative in the statistical literature because,

unlike most introductory books in medical statistics, it provides an explanatory

rather than mathematical approach to statistics, and, in addition, emphasizes non-

classical but increasingly frequently used methods for the statistical analyses of

clinical trials, e.g., equivalence testing, sequential analyses, multiple linear

regression analyses for confounding, interaction, and synergism. The authors are

not aware of any other work published so far that is comparable with the current

work, and, therefore, believe that it does fill a need.

August 1999

Dordrecht, Leiden , Delft

PREFACE TO FIRST EDITION

xviii PREFACES

PREFACE TO SECOND EDITION

In this second edition the authors have removed textual errors from the first edition.

Also seven new chapters (chapters 8, 10, 13, 15-18) have been added. The

principles of regression analysis and its resemblance to analysis of variance was

missing in the first edition, and have been described in chapter 8. Chapter 10

assesses curvilinear regression. Chapter 13 describes the statistical analyses of

crossover data with binary response. The latest developments including statistical

analyses of genetic data and quality-of-life data have been described in chapters 15

and 16. Emphasis is given in chapters 17 and 18 to the limitations of statistics to

assess non-normal data, and to the similarities between commonly-used statistical

tests. Finally, additional tables including the Mann-Whitney and Wilcoxon rank

sum tables have been added in the Appendix.

December 2001, Dordrecht, Amsterdam, Delft

PREFACE TO THE THIRD EDITION

The previous two editions of this book, rather than having been comprehensive,

concentrated on the most relevant aspects of statistical analysis. Although well-

received by students, clinicians, and researchers, these editions did not answer all of

their questions. This called for a third, more comprehensive, rewrite. In this third

edition the 18 chapters from the previous edition have been revised, updated, and

provided with a conclusions section summarizing the main points. The formulas

have been re-edited using the Formula-Editor from Windows XP 2004 for enhanced

clarity. Thirteen new chapters (chapters 8-10, 14,15, 17, 21, 25-29, 31) have been

added. The chapters 8-10 give methods to assess the problems of multiple testing

and data testing closer to expectation than compatible with random. The chapters 14

and 15 review regression models using an exponential rather than linear

relationship including logistic, Cox, and Markow models. Chapter 17 reviews

important interaction effects in clinical trials and provides methods for their

analysis. In chapter 21 study designs appropriate for medicines from one class are

discussed. The chapters 25-29 review respectively (1) methods to evaluate the

presence of randomness in the data, (2) methods to assess variabilities in the data,

(3) methods to test reproducibility in the data, (4) methods to assess accuracy of

diagnostic tests, and (5) methods to assess random rather than fixed treatment

effects. Finally, chapter 31 reviews methods to minimize the dilemma between

sponsored research and scientific independence. This updated and extended edition

has been written to serve as a more complete guide and reference-text to students,

physicians, and investigators, and, at the same time, preserves the common sense

approach to statistical problem-solving of the previous editions.

August 2005, Dordrecht, Amsterdam, Delft

xxi

In clinical medicine appropriate statistics has become indispensable to evaluate

treatment effects. Randomized controlled trials are currently the only trials that

truly provide evidence-based medicine. Evidence based medicine has become

crucial to optimal treatment of patients. We can define randomized controlled trials

by using Christopher J. Bulpitt’s definition “a carefully and ethically designed

experiment which includes the provision of adequate and appropriate controls by a

process of randomization, so that precisely framed questions can be answered”. The

answers given by randomized controlled trials constitute at present the way how

patients should be clinically managed. In the setup of such randomized trial one of

the most important issues is the statistical basis. The randomized trial will never

work when the statistical grounds and analyses have not been clearly defined

beforehand. All endpoints should be clearly defined in order to perform appropriate

power calculations. Based on these power calculations the exact number of

available patients can be calculated in order to have a sufficient quantity of

individuals to have the predefined questions answered. Therefore, every clinical

physician should be capable to understand the statistical basis of well performed

clinical trials. It is therefore a great pleasure that Drs. T.J. Cleophas, A.H.

Zwinderman, and T.F. Cleophas have published a book on statistical analysis of

clinical trials. The book entitled “Statistics Applied to Clinical Trials” is clearly

written and makes complex issues in statistical analysis transparant. Apart from

providing the classical issues in statistical analysis, the authors also address novel

issues such as interim analyses, sequential analyses, and meta-analyses. The book is

composed of 18 chapters, which are nicely structured. The authors have deepened

our insight in the applications of statistical analysis of clinical trials. We would like

to congratulate the editors on this achievement and hope that many readers will

enjoy reading this intriguing book.

E.E. van der Wall, MD, PhD, Professor of Cardiology, President Netherlands

Association of Cardiology, Leiden, The Netherlands

FOREWORD

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