The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research. Statistical Analysis of Cost-Effectiveness Data provides a practical book that synthesises the huge amount of research that has taken place in the area over the last two decades. Comprising an up-to-date overview of the statistical analysis of cost-effectiveness data, the book is supported by numerous worked examples from the author's own experience. It has been written in a style suitable for medical statisticians and health care professionals alike. Key features include: an overview of statistical methods used in the analysis of cost-effectiveness data. coverage of Bayesian methodology. illustrated throughout by worked examples using real data. suitability for health care professionals with limited statistical knowledge. discussion of software used for data analysis. An essential reference for biostatisticians and health economists engaged in cost-effectiveness analysis of health-care interventions, both in academia and industry. Also of interest to graduate students of biostatistics, public health and economics.

Dr.Andrew R. Willan is an academic biostatistician and clinical trial methodologist, and currently holds the positions of Senior Scientist Emeritus at SickKids Research Institute, Professor of Biostatistics in the Dalla Lana School of Public Health at the University of Toronto, and Professor Emeritus in the Department of Clinical Epidemiology and Biostatistics at McMaster University. His contributions to statistical methodology include publications in the areas of cost-effectiveness analysis, value of information methods, management trials, crossover trials, non-nested regression analysis and bivariate response models. Dr. Willan has been particularly instrumental in developing the field of statistical analysis of cost-effectiveness data with twenty peer-review articles and a book, co-authored with Professor Andy Briggs, in the Wiley Statistics in Practice series, entitled Statistical Analysis of Cost-effectiveness Data.

Preface

xi

1 Concepts

1

(10)

1.1 Introduction

1

(1)

1.2 Cost-effectiveness data and the parameters of interest

2

(3)

1.3 The cost-effectiveness plane, the ICER and INB

5

(3)

1.4 Outline

8

(3)

2 Parameter Estimation for Non-censored Data

11

(16)

2.1 Introduction

11

(1)

2.2 Cost

12

(8)

2.2.1 Sample means for estimating incremental cost

12

(2)

2.2.2 Using multiple regression models

14

(1)

2.2.3 Transformation (and the retransformation problem)

15

(2)

2.2.4 Generalized linear models

17

(1)

2.2.5 Two-part models for excess zeros

18

(1)

2.2.6 Cost prediction models

19

(1)

2.3 Effectiveness

20

(5)

2.3.1 Probability of surviving

21

(1)

2.3.2 Mean survival time

21

(1)

2.3.3 Mean quality-adjusted survival time

22

(2)

2.3.4 Mean quality-adjusted survival: controlling for baseline utility

24

(1)

2.4 Summary

25

(2)

3 Parameter Estimation for Censored Data

27

(16)

3.1 Introduction

27

(1)

3.2 Mean Cost

28

(6)

3.2.1 Direct (Lin) method

29

(2)

3.2.2 Inverse-probability weighting

31

(3)

3.3 Effectiveness

34

(8)

3.3.1 Probability of surviving

34

(2)

3.3.2 Mean survival time

36

(3)

3.3.3 Mean quality-adjusted survival time

39

(3)

3.4 Summary

42

(1)

4 Cost-effectiveness Analysis

43

(24)

4.1 Introduction

43

(1)

4.2 Incremental cost-effectiveness ratio

44

(5)

4.3 Incremental net benefit

49

(2)

4.4 The cost-effectiveness acceptability curve

51

(3)

4.5 Using bootstrap methods

54

(3)

4.6 A Bayesian incremental net benefit approach

57

(3)

4.7 Kinked thresholds

60

(4)

4.8 Summary

64

(3)

5 Cost-effectiveness Analysis: Examples

67

(26)

5.1 Introduction

67

(1)

5.2 The CADET-Hp trial

67

(5)

5.3 Symptomatic hormone-resistant prostate cancer

72

(5)

5.4 The Canadian implantable defibrillator study (CMS)

77

(5)

5.5 The EVALUATE trial

82

(4)

5.6 Bayesian approach applied to the UK PDS study

86

(4)

5.7 Summary

90

(3)

6 Power and Sample Size Determination

93

(24)

6.1 Introduction

93

(1)

6.2 Approaches based on the cost-effectiveness plane

94

(9)

6.2.1 Briggs and Gray

95

(3)

6.2.2 Willan and O'Brien

98

(3)

6.2.3 Gardiner et al.

101

(2)

6.3 The classical approach based on net benefit

103

(3)

6.3.1 The method

103

(2)

6.3.2 Example

105

(1)

6.4 Bayesian take on the classical approach

106

(2)

6.4.1 The Method

106

(1)

6.4.2 Example

107

(1)

6.5 The value of information approach

108

(8)

6.5.1 The method

108

(6)

6.5.2 Example

114

(2)

6.6 Summary

116

(1)

7 Covariate Adjustment and Sub-group Analysis

117

(28)

7.1 Introduction

117

(1)

7.2 Non-censored data

118

(11)

7.2.1 Example, non-censored data

121

(8)

7.3 Censored data

129

(13)

7.3.1 Cost

131

(1)

7.3.2 Quality-adjusted survival time

132

(2)

7.3.3 Survival time

134

(1)

7.3.4 The Canadian implantable defibrillator study (CIDS)

135

(3)

7.3.5 The evaluate trial

138

(4)

7.4 Summary

142

(3)

8 Multicenter and Multinational Trials

145

(20)

8.1 Introduction

145

(2)

8.2 Background to multinational cost-effectiveness

147

(4)

8.3 Fixed effect approaches

151

(3)

8.3.1 Willke et al.

151

(1)

8.3.2 Cook et al.

152

(2)

8.4 Random effects approaches

154

(10)

8.4.1 Aggregate level analysis: multicenter trials

154

(2)

8.4.2 Aggregate level analysis: multinational trials

156

(6)

8.4.3 Hierarchical modeling

162

(2)

8.5 Summary

164

(1)

9 Modeling Cost-effectiveness

165

(18)

9.1 Introduction

165

(1)

9.2 A general framework for modeling cost-effectiveness results

166

(1)

9.3 Case study: an economic appraisal of the goal study

167

(13)

9.3.1 The GOAL study

168

(2)

9.3.2 Standard approach to estimating cost-effectiveness

170

(1)

9.3.3 An alternative approach to estimating cost-effectiveness

171

(8)

9.3.4 Comparing the two analyses of GOAL

179

(1)

9.4 Summary

180

(3)

References

183

(10)

Author Index

193

(2)

Subject Index

195

(2)

Series List

197

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Statistical Analysis of Cost-effectiveness Data

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