Statistics in Clinical Vaccine Trials (eBook)

Preface 7
Acknowledgement 11
Contents 13
Acronyms 17
1 Basic Concepts of Vaccine Immunology 19
1.1 Vaccination and Preventing Infectious Diseases 19
1.2 Microorganisms: Bacteria, Yeasts, Protozoa and Viruses 20
1.3 The Immune System 21
1.3.1 Basics 21
1.3.2 Microbial Clearance 22
1.3.3 Active and Passive Protection from Infectious Diseases 23
1.3.4 Antigenic Variation 23
1.3.5 Tumour Immunology 24
1.4 Prevention of Infectious Diseases by Vaccination 24
1.4.1 Viral and Bacterial Vaccines Currently in Use 26
1.4.2 Routes of Administration 28
1.4.3 Malaria Vaccines 29
1.4.4 Experimental Prophylactic and Therapeutic Vaccines 29
2 Humoral and Cellular Immunity 31
2.1 Humoral Immunity 31
2.1.1 Antibody Titres and Antibody Concentrations 32
2.1.2 Two Assays for Humoral Immunity 32
2.2 Cellular Immunity 33
2.2.1 Assays for Cellular Immunity 34
3 Standard Statistical Methods for the Analysis of Immunogenicity Data 36
3.1 Introduction 36
3.2 Geometric Mean Titres and Concentrations 37
3.2.1 Single Vaccine Group 39
3.2.2 Two Vaccine Groups 40
3.3 Geometric Mean Fold Increase 41
3.3.1 Analysis of a Single Geometric Mean Fold Increase 42
3.3.2 Analysis of Two Geometric Mean Fold Increases 42
3.3.3 A Misconception about Fold Increasesand Baseline Imbalance 44
3.4 Two Seroresponse Rates 45
3.4.1 Seroprotection Rate 45
3.4.2 Seroconversion Rate 45
3.5 Analysis of Proportions 46
3.5.1 Analysis of a Single Proportion 46
3.5.1.1 Confidence Intervals for a Single Rate 47
3.5.2 Comparing Two Proportions 50
3.5.3 The Suissa and Shuster Exact Test for Comparing Two Proportions 53
3.6 Multiple Co-Primary Endpoints and the Intersection–Union Test 56
3.7 The Reverse Cumulative Distribution Plot 56
3.8 Discussion 58
3.9 Sample Size Estimation 59
3.9.1 Comparing Two Geometric Mean Responses 59
3.9.2 Comparing Two Proportions 60
3.9.3 Sample Size Estimation for Trialswith Multiple Co-Primary Endpoints 61
4 Antibody Titres and Two Types of Bias 64
4.1 Standard Antibody Titres versus Mid-Value Titres 64
4.2 Censored Antibody Titres and Maximum Likelihood Estimation 66
4.2.1 ML Estimation for Censored Normal Data 67
4.2.2 ML Estimation for Censored Antibody Titres 69
5 Adjusting for Imbalance in Pre-Vaccination State 73
5.1 Imbalance in Pre-Vaccination State 73
5.2 Adjusting for Baseline Imbalance 74
5.3 Analysis of Covariance for Antibody Values 75
5.3.1 A Solution to the Problem of Heteroscedasticity 76
5.3.2 Fitting the Variance Model for Heteroscedasticity 76
5.3.3 ANCOVA for Comparative Clinical Vaccine Trials 78
6 Vaccine Equivalence and Noninferiority Immunogenicity Trials 82
6.1 Equivalence and Noninferiority 82
6.2 Equivalence and Noninferiority Testing 83
6.2.1 Basic Concepts 83
6.2.2 Equivalence and Noninferiority Testing for Normal Data 84
6.2.3 The Confidence Interval Approach to Equivalence and Noninferiority Testing 85
6.3 Equivalence and Noninferiority Vaccine Trials with a Geometric Mean Response as Outcome 85
6.4 Equivalence and Noninferiority Trails with a Seroresponse Rate as Outcome 88
6.5 Vaccine Lot Consistency Trials 89
6.5.1 Lot Consistency and the Confidence Interval Method 89
6.5.2 The Wiens and Iglewicz Test to Inspect the Consistency of Three Vaccine Lots 90
6.6 Discussion 93
6.7 Sample Size Estimation 94
6.7.1 Comparing Two Geometric Mean Responses 94
6.7.2 Comparing Two Seroresponse Rates 97
6.7.3 Lot Consistency Trials 97
7 Vaccine Field Efficacy Trials 100
7.1 Introduction 100
7.2 Some Critical Aspects of Vaccine Field Trials 101
7.2.1 Efficacy versus Effectiveness 101
7.2.2 The Influence of the Sensitivity and Specificity of the Diagnostic Test on the Vaccine Efficacy Estimate 102
7.2.3 Surveillance Period 105
7.3 Incidence Measures for Infection 105
7.3.1 Attack Rate 105
7.3.2 Infection Rate 106
7.3.3 Force of Infection 107
7.4 Statistical Analysis of Vaccine Efficacy Data 108
7.4.1 Comparing Two Attack Rates 109
7.4.2 Comparing Two Infection Rates 110
7.4.3 Comparing Two Force of Infection Functions 112
7.5 Recurrent Infections 114
7.5.1 Average Number of Episodes Experienced by a Subject 114
7.5.1.1 Time to a Next Episode 118
7.6 Sample Size Estimation 118
7.6.1 Trials Comparing Two Attack Rates 118
7.6.2 Trials Comparing Two Infection Rates 120
7.6.3 Trials Comparing Two Forces of Infection 121
8 Correlates of Protection 122
8.1 Introduction 122
8.2 The Protection Curve 123
8.3 Estimating the Protection Curve 123
8.3.1 Estimating the Protection Curve from Challenge 
123 
8.3.2 Estimating a Protection Curve from Vaccine FieldEfficacy Study Data 126
8.3.3 Predicting Vaccine Efficacy 128
8.4 Threshold of Protection 128
8.5 Discussion 130
9 Safety of Vaccines 132
9.1 Ensuring Vaccine Safety 132
9.2 Vaccine Safety Surveillance 133
9.3 Safety Data and the Problem of Multiplicity 135
9.4 Vaccine Reactogenicity 139
9.4.1 Local and Systemic Reactions 139
9.4.2 Statistical Analysis of Local and Systemic Reactions 140
9.4.2.1 Analyzing Incidences of Local and Systemic Reactions 140
9.4.2.2 Analyzing the Severity of Local and Systemic Reactions 142
A SAS and Floating Point Format for Calculated Variables 145
B Closed-Form Solutions for the Constrained 
147 
C Simulation Results on Jewell's Correctionfor the Rate Ratio 148
D Proof of Inequality (3.16) 
149 
E A Generalized Worst-Case Sensitivity Analysis for a Single Seroresponse Rate for Which the Confidence Interval Must Fall Above a Pre-Specified Bound 150
E.1 Introduction 150
E.2 Motivating Example 151
E.3 Complete-Case and Worst-Case Maximum Likelihood Analyses 151
E.4 Maximum Likelihood Analysis with Missing Data 153
E.5 Generalized Sensitivity Analysis 153
E.6 Concluding Remarks 154
E.7 Technical Notes 155
References 156
Index 160