Interpreting epidemiologic evidence: connecting research to applications

241 Pages·2016·1.94 MB·English

by  Gregory A, David A., Savitz, Wellenius

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Interpreting Epidemiologic
Evidence
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Interpreting Epidemiologic
Evidence
Connecting Research to Applications
Second Edition
David A. Savitz
and
Gregory A. Wellenius
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First Edition published in 2003
Second Edition published in 2016
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Library of Congress Cataloging- i n-P ublication Data
Names: Savitz, David A., author. | Wellenius, Gregory A., author.
Title: Interpreting epidemiologic evidence : connecting research to applications /
David A. Savitz and Gregory A. Wellenius.
Description: 2nd edition. | Oxford ; New York : Oxford University Press, [2016]
Identifers: LCCN 2016002798 (print) | LCCN 2016003547 (ebook) | ISBN 9780190243777
(pbk. : alk. paper) | ISBN 9780190243784 (ebook) | ISBN 9780190243791 (ebook)
Subjects: | MESH: Epidemiologic Research Design | Bias (Epidemiology)
Classifcation: LCC RA652.4 (print) | LCC RA652.4 (ebook) | NLM WA 950 | DDC 614.4—dc23
LC record available at http://lccn.loc.gov/2016002798
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Contents

Preface xi

1. Introduction 1

Synopsis 1

Learning Objectives 1

Perspective 1

Approach to the Evaluation of Evidence 3

Organization of Book 4

2. Te Nature of Epidemiologic Evidence 7

Synopsis 7

Learning Objectives 7

Goals of Epidemiologic Research 7

Measurement of Causal Relations Between Exposure and Disease 11

Applications of Epidemiologic Research 14

Framework for Examining Epidemiologic Evidence 15

Relationship of Epidemiology to Health Policy 16

Exercise: Critical Assessment of Study Methods, Results, and Applications 19

3. Causal Diagrams for Epidemiologic Inference 21

Synopsis 21

Learning Objectives 21

Introduction 21

Causal Diagrams in Epidemiology 23

Purpose and Terminology 23

Directed Acyclic Graphs Encode Our Assumptions 24

Statistical Associations 26

Connection to Data Analyses 30

Depicting Passage of Time 32

Direct Versus Indirect Efects 32

Concluding Toughts 33

Recommended Additional Readings 33

Exercise: Application of Causal Diagrams for Epidemiologic Inference 34
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4. Strategy for Drawing Inferences from Epidemiologic Evidence 35

Synopsis 35

Learning Objectives 35

Conceptual Framework for the Evaluation of Error 35

Estimation of Measures of Association 37

Systematic Evaluation of Sources of Error 38

Objective Evaluation of Sources of Error 39

Identifying the Most Important Sources of Error 40

Specifying Bias Scenarios 42

Exercise: Specifying Scenarios of Bias 44

5. Confounding I: Teoretical Considerations 45

Synopsis 45

Learning Objectives 45

Defnition 46

Identifying Potential Confounders 47

Traditional Approach to Assessing Confounding 48

Modern Approach to Assessing Confounding 49

Inappropriate Adjustments 51

Assessing the Direction and Magnitude of Potential Confounding 53

Methods of Controlling Confounding 56

Randomization 57

Selection of Study Setting Free of Confounding 57

Restrict Study Groups to Enhance Comparability 58

Statistical Adjustment for Confounding 59

Recommended Additional Readings 60

Exercise: Conceptual Basis of Confounding 61

6. Confounding II: Practical Considerations 63

Synopsis 63

Learning Objectives 63

Evaluating the Presence and Impact of Confounding 64

Specifying Scenarios of Confounding 64

Assessing Whether Confounding Is Present 65

Consider Potential for Complete Confounding 65

Assess Consequences of Inaccurate Confounder Measurement 66

Applying Knowledge of Confounding Based on Other Studies 68

Assessing Confounding When Risk Factors are Unknown 70

Dose-R esponse Gradients and Potential for Confounding 71

Integrated Assessment of Potential Confounding 72

Exercise: Connecting Conceptual and Statistical Assessment of Confounding 74
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7. Selection Bias and Confounding Resulting from Selection in Cohort Studies 77

Synopsis 77

Learning Objectives 77

Study Designs 78

Defnition and Examples of Selection Bias 78

Selection Bias Versus Confounding 80

Evaluation of Bias in Cohort Studies 82

Compare Tose Included to Tose Not Included 82

Compare Disease Rates Among Unexposed to External Populations 83

Assess Whether Expected Patterns of Disease Are Present 83

Assess Pattern of Results Related to Participant Selection 84

Assess Rates for Diseases Known Not to Be Afected by the Exposure 85

Integrated Assessment of Potential for Bias in Cohort Studies 86

Exercise: Assessment of Bias Due to Selection in Cohort Studies 90

8. Selection Bias in Case-C ontrol Studies 93

Synopsis 93

Learning Objectives 93

Control Selection 94

Participant Selection in Case-C ontrol and Cohort Studies 94

Selection of Controls from the Source Population 96

Coherence of Cases and Controls 98

Evaluation of Selection Bias in Case-C ontrol Studies 100

Temporal Coherence of Cases and Controls 100

Discretionary Healthcare of Cases and Controls 102

Compare Exposure Prevalence in Controls to an External Population 104

Determine Whether Exposure Prevalence Varies as Expected Among Controls 104

Examine Markers of Potential Selection Bias in Relation
to Measures of Association 105

Adjust Measures of Association for Known Sources of Noncomparability 106

Determine Whether Established Associations Can Be Confrmed 107

Integrated Assessment of Potential for Selection Bias in Case-C ontrol Studies 109

Exercise: Assessing Selection Bias in Case-C ontrol Studies 111

9. Bias Due to Loss of Study Participants 113

Synopsis 113

Learning Objectives 113

Conceptual Framework for Examining Bias Due to Loss of Study Participants 113

Evaluation of Bias Due to Loss of Study Participants 118

Characterize Nonparticipants 118

Consider Gradient of Difculty in Recruitment 119
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Stratify Study Base by Markers of Participation 122

Impute Information for Nonparticipants 123

Integrated Assessment of Potential for Bias Due to Loss of Study Participants 124

Exercise: Examining Implications of Nonparticipation 126

10. Measurement and Classifcation of Exposure 127

Synopsis 127

Learning Objectives 127

Introduction 128

Ideal Versus Operational Measures of Exposure 128

Biologically Relevant Exposure 129

Temporally Relevant Exposure 132

Optimal Level of Exposure Aggregation 133

Comparison of Optimal to Operational Measures of Exposure 134

Does Exposure Misclassifcation Difer by Disease Status? 135

Defnitions 135

Mechanisms of Diferential Exposure Misclassifcation 135

Evaluation of Exposure Misclassifcation 136

Compare Routine Measure to Superior Measures 137

Examine Multiple Indicators of Exposure 138

Examine Subsets of the Population with Difering Exposure Data Quality 139

Evaluate Known Predictors of Exposure 140

Evaluate Known Consequences of Exposure 141

Examine Dose-R esponse Gradients 141

Evaluate Whether Exposure Misclassifcation Difers by Disease Status 143

Identifcation of Subgroups with Nondiferential Exposure Misclassifcation 145

Integrated Assessment of Bias Due to Exposure Misclassifcation 146

Exercise: Assessing the Presence and Impact of Exposure Misclassifcation 147

11. Measurement and Classifcation of Disease 149

Synopsis 149

Learning Objectives 149

Framework for Evaluating Disease Misclassifcation 150

Sources of Disease Misclassifcation 151

Impact of Diferential and Nondiferential Disease Misclassifcation 154

Evaluation of Disease Misclassifcation 157

Verify Diagnostic Accuracy for Subset of Study Participants 157

Examine Results Across Levels of Diagnostic Certainty 159

Evaluate Alternate Methods of Disease Grouping 162

Determine Whether Misclassifcation Is Diferential by Exposure Status 163

Create Subgroups with Accurate Ascertainment or Nondiferential
Underascertainment 165
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Restrict Inference to Disease Outcome Tat Can Be Ascertained Accurately 165

Integrated Assessment of Potential for Bias Due to Disease Misclassifcation 166

Exercise: Assessing the Presence and Impact of Disease Misclassifcation 168

12. Random Error 171

Synopsis 171

Learning Objectives 171

Nature of Random Variation 171

Sequential Approach to Considering Random and Systematic Error 172

Special Considerations in Evaluating Random Error in Observational Studies 173

Statistical Signifcance Testing 174

Interpretation of Confdence Intervals 177

Multiple Comparisons and Related Issues 179

Integrated Assessment of Random Error 181

Exercise: Assessing Random Error 183

13. Integration of Evidence Across Studies 185

Synopsis 185

Learning Objectives 185

Introduction 186

Systematic Evidence Reviews 186

Data Pooling and Comparative Analyses 186

Meta-A nalysis 189

Interpreting Consistency and Inconsistency Among Studies 191

Inconsistent Findings 191

Consistent Findings 194

Evolution of Epidemiologic Research 194

Integrated Assessment from Combining Evidence Across Studies 195

Exercise: Interpreting Evidence from a Collection of Studies 197

14. Characterization and Communication of Conclusions 199

Synopsis 199

Learning Objectives 199

Presenting Clear, Objective, and Informed Conclusions 200

Applications of Epidemiology 201

Integration of Epidemiologic Evidence with Other Information 202

Identifcation of Key Concerns 204

Controversy over Interpretation 205

Te Case Against Algorithms for Interpreting Epidemiologic Evidence 206

Exercise: Communicating Summary Assessment of Epidemiologic Evidence 209

Index 211