Clinical Epidemiology: The Essentials / Edition 6

by Grant S. Fletcher MD, MPH

Overview

Selected as a Doody's Core Title for 2022 and 2023!


Now in its Sixth Edition, Clinical Epidemiology: The Essentials is a comprehensive, concise, and clinically oriented introduction to the subject of epidemiology. Written by expert educators, this approachable, informative text introduces students to the principles of evidence-based medicine that will help them develop and apply methods of clinical observation in order to form accurate conclusions.
 
The updated sixth edition reflects the most current approaches to clinical epidemiology, including the latest coverage of modeling and expanded insight on applying concepts to clinical practice, with updated, clinical vignette-style end-of-chapter questions to help strengthen students’ understanding and ensure a confident transition to clinical settings.

• Updated content throughout reflects the latest practices in clinical epidemiology.
• Increased emphasis on clinical judgment helps students confidently evaluate the effectiveness of guidelines and integrate them into practice.
• Updated vignette-style end-of-chapter questions place concepts in a clinical context and reinforce students’ understanding.
• Key Word Lists at the start of each chapter familiarize students with critical terminology for clinical competence.
• Example boxes clarify the clinical implications of important concepts with relevant real-world patient care scenarios.
• Appendix of Additional Readings highlights trusted resources for further review.

Product Details

ISBN-13:	9781975109554
Publisher:	LWW
Publication date:	03/06/2020
Series:	Lippincott Connect
Edition description:	Sixth, North American Edition
Pages:	288
Product dimensions:	6.90(w) x 10.00(h) x 0.60(d)

Table of Contents

1 Introduction 1

Clinical Questions and Clinical Epidemiology 2

Health Outcomes 2

The Scientific Basis for Clinical Medicine 3

Basic Principles 5

Variables 6

Numbers and Probability 6

Populations and Samples 6

Bias (Systematic Error) 6

Chance 10

The Effects of Bias and Chance Are Cumulative 10

Internal and External Validity 11

Information and Decisions 12

Organization of This Book 12

2 Frequency 17

Are Words Suitable Substitutes for Numbers? 17

Prevalence and Incidence 18

Prevalence 18

Incidence 18

Prevalence and Incidence in Relation to Time 19

Relationships Among Prevalence, Incidence, and Duration of Disease 19

Some Other Rates 20

Studies of Prevalence and Incidence 20

Prevalence Studies 21

Incidence Studies 21

Cumulative Incidence 21

Incidence Density (Person-Years) 21

Basic Elements of Frequency Studies 22

What Is a Case? Defining the Numerator 22

What Is the Population? Defining the Denominator 24

Does the Study Sample Represent the Population? 25

Distribution of Disease by Time, Place, and Person 25

Time 25

Place 26

Person 26

Uses of Prevalence Studies 27

What Are Prevalence Studies Good for? 27

What Are Prevalence Studies Not Particularly Good for? 28

3 Abnormality 31

Types of Data 32

Nominal Data 32

Ordinal Data 32

Interval Data 32

Performance of Measurements 33

Validity 33

Reliability 34

Range 35

Responsiveness 35

Interpretability 35

Variation 36

Variation Resulting from Measurement 36

Variation Resulting from Biologic Differences 36

Total Variation 37

Effects of Variation 38

Distributions 39

Describing Distributions 39

Actual Distributions 39

The Normal Distribution 39

Criteria for Abnormality 41

Abnormal = Unusual 42

Abnormal = Biologic Dysfunction 43

Abnormal = Illness 45

Abnormal = Treating the Condition Leads to a Better Clinical Outcome 47

Regression to the Mean 48

4 Diagnosis 53

Simplifying Data 53

The Accuracy of a Test Result 54

The Gold Standard 55

Sensitivity and Specificity 55

Definitions 55

Use of Sensitive Tests 55

Use of Specific Tests 57

Trade-Offs Between Sensitivity and Specificity 57

The Receiver Operator Characteristic (ROC) Curve 58

Studies of Diagnostic Tests 59

Spectrum of Patients-the Study Population 60

Bias 61

Chance 61

Imperfect Gold Standards 62

Predictive Value 64

Definitions 64

Determinants of Predictive Value 65

Estimating Prevalence (Pretest Probability) 66

Implications for Interpreting the Medical Literature 68

Likelihood Ratios 68

Odds 68

Definitions 69

Use of Likelihood Ratios 69

Why Use Likelihood Ratios? 69

Calculating Likelihood Ratios 70

Multiple Tests 71

Parallel Testing 72

Clinical Prediction Rules 73

Serial Testing 74

Serial Likelihood Ratios 74

Assumption of Independence 74

5 Risk: Basic Principles 78

Risk Management 79

Risk Factors 79

Recognizing Risk Factors 80

Long Latency 80

Immediate Versus Distant Causes 80

Common Exposure to Risk Factors 80

Low Incidence of Disease 81

Small Risk 81

Multiple Causes and Multiple Effects 81

Risk Factors May or May Not Be Causal 81

Risk Prediction Models 82

Combining Multiple Factors 82

Evaluating Risk Prediction Tools 83

Discrimination 83

Calibration 85

Validating Models 86

External Validation 86

Comparing Models 87

Assessing Models in Clinical Practice 87

Risk Stratification 87

Clinical Uses of Risk Factors, Prognostic Factors, and Risk Prediction Tools 88

Risk Prediction and Pretest Probability for Diagnostic Testing 88

Using Risk Factors to Choose Treatment 89

Risk Stratification for Screening Programs 89

Removing Risk Factors to Prevent Disease 89

6 Risk: Exposure to Disease 92

Studies of Risk 92

When Experiments Are Not Possible or Ethical 92

Cohorts 93

Cohort Studies 93

Prospective and Historical Cohort Studies 94

Advantages and Disadvantages of Cohort Studies 96

Ways to Express and Compare Risk 98

Absolute Risk 99

Attributable Risk 99

Relative Risk 99

Interpreting Attributable and Relative Risk 99

Population Risk 100

Taking Other Variables into Account 101

Extraneous Variables 101

Simple Descriptions of Risk 101

Confounding 102

Working Definition 102

Potential Confounders 102

Confirming Confounding 102

Control of Confounding 103

Randomization 103

Restriction 103

Matching 104

Stratification 104

Standardization 105

Multivariable Adjustment 105

Overall Strategy for Control of Confounding 106

Observational Studies and Cause 106

Effect Modification 106

Mendelian Randomization 107

7 Risk: From Disease to Exposure 111

Case-Control Studies 112

Design of Case-Control Studies 114

The Source Population 114

Selecting Cases 114

Selecting Controls 114

Measuring Exposure 116

The Odds Ratio: An Estimate of Relative Risk 118

Odds Ratio Calculation 119

Odds Ratio as an Indirect Estimate of Relative Risk 119

Odds Ratio as a Direct Estimate of Relative Risk 120

Controlling for Extraneous Variables 120

Investigation of a Disease Outbreak 121

8 Prognosis 126

Differences in Risk and Prognostic Factors 126

The Patients Are Different 127

The Outcomes Are Different 127

The Rates Are Different 127

The Factors May be Different 127

Clinical Course and Natural History of Disease 127

Elements of Prognostic Studies 127

Patient Sample 127

Zero Time 128

Follow-Up 129

Outcomes of Disease 129

Describing Prognosis 129

A Trade-Off: Simplicity Versus More Information 129

Survival Analysis 130

Survival of a Cohort 130

Survival Curves 132

Interpreting Survival Curves 133

Identifying Prognostic Factors 133

Case Series 134

Clinical Prediction Rules 134

Bias in Cohort Studies 135

Sampling Bias 136

Migration Bias 136

Measurement Bias 136

Bias from "Non-differential" Misclassification 137

Bias from Missing Data 137

Bias, Perhaps, But Does It Matter? 137

Sensitivity Analysis 137

9 Treatment 142

Ideas and Evidence 142

Ideas 142

Testing Ideas 143

Studies of Treatment Effects 144

Observational and Experimental Studies of Treatment Effects 144

Randomized Controlled Trials 144

Ethics 145

Sampling 145

Intervention 147

Comparison Groups 147

Allocating Treatment 148

Differences Arising After Randomization 149

Blinding 150

Assessment of Outcomes 150

Efficacy and Effectiveness 152

Intention-to-Treatand Explanatory Trials 153

Superiority, Equivalence, and Noninferiority 153

Variations on Basic Randomized Trials 155

Tailoring the Results of Trials to Individual Patients 156

Subgroups 156

Effectiveness in Individual Patients 156

N of 1 Triais 156

Alternatives to Randomized Controlled Trials 157

Limitations of Randomized Trials 157

Observational Studies of Interventions 157

Clinical Databases 158

Randomized Versus Observational Studies? 158

Phases of Clinical Trials 158

10 Prevention 162

Preventive Activities in Clinical Settings 162

Types of Clinical Prevention 163

Levels of Prevention 163

Primary Prevention 163

Secondary Prevention 164

Tertiary Prevention 164

Confusion About Primary, Secondary, and Tertiary Prevention 164

Scientific Approach to Clinical Prevention 165

Burden of Suffering 165

Effectiveness of Treatment 166

Treatment in Primary Prevention 166

Treatment in Secondary Prevention 167

Treatment in Tertiary Prevention 168

Methodologic Issues in Evaluating Screening Programs 169

Prevalence and Incidence Screens 169

Special Biases 169

Performance of Screening Tests 172

High Sensitivity and Specificity 172

Detection and Incidence Methods for Calculating Sensitivity 173

Low Positive Predictive Value 174

Simplicity and Low Cost 174

Safety 175

Acceptable to Patients and Clinicians 175

Unintended Consequences of Screening 175

Risk of False-Positive Result 176

Risk of Negative Labeling Effect 176

Risk of Overdiagnosis (Pseudodisease) in Cancer Screening 177

Incidentalomas 178

Changes in Screening Tests and Treatments Over Time 179

Weighing Benefits Against Harms of Prevention 179

11 Chance 185

Two Approaches to Chance 185

Hypothesis Testing 186

False-Positive and False-Negative Statistical Results 186

Concluding That a Treatment Works 186

Dichotomous and Exact P Values 187

Statistical Significance and Clinical Importance 187

Statistical Tests 188

Concluding That a Treatment Does Not Work 189

How Many Study Patients Are Enough? 190

Statistical Power 190

Estimating Sample Size Requirements 190

Point Estimates and Confidence Intervals 193

Statistical Power After a Study Is Completed 194

Detecting Rare Events 194

Multiple Comparisons 194

Subgroup Analysis 196

Multiple Outcomes 197

Noninferiority Studies 198

Multivariable Methods 198

Bayesian Reasoning 200

12 Cause 204

Basic Principles 205

Single Causes 205

Multiple Causes 205

Proximity of Cause to Effect 206

Indirect Evidence for Cause 208

Examining Individual Studies 208

Hierarchy of Research Designs 209

The Body of Evidence for and Against Cause 209

Does Cause Precede Effect? 210

Strength of the Association 210

Dose-Response Relationships 210

Reversible Associations 211

Consistency 211

Biologic Plausibility 211

Specificity 212

Analogy 212

Aggregate Risk Studies 212

Modeling 214

Weighing the Evidence 216

13 Summarizing the Evidence 219

Traditional Reviews 219

Systematic Reviews 220

Defining a Specific Question 220

Selecting Studies 221

Assessing Study Quality and Characteristics 223

Summarizing Results 225

Combining Studies in Meta-Analyses 226

Are the Studies Similar Enough to Justify Combining? 226

How Are the Results Pooled? 227

Identifying Reasons for Heterogeneity 228

Additional Meta-Analysis Methods 229

Patient-Level Meta-Analysis 229

Network Meta-Analysis 230

Cumulative Meta-Analyses 230

Systematic Reviews of Observational and Diagnostic Studies 231

Strengths and Weaknesses of Meta-Analyses 232

14 Knowledge Management 236

Basic Principles 236

Do It Yourself or Delegate? 236

Which Medium? 237

Grading Information 237

Misleading Reports of Research Findings 237

Looking Up Answers to Clinical Questions 239

Solutions 239

Surveillance on New Developments 241

Journals 242

"Reading" Journals 243

Guiding Patients' Quest for Health Information 245

Putting Knowledge Management into Practice 245

Appendix A Answers to Review Questions 249

Appendix B Additional Readings 262

Index 265

Editorial Reviews

Reviewer: Muddasir Ashraf, M.D /MS CI student(University of Iowa Hospital)
Description: This sixth edition book covers essential concepts of clinical epidemiology and how they can enhance patient care outcomes. Keywords and examples from clinical medicine are unique elements. The ebook helps in selecting topics for later reference by adding them to the study selection list. The hyperlinks to the references and cross-links to other content are helpful, too. The fifth edition was published in 2012.
Purpose: The purpose of this book is to equip clinicians with the essential knowledge needed to weigh evidence themselves and help them make high-stakes decisions based on evidence. The author also mentions that this book will help clinicians who are committed to pursuing research careers. The print copy and ebook both meet these objectives. The print copy is more fun to read, but it does have its limitations. The ebook is more time-efficient due to hyperlinks and selecting topics of interest for later reference.
Audience: According to the author, this book is for clinicians including physicians, nurses, physician assistants, psychologists, veterinarians, and students. The book does meet the needs of the intended audience. The author is an associate professor of medicine with extensive clinical experience and a degree in medicine and public health. I do not see a significant number of publications on PubMed, but overall, I think the author is a credible authority on this subject.
Features: The author introduces basic principles of epidemiology, then goes into depth on topics like diagnosis, treatment, and prevention. He then talks about summarizing the evidence, with clinical medicine examples given throughout to help clinicians apply these principles to daily clinical practice. He expands on concepts like comparative effectiveness, pragmatic clinical trials, non-inferiority trials, stepped-wedge trials, network meta-analysis, and modern concepts in grading evidence-based recommendations. There are review questions at the end of each chapter for self-assessment.
Assessment: This book is well written. Its strengths are the simple language used to communicate concepts and examples in every chapter to leave less room for abstract thinking. The website has additional features, but I think it could be improved to be more user-friendly. The book meets its objectives to equip the audience to apply epidemiology principles to everyday clinical practice and help them critically analyze and use appropriate evidence to make high-stakes decisions for best patient outcomes. This edition is justified.

Doody's Review Service