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Clinical Epidemiology

The Essentials
Edition: 6
9781975109554
ISBN/ISSN:
9781975109554
Publication Date:
February 27, 2020
2020-02-27
9781975109554
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Selected as a Doody's Core Title for 2022 and 2023! Now in its Sixth Edition, Clinical Epidemiology: The Essentials is ...
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  • 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.
  • Edition
    6
    ISBN/ISSN
    9781975109554
    Product Format
    Paperback Book
    Trim Size
    7 x 10
    Pages
    288
    Edition
    6
    Publication Date
    February 27, 2020
    Weight
    0.95
  • Grant S. Fletcher MD, MPH
    Assistant Professor of Medicine
    Division of Internal Medicine
    The University of Washington School of Medicine
    Seattle, WA
     
  • ix
    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
    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
    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
    1
    Contents
    2
    3 Contents
    ariation 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
    Diagnosis 53
    Simplifying Data 53
    he Accuracy of a Test Result 54
    The Gold Standard 55
    ensitivity 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
    tudies of Diagnostic Tests 59
    Spectrum of Patients—the Study Population 60
    Bias 61
    Chance 61
    Imperfect Gold Standards 62
    redictive 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
    Risk: Basic
    Principles 78
    Risk Measurement 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
    4
    5 Contents xi
    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
    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
    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
    6
    7
    8xii Contents
    Measurement Bias 136
    Bias from “Non-differential”
    Misclassification 137
    Bias from Missing Data 137
    Bias, Perhaps, But Does It Matter? 137
    ensitivity Analysis 137
    Treatment 142
    Ideas and Evidence 142
    Ideas 142
    Testing Ideas 143
    tudies of Treatment Effects 144
    Observational and Experimental Studies
    of Treatment Effects 144
    andomized 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-Treat and
    Explanatory Trials 153
    Superiority, Equivalence, and Noninferiority 153
    ariations on Basic Randomized Trials 155
    ailoring the Results of Trials to Individual
    atients 156
    Subgroups 156
    Effectiveness in Individual Patients 156
    N of 1 Trials 156
    Alternatives to Randomized Controlled
    rials 157
    Limitations of Randomized Trials 157
    Observational Studies
    of Interventions 157
    Clinical Databases 158
    Randomized Versus
    Observational Studies? 158
    Phases of Clinical Trials 158
    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
    9
    10 Contents xiii
    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
    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
    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
    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
    11
    12
    13
    14xiv Contents
    Journals 242
    “Reading” Journals 243
    Guiding Patients’ Quest for Health
    nformation 245
    utting Knowledge Management
    into Practice 245
    APPENDIX A: ANSWERS TO REVIEW
    QUESTIONS 249
    APPENDIX B: ADDITIONAL READINGS 262
    INDEX 265
    • 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.
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