Clinical Epidemiology: The Essentials / Edition 6 available in Paperback, eBook
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Clinical Epidemiology: The Essentials / Edition 6
- ISBN-10:
- 1975109554
- ISBN-13:
- 9781975109554
- Pub. Date:
- 03/06/2020
- Publisher:
- LWW
![Clinical Epidemiology: The Essentials / Edition 6](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.9.4)
Clinical Epidemiology: The Essentials / Edition 6
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Overview
- 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