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Clinical epidemiology [electronic resource] : the essentials /
Robert H. Fletcher, Suzanne W. Fletcher, Grant S. Fletcher.
5th ed.
Philadelphia : Wolters Kluwer/Lippincott Williams & Wilkins Health, c2014.
253 p. : col. ill. ; 26 cm.
9781451144475 (alk. paper)
More Details
Philadelphia : Wolters Kluwer/Lippincott Williams & Wilkins Health, c2014.
9781451144475 (alk. paper)
Licensed for access by U. of T. users.
contents note
Frequency -- Abnormality -- Risk : basic principles -- Risk : exposure to disease -- Risk : disease to exposure -- Prognosis -- Diagnosis -- Treatment -- Prevention -- Chance -- Cause -- Summarizing the evidence -- Knowledge management.
catalogue key
Includes bibliographical references (p. 249-250) and index.
A Look Inside
This item was reviewed in:
Reference & Research Book News, February 2013
To find out how to look for other reviews, please see our guides to finding book reviews in the Sciences or Social Sciences and Humanities.
Bowker Data Service Summary
This title provides an introduction to epidemiology that will be useful for medical, nursing, and pharmacy students to develop a system to observe and assess outcomes in similar patient types, and then apply this knowledge of outcomes to improve future patient care. The book has illustrations, pedagogical tools, examples, and summary boxes.
Main Description
Now in its Fifth Edition, Clinical Epidemiology: The Essentials is a comprehensive, concise, and clinically oriented introduction to the subject of epidemiology. Written by expert educators, this 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 Fifth Edition includes more complete coverage of systematic reviews and knowledge management, as well as other key topics such as abnormality, diagnosis, frequency and risk, prognosis, treatment, prevention, chance, studying cases and cause.
Main Description
Now in its Fifth Edition, Clinical Epidemiology: The Essentials is a comprehensive, concise, and clinically oriented introduction to the subject of epidemiology. Written by expert educators, this text introduces students to the principles of evidence-based medicine that will help them develop and apply methods of clinical observation to form accurate conclusions. Intended primarily for medical students taking their first course in epidemiology and public health, the comprehensive coverage and clinical examples also make this a perfect reference for residents and clinicians. Other features and highlights include: Revised, four-color art program aids visual learners, "Key Words" lists start each chapter and tip the reader to the important concepts that must be mastered for efficient studying, End-of-chapter review questions with answers help students test their understanding and mastery of the material, "Example" feature helps clarify important concepts by discussing real-world studies taken directly from clinical literature, Highly regarded for its clear, concise writing style, this book is perfect both for students learning epidemiology and as a reference guide for practitioners and more advanced students. Whether you're learning epidemiology for the first time or looking for a clinically oriented reference, you won't find a better book than Clinical Epidemiology: The Essentials. Book jacket.
Table of Contents
Introductionp. 1
Clinical Questions and Clinical Epidemiologyp. 2
Health Outcomesp. 2
The Scientific Basis for Clinical Medicinep. 3
Basic Principlesp. 6
Variablesp. 6
Numbers and Probabilityp. 6
Populations and Samplesp. 6
Bias (Systematic Error)p. 7
Selection Biasp. 7
Measurement Biasp. 8
Confoundingp. 8
Chancep. 10
The Effects of Bias and Chance Are Cumulativep. 10
Internal and External Validityp. 11
Information and Decisionsp. 12
Organization of this Bookp. 12
Frequencyp. 17
Are Words Suitable Substitutes for Numbers?p. 18
Prevalence and Incidencep. 18
Prevalencep. 18
Incidencep. 18
Prevalence and Incidence in Relation to Timep. 19
Relationships Among Prevalence, Incidence, and Duration of Diseasep. 19
Some other Ratesp. 20
Studies of Prevalence and Incidencep. 21
Prevalence Studiesp. 21
Incidence Studiesp. 21
Cumulative Incidencep. 21
Incidence Density (Person-Years)p. 22
Basic Elements of Frequency Studiesp. 23
What Is a Case? Defining the Numeratorp. 23
What Is the Population? Defining the Denominatorp. 25
Does the Study Sample Represent the Population?p. 25
Distribution of Disease by Time, Place, and Personp. 25
Timep. 26
Placep. 27
Personp. 27
Uses of Prevalence Studiesp. 28
What Are Prevalence Studies Good For?p. 28
What Are Prevalence Studies Not Particularly Good For?p. 28
Abnormalityp. 31
Types of Datap. 32
Nominal Datap. 32
Ordinal Datap. 32
Interval Datap. 32
Performance of Measurementsp. 33
Validityp. 33
Content Validityp. 33
Criterion Validityp. 33
Construct Validityp. 34
Reliabilityp. 34
Rangep. 34
Responsivenessp. 34
Interpretabilityp. 35
Variationp. 35
Variation Resulting from Measurementp. 35
Variation Resulting from Biologic Differencesp. 36
Total Variationp. 37
Effects of Variationp. 37
Distributionsp. 38
Describing Distributionsp. 38
Actual Distributionsp. 39
The Normal Distributionp. 40
Criteria for Abnormalityp. 41
Abnormal = Unusualp. 42
Abnormal = Associated with Diseasep. 43
Abnormal = Treating the Condition Leads to a Better Clinical Outcomep. 43
Regression to the Meanp. 45
Risk: Basic Principlesp. 50
Risk Factorsp. 51
Recognizing Riskp. 51
Long Latencyp. 51
Immediate Versus Distant Causesp. 51
Common Exposure to Risk Factorsp. 52
Low Incidence of Diseasep. 52
Small Riskp. 52
Multiple Causes and Multiple Effectsp. 52
Risk Factors May or May Not Be Causalp. 53
Predicting Riskp. 54
Combining Multiple Risk Factors to Predict Riskp. 54
Risk Prediction in Individual Patients and Groupsp. 54
Evaluating Risk Prediction Toolsp. 56
Calibrationp. 56
Discriminationp. 56
Sensitivity and Specificity of a Risk Prediction Toolp. 56
Risk Stratificationp. 57
Why Risk Prediction Tools Do Not Discriminate Well Among Individualsp. 57
Clinical Uses of Risk Factors and Risk Prediction Toolsp. 58
Risk Factors and Pretest Probability for Diagnostic Testingp. 58
Using Risk Factors to Choose Treatmentp. 58
Risk Stratification for Screening Programsp. 58
Removing Risk Factors to Prevent Diseasep. 59
Risk: Exposure to Diseasep. 61
Studies of Riskp. 61
When Experiments Are Not Possible or Ethicalp. 61
Cohortsp. 62
Cohort Studiesp. 62
Prospective and Historical Cohort Studiesp. 63
Prospective Cohort Studiesp. 63
Historical Cohort Studies Using Medical Databasesp. 64
Case-Cohort Studiesp. 65
Advantages and Disadvantages of Cohort Studiesp. 65
Ways to Express and Compare Riskp. 67
Absolute Riskp. 67
Attributable Riskp. 68
Relative Riskp. 68
Interpreting Attributable and Relative Riskp. 68
Population Riskp. 69
Taking other Variables into Accountp. 71
Extraneous Variablesp. 71
Simple Descriptions of Riskp. 71
Confoundingp. 71
Working Definitionp. 72
Potential Confoundersp. 72
Confirming Confoundingp. 72
Control of Confoundingp. 72
Randomizationp. 73
Restrictionp. 73
Matchingp. 74
Stratificationp. 74
Standardizationp. 75
Multivariable Adjustmentp. 75
Overall Strategy for Control of Confoundingp. 75
Observational Studies and Causep. 76
Effect Modificationp. 76
Risk: From Disease to Exposurep. 80
Case-Control Studiesp. 81
Design of Case-Control Studiesp. 83
Selecting Casesp. 83
Selecting Controlsp. 83
The Population Approachp. 83
The Cohort Approachp. 84
Hospital and Community Controlsp. 84
Multiple Control Groupsp. 84
Multiple Controls per Casep. 85
Matchingp. 85
Measuring Exposurep. 85
Multiple Exposuresp. 87
The Odds Ratio: An Estimate of Relative Riskp. 87
Controlling for Extraneous Variablesp. 88
Investigation of A Disease Outbreakp. 89
Prognosisp. 93
Differences in Risk and Prognostic Factorsp. 93
The Patients Ate Differentp. 94
The Outcomes Are Differentp. 94
The Rates Are Differentp. 94
The Factors May be Differentp. 94
Clinical Course and Natural History of Diseasep. 94
Elements of Prognostic Studiesp. 95
Patient Samplep. 95
Zero Timep. 96
Follow-Upp. 96
Outcomes of Diseasep. 96
Describing Prognosisp. 97
A Trade-Off: Simplicity versus More Informationp. 97
Survival Analysisp. 97
Survival of a Cohortp. 97
Survival Curvesp. 98
Interpreting Survival Curvesp. 100
Identifying Prognostic Factorsp. 100
Case Seriesp. 101
Clinical Prediction Rulesp. 102
Bias in Cohort Studiesp. 102
Sampling Biasp. 103
Migration Biasp. 103
Measurement Biasp. 104
Bias from "Non-differential" Misclassificationp. 104
Bias, Perhaps, but does it Matter?p. 104
Sensitivity Analysisp. 104
Diagnosisp. 108
Simplifying Datap. 108
The Accuracy of a Test Resultp. 109
The Gold Standardp. 109
Lack of Information on Negative Testsp. 110
Lack of Information on Test Results in the Nondiseasedp. 110
Lack of Objective Standards for Diseasep. 110
Consequences of Imperfect Gold Standardsp. 111
Sensitivity and Specificityp. 111
Definitionsp. 113
Use of Sensitive Testsp. 113
Use of Specific Testsp. 113
Trade-Offs between Sensitivity and Specificityp. 113
The Receiver Operator Characteristic (ROC) Curvep. 114
Establishing Sensitivity and Specificityp. 115
Spectrum of Patientsp. 116
Biasp. 116
Chancep. 117
Predictive Valuep. 117
Definitionsp. 117
Determinants of Predictive Valuep. 118
Estimating Prevalence (Pretest Probability)p. 119
Increasing the Pretest Probability of Diseasep. 120
Specifics of the Clinical Situationp. 120
Selected Demographic Groupsp. 120
Referral Processp. 120
Implications for Interpreting the Medical Literaturep. 122
Likelihood Ratiosp. 122
Oddsp. 122
Definitionsp. 122
Use of Likelihood Ratiosp. 122
Why Use Likelihood Ratios?p. 123
Calculating Likelihood Ratiosp. 124
Multiple Testsp. 125
Parallel Testingp. 126
Clinical Prediction Rulesp. 127
Serial Testingp. 128
Serial Likelihood Ratiosp. 128
Assumption of Independencep. 129
Treatmentp. 132
Ideas and Evidencep. 132
Ideasp. 132
Testing Ideasp. 133
Studies of Treatment Effectsp. 134
Observational and Experimental Studies of Treatment Effectsp. 134
Randomized Controlled Trialsp. 134
Ethicsp. 135
Samplingp. 135
Interventionp. 136
Comparison Groupsp. 138
Allocating Treatmentp. 139
Differences Arising after Randomizationp. 139
Patients May Not Have the Disease Being Studiedp. 140
Compliancep. 140
Cross-overp. 141
Cointerventionsp. 141
Blindingp. 141
Assessment of Outcomesp. 142
Efficacy and Effectivenessp. 143
Intention-to-Treat and Explanatory Trialsp. 144
Superiority, Equivalence, and Non-Inferiorityp. 145
Variations on Basic Randomized Trialsp. 145
Tailoring the Results of Trials to Individual Patientsp. 146
Subgroupsp. 146
Effectiveness in Individual Patientsp. 146
Trials of N = 1p. 146
Alternatives to Randomized Controlled Trialsp. 147
Limitations of Randomized Trialsp. 147
Observational Studies of Interventionsp. 147
Clinical Databasesp. 148
Randomized versus Observational Studies?p. 148
Phases of Clinical Trialsp. 148
Preventionp. 152
Preventive Activities in Clinical Settingsp. 152
Types of Clinical Preventionp. 152
Immunizationp. 153
Screeningp. 153
Behavioral Counseling (Lifestyle Changes)p. 153
Chemopreventionp. 153
Levels of Preventionp. 153
Primary Preventionp. 153
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