Epidemiology and Biostatistics

by Kestenbaum, Bryan; Adeney, Kathryn L., M.D.; Weiss, Noel S.; Shoben, Abigail S. (CON)

• ISBN13: 9780387884325
• ISBN10: 0387884327
• Edition: 1st
• Format: Paperback
• Copyright: 2009-08-21
• Publisher: Springer Verlag

Summary

This text provides students and other health professionals with the knowledge necessary to interpret clinical research articles, design clinical studies, and learn essential epidemiological concepts in an expedient and concise manner. In recent years, there has been an explosion in the volume and complexity of clinical research, highlighting the need for a conceptual understanding of the basic underpinnings of this discipline. Fundamental concepts are presented in a highly succinct format suitable for students with no previous background in epidemiology or statistics.

Table of Contents

Epidemiology
Measures of Disease Frequency	p. 3
Importance of Measures of Disease Frequency	p. 5
Prevalence	p. 5
Incidence	p. 6
Relationship Between Prevalence and Incidence	p. 9
Stratification of Disease Frequency by Person, Place, and Time	p. 9
Disease Frequency Measurements Stratified by Characteristics of Person	p. 10
Disease Frequency Measurements Stratified by Characteristics of Place	p. 10
Disease Frequency Measurements Stratified by Characteristics of Time	p. 11
Disease Frequency Measurements To Complement Experimental Data	p. 11
General Considerations in Clinical Research Design	p. 13
Study Population	p. 14
Definition of the Study Population	p. 14
Choice of Study Population and Generalizability of Study Findings	p. 15
Where to Find Information About the Study Population in a Clinical Research Article	p. 16
Exposure and Outcome	p. 17
Definition	p. 17
Specifying and Measuring the Exposure and Outcome	p. 18
Where to Find Exposure and Outcome Data in a Clinical Research Article	p. 18
Interventional Versus Observational Study Designs	p. 19
Inferring Causation from Association Studies	p. 21
Importance of Distinguishing Causation from Association	p. 21
Factors Favoring an Inference of Causation	p. 22
Case Reports and Case Series	p. 25
Cross-Sectional Studies	p. 29
Cohort Studies	p. 33
Overview of Cohort Study Design	p. 33
Ascertainment of Study Data	p. 35
Validity of Measurements	p. 35
Timing of Measurements	p. 36
Uniform Measurements	p. 37
Retrospective Versus Prospective Data Collection	p. 37
Advantages of Cohort Studies	p. 38
Study of Multiple Outcomes	p. 38
Ability to Discern Temporal Relationship Between Exposure and Outcome	p. 38
Disadvantages of Cohort Studies	p. 39
Confounding	p. 39
Inability to examine Diseases That Are Rare or Have a Long Latency	p. 39
Cohort Studies for Evaluating Medication Use	p. 40
Analysis of Data From Cohort Studies	p. 41
Incidence Proportion Versus Incidence Rate	p. 41
Relative Risk	p. 42
Attributable Risk (also Called "Risk Difference" or "Excess Risk")	p. 44
Case-Control Studies	p. 45
Case-Control Study Design	p. 47
Overview	p. 47
Selection of Cases	p. 48
Selection of Controls	p. 49
Advantages of Case-Control Studies	p. 51
Case Control Studies Can Be Ideal for the Study of Rare Diseases or Those with a Long Latency	p. 51
Case-Control Studies Allow for the Study of Multiple Exposures	p. 51
Disadvantages of Case-Control Studies	p. 52
Observational Study Design	p. 52
Recall Bias	p. 52
Case Control Studies only Provide Information Regarding the Relative Risk (Odds) of Disease	p. 53
Analysis of Case-Control Data	p. 53
Theory of the Odds Ratio	p. 53
Practical Calculation of the Odds Ratio	p. 55
Odds Ratios and Relative Risk	p. 55
Case-Control Studies Cannot Estimate the Actual Incidence of a Disease or Outcome	p. 56
Randomized Trials	p. 59
Rationale for Randomized Trials	p. 59
Kidney Transplant and Mortality	p. 60
Angioplasty versus Fibrinolysis for Patients with Acute Myocardial Infarction	p. 60
Equipoise	p. 61
Phases of Drug Development	p. 61
Phase I Studies	p. 62
Phase II Studies	p. 62
Phase III/IV Studies	p. 62
Conduct of Randomized Trials	p. 62
Comparison Group	p. 62
Placebo	p. 63
Block Randomization	p. 64
Biological Versus Clinical Endpoints	p. 65
Limitations of Randomized Controlled Trials	p. 65
Generalizability of the Study Population	p. 65
Generalizability of the Study Environment	p. 66
Limited Question	p. 67
Limited Clinical Applicability	p. 67
Randomized Design Accounts only for Confounding	p. 68
Analysis of Randomized Controlled Trial Data	p. 68
Measures of Effect	p. 68
Numbers Needed to Treat/Harm	p. 69
Measures of Effect in Journal Articles	p. 69
Intention-to Treat-Analysis	p. 70
Subgroup Analyses	p. 71
Misclassification	p. 75
Definition of Misclassification	p. 75
Nondifferential Misclassification	p. 76
Example of Nondifferential Misclassification of the Exposure	p. 76
Definition and Impact of Nondifferential Misclassification of the Exposure	p. 78
Nondifferential Misclassification of the Outcome	p. 81
Definition and Impact of Nondifferential Misclassification of the Outcome	p. 84
Differential Misclassification	p. 84
Assessment of Misclassification in Clinical Research Articles	p. 89
Introduction to Confounding	p. 91
Confounding and the Interpretation of Clinical Data	p. 91
Formal Evaluation of a Potential Confounding Factor	p. 94
Evaluation of a Confounder: Association with Exposure	p. 95
Evaluation of a Confounder: Association with Outcome	p. 95
Evaluation of a Confounder: Not in the Causal Pathway of Association	p. 96
Other Examples of Factors That Reside on the Causal Pathway of Association	p. 98
Scientifically Meaningful Versus Statistical Associations	p. 98
Evaluation of a Confounder in Clinical Research Articles	p. 99
Confounding-by-Indication	p. 100
Methods to Control for Confounding	p. 101
Restriction	p. 102
Method of Restriction	p. 102
Pros and Cons of Restriction as a Means to Control for Confounding	p. 102
Restriction to Control for Confounding-by-Indication	p. 103
Stratification	p. 103
Method of Stratification	p. 103
Pros and Cons of Stratification as a Means to Control for Confounding	p. 105
Stratum-Specific Associations	p. 105
Matching	p. 106
Method of Matching	p. 106
Pros and Cons of Matching as a Means to Control Confounding	p. 107
Regression	p. 108
Randomization	p. 108
Interpreting Study Results After Adjustment for Confounding	p. 109
Unadjusted Versus Adjusted Associations: Confounding	p. 109
Confounding: An Advanced Example	p. 110
Effect Modification	p. 113
Concept of Effect Modification	p. 113
Synergy Between Exposure variables	p. 114
Effect Modification Versus Confounding	p. 115
Evaluation of Effect Modification	p. 116
Epidemiologic Evaluation of Effect Modification	p. 116
Statistical Evaluation of Effect Modification	p. 116
Effect Modification in Clinical Research Articles	p. 117
Effect Modification on the Relative and Absolute Scales	p. 118
Screening	p. 121
General Principles of Screening	p. 122
Qualities of Diseases Appropriate for Screening	p. 122
The Disease should be Important in the Screened Population	p. 122
Early Recognition and Treatment of the Disease Should Prevent Clinical Outcomes	p. 123
The Disease Should have a Preclinical Phase	p. 123
Qualities of Screening Tests	p. 123
General Qualities	p. 123
Reliability and Validity	p. 123
Validity of Screening Tests	p. 124
Sensitivity and Specificity	p. 124
Positive and Negative Predictive Value	p. 125
Screening Tests with Continuous Values	p. 129
Reliability of Screening Tests	p. 132
Variation in Measurement Tools and Within and Individual	p. 132
Measures of Reliability	p. 133
Types of Bias in Screening Studies	p. 134
Referral Bias	p. 134
Lead Time Bias	p. 135
Length Bias Sampling	p. 136
Overdiagnosis Bias	p. 137
Association versus Prediction	p. 137
Diagnostic Testing	p. 139
General Considerations in Medical Testing	p. 139
Likelihood Ratios	p. 143
Biostatistics
Summary Measures in Statistics	p. 153
Types of Variables	p. 153
Univariate Statistics	p. 154
Histograms	p. 154
Measures of Location and Spread	p. 156
Quantiles	p. 158
Univariate Statistics for Binary Data	p. 159
Bivariate Statistics	p. 159
Tabulation Across Categories	p. 159
Correlation	p. 160
Quantile-Continuous Variable Plots	p. 162
Introduction to Statistical Inference	p. 163
Definition of a Population, Sample, and random Sample	p. 163
Statistical Inference	p. 164
Generalizability	p. 165
Confidence Intervals	p. 165
P-values	p. 168
Confidence Intervals and p-values in Clinical Research	p. 169
Hypothesis Testing	p. 171
Study Hypothesis and Null Hypothesis	p. 172
Distribution of Sampling Means	p. 173
Properties of the Distribution of Sampling Means	p. 174
Normal (Bell-Shaped) Distribution for Reasonably Large Sample Sizes	p. 174
Mean Equal to the Population Mean	p. 175
Spread of the Distribution Related to Population Variation and Sample Size	p. 175
Distribution of Sampling Means: Summary	p. 177
Conducting the Experiment	p. 177
Interpreting Hypothesis Tests	p. 181
Common Tests of Hypothesis in Clinical Research	p. 181
T-Tests	p. 181
Chi-Square Tests	p. 182
ANOVA Tests	p. 182
An Imperfect System	p. 183
Type I Errors	p. 183
Type II Errors	p. 184
Power	p. 184
Linear Regression	p. 189
Describing the Association Between Two Variables	p. 189
Univariate Linear Regression	p. 192
The Linear Regression Equation	p. 192
Residuals and the Sum of Squares	p. 193
Absolute Versus Relative Fit	p. 194
Interpreting Results from Univariate Regression Equations	p. 195
Interpreting Continuous Covariates	p. 195
Interpreting Binary Covariates	p. 195
Special Considerations	p. 197
Influential Points	p. 197
Nonlinear Associations	p. 198
Extrapolating the Regression Equation Beyond the Study Data	p. 200
Multiple Linear Regression	p. 200
Definition of the Multivariate Model	p. 200
Interpreting Results from the Multiple Regression Model	p. 201
Confounding and Effect Modification in Regression Models	p. 204
Confounding	p. 204
Effect Modification	p. 205
Non-Linear Regression	p. 209
Regression for Ratios	p. 209
Logistic Regression	p. 211
Application of Logistic Regression Models	p. 213
Survival Analysis	p. 215
Limitations of Incidence Measures for Evaluating Risk	p. 215
Incidence Measures: Oversimplification of Study Results Over time	p. 216
Incidence Measures: Crude Handling of Participant Dropout	p. 216
Survival Data	p. 217
Statistical Testing of Survival Data	p. 219
Definitions of Events and Censoring	p. 220
Kaplan-Meier Estimation	p. 221
Kaplan-Meier Estimation of S(t)	p. 221
Kaplan-Meier Estimation of S(t) with Censored Data	p. 222
Cox's Proportional Hazards Model	p. 224
Description of the Proportional Hazards Model	p. 224
Interpreting Survival Data and the Proportional Hazards Model	p. 227
Survival Versus Hazard Ratio Data	p. 228
References	p. 229
Author Index	p. 233
Subject Index	p. 237
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