EPID 623-88 Introduction to Analysis and Interpretation of HIV/STD Data

EPID 623-88 Introduction to Analysis and

Interpretation of HIV/STD Data

Epidemiologic Study Designs—a review

Manya Magnus, Ph.D.Summer 2001

Objectives

• To review epidemiologic study designs• To review measures of association

used in epidemiologic studies• To discuss interpretation of study

results

Basic study designsAnalytic

Descriptive Observational Intervention

Case reports/series Cross-sectional

Randomized controlled trials

Birth cohorts

Cohort (concurrent, non-

concurrent)

Community-based

interventions

Ecologic/correlational

Case-control (and variations)

Case reports/case series (1)

• Description of unique, unusual, rare events in one or several individuals

• Often used by physicians• May stimulate awareness of problem

(note: PCP, DES/vaginal clear cell adenocarcinoma), hypothesis generating

Case reports/case series (2)

• Analysis of case series:– Might focus on incidence or prevalence in

general (or target) population– Raw data, small numbers– If more than a few, proportions (5/10=50%)– Narrative as essence of report, plus

communication of context, why interesting

Birth cohorts

• Allows exploration of trends based on age or period effects

• Allows exploration of cumulative effects of exposure, latency periods, timing of exposure

• Explore cohort effects, age effects, period effects

• Interaction between time and calendar age• Looking graphically at cross-sectional data by

age group

Ecologic studies

• Aggregate measures• Environmental measures• Global measures• Units of observation generally geographic region,

area• Looking at number of outcome events and

predictors of interest on aggregate level• “Ecologic fallacy” issues• Evaluation of association: plotting, comparison of

rates, prevalence, adjusted-measures, etc.

Cross-sectional studies

• Individual-level data• “Snapshot” of exposure and outcome• No temporality provided• No causation can be inferred• Useful in hypothesis generating• Analysis: frequencies, cross-tabs, point

prevalence rate ratio, odds ratio, comparison of rates, etc.

Cohort studies

• Concurrent or non-concurrent• “gold standard” for observational studies• Basis for other designs• Disease-free at baseline• Follow for outcome• Analysis: frequencies, cross-tabs, relative

risk, hazard ratio, attributable risk, etc.

Case-control studies

• Look at those with/without outcome of interest and evaluate exposures

• Good for rare diseases• Many variations (nested, case-cohort,

etc.)• Analysis: frequencies, cross-tabs, odds

ratio, attributable risk, etc.

Randomized controlled clinical trials

• Cohort studies based on model of RCT• Randomize subjects to receive

intervention and follow for outcome(s) of interest

• Intent-to-treat analysis• Analysis: frequencies, cross-tabs,

relative risk, hazard ratio, etc.

Community-based interventions

• Similar to RCT, but randomizing communities

• Unit of analysiscommunity (note power issues)

Reminders (1)Diseased Not

diseased

Exposed A B A+B

Not exposed

C D C+D

A+C B+D A+B+C+D

Reminders (2)

Relative risk (RR) formula

[A/(A+B)]/[C/(C+D)]

Reminders (3)

Odds ratio (OR) formula

AD/BC

Interpreting published results

Steps to understanding published tables

1. What is the study design?

Steps to understanding published tables

1. What is the study design?

2. What is unit of analysis?

Steps to understanding published tables

1. What is the study design?2. What is unit of analysis?

3. What are predictors of interest?

Steps to understanding published tables

1. What is study design?2. What is unit of analysis?3. What are predictors of interest?

4. What are outcomes of interest?

Steps to understanding published tables

1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?

5. In tables, what is n?

Steps to understanding published tables

1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?

6. Is the table referring to subset or whole sample?

Steps to understanding published tables

1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?

7. What is being presented, compared?

Steps to understanding published tables

1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?7. What is being presented, compared?

8. What are the denominators? Do they differ by column?

Steps to understanding published tables

1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?7. What is being presented, compared?8. What are the denominators? Do they differ by column?

9. Can you add up data from text?

Steps to understanding published tables

1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?7. What is being presented, compared?8. What are the denominators? Do they differ by column?

9. Can you add up data from text? 10. Can you calculate measures of association?

Do they agree with the authors’?

Steps to understanding published tables

1. What is study design?2. What is unit of analysis?3. What are predictors of interest?4. What are outcomes of interest?5. In tables, what is n?6. Is the table referring to subset or whole sample?7. What is being presented, compared?8. What are the denominators? Do they differ by column?9. Can you add up data from text? 10. Can you calculate measures of association? Do they agree

with the authors’?

11. Are the authors’ conclusions correct?