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A Brief Introduction to Epidemiology - XI

(Epidemiologic Research Designs:Experimental/Interventional Studies)

Betty C. Jung, RN, MPH, CHES

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Learning Objectives

To understand: – What experimental studies are

– The value of such studies

– The basic methodology

– Pros and Cons of such studies

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Introduction

The primary purpose of research is to conduct a scientific, or, scholarly investigation into a phenomenon, or to answer a burning question.

Research is defined as a systematic approach to problem solving.

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Epidemiological Study Designs

Observational Studies - examine associations between risk factors and outcomes (Analytical - determinants and risk of disease, and descriptive - patterns and frequency of disease)

Intervention Studies - explore the association between interventions and outcomes. (Experimental studies or clinical trials)

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Epidemiological Study Designs Observational

– Cross-Sectional– Case-control– Cohort

Interventional– Natural Experiment (Community Trial)– Field Trial– Experiment/Randomized Trails (ex. Clinical Trial)

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Examples of Experimental Epidemiologic Studies

Prophylactic vaccines tested on children populations to prove the efficacy of the vaccines in preventing the diseases (i.e., polio)

Prophylaxis with drugs in preventing disease (i.e., penicillin to prevent rheumatic fever)

Impact on health-related behavior and coronary heart disease in response to community-wide heart disease prevention intervention

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Value

Experiments are seen as the “Supreme Court” of epidemiologic research as they provide the strongest possible evidence of disease causation.

Experimental study designs can rule out with greater certainty factors that may confound potential cause and affect relationships.

A study’s degree of internal validity depends on the study design’s ability to determine whether an antecedent causes an effect (or outcome).

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Community Trials

Communities rather than individuals comprise the treatment groups

Appropriate for diseases that have their origins in social conditions that can be influenced by intervention directed at group behavior as well as individuals

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Limitations of Community Trials

Random allocation of communities is not practical

Only a small number of communities can be included

Other methods are needed to ensure any difference found can be attributed to the intervention rather than to any inherent differences between the communities studied

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Field Trials

Involve people who are disease-free but presumed to be at risk

Data collection – “in the field” – among non-institutionalized people in the general population

Used to evaluate interventions that reduce exposure without measuring the occurrence of health effects.

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Limitations of Field Trials

Hugh undertaking Major logistic considerations Major financial considerations Think of how much work is required

to randomize and allocate participants to various treatment groups!

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Experimental Study Design

Time

Sample of Cases

Treated (T)

Not Treated (NT)(Control)

Treated - Improved

Treated – Not Improved

Not Treated - Improved

Not Treated – Not Improved

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Randomized Trial Methodology

Random allocation - Each subject has an equal chance of being assigned to any group in the study, so that all groups in a study are similar in all characteristics not controlled by other methods, such as subject selection.

Random allocation can be used with matching to ensure the study groups are comparable

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Randomized Trial Design

Time

Defined Population

New Treatment

Current Treatment

Improved

Not Improved

Improved

Not Improved

RANDOMIZED

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Four Possibilities The treatments do not differ and we

correctly conclude they do not differ The treatments do not differ but we

conclude they do differ The treatments differ but we conclude

they do not differ The treatments do differ and we

correctly conclude that they do differ

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Pros Helpful in assessing the value of new therapies to

combat acute diseases in developing countries Can evaluate a single variable in a precisely

defined patient group Prospective design Eliminates bias by comparing two otherwise

identical groups Allows for meta-analysis

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Cons Expensive and time consuming Not always properly conducted – too few

subjects, too short a time period Influence of sponsorship Use of surrogate endpoints may introduce

“hidden bias” Failure to randomize all eligible subjects Failure to blind assessors to randomized

status of subjects

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References

For Internet Resources on the topics covered in this lecture, check out my Web site:

http://www.bettycjung.net/