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Epidemiologic Research Designs. Ramon Jason M. Javier, M.D., D.P.A.F.P. Department of Preventive and Community Medicine College of Medicine U.E.R.M.M.M.C.I. Objectives. To define epidemiology and differentiate the two main categories of epidemiologic work.

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epidemiologic research designs

Epidemiologic Research Designs

Ramon Jason M. Javier, M.D., D.P.A.F.P.

Department of Preventive and Community Medicine

College of Medicine

U.E.R.M.M.M.C.I.

objectives
Objectives
  • To define epidemiology and differentiate the two main categories of epidemiologic work.
  • To review the various epidemiologic studies, as well as the different research designs used in Medicine
epidemiology
Epidemiology

Epidemiology is the study of the distribution and determinants of disease in human population.

Epidemiology has two main categories of work:

  • Descriptive Epidemiology
  • Analytic Epidemiology
descriptive epidemiology
Descriptive Epidemiology

Descriptive Epidemiology includes activities related to characterizing the distribution of diseases within a population.

descriptive epidemiology1
Descriptive Epidemiology
  • Community Reaction to Disease
    • absence of disease
    • sporadic occurrence
    • endemic occurrence
    • epidemic
descriptive epidemiology2
Descriptive Epidemiology
  • Descriptive Variables
      • time / temporal variation
      • place
      • person
analytic epidemiology
Analytic Epidemiology

Analytic Epidemiology is concerned with activities related to identifying possible causes for the occurrence of diseases. It essentially identifies determinantsof disease occurrence.

applications of epidemiology
Applications of Epidemiology
  • disease surveillance
  • searching for causes of disease
  • diagnostic testing
  • determining natural history of disease
  • searching for prognostic factors
  • testing new treatments
  • evaluating community health interventions
epidemiologic research designs1
Epidemiologic Research Designs
  • Observational Designs
  • Experimental Designs
observational designs
Observational Designs
  • Descriptive Study
    • Case Report
    • Case Series
    • Cross-Sectional* (Survey Studies)
  • Analytic Study
    • Cross-Sectional*
    • Cohort Study
    • Case-Control Study
experimental designs
Experimental Designs

Analytic Study

  • Clinical Trial
    • Randomized Clinical Trial
    • Quasi-Experimental
  • Field Trial
case report
Case Report

A case report is a detailed report of the symptoms, signs, diagnosis, treatment, and follow-up of an individual patient. A case report may contain the demographic profile of an individual patient, that usually describes an unusual or novel occurrence.

case report1
Case Report

Most case reports focus on:

  • an unexpected association between diseases or symptoms
  • an unexpected event in the course of observing or treating a patient
  • findings that shed new light on the possible pathogenesis of a disease or an adverse effect
case report2
Case Report

Most case reports focus on: (continued)

  • unique or rare features of a disease
  • unique therapeutic approaches
  • a positional or quantitative variation of the anatomical structures
case series
Case Series

A case series is a medical research study very similar in structure and form as case reports, but describes a group of cases, instead of a single patient.

This study design may be retrospective or prospective, and usually requires a relatively small sample size (usually 10 or more).

case series1
Case Series

This design reports the frequency of events or outcomes of a disease, but does not show temporal relationships between events and outcomes.

This study design has case selection bias and lacks statistical validity.

cross sectional study
Cross-Sectional Study

In a cross-sectional study, the variables are all measured at a single point in time, with no structural distinction between predictors (exposure) and outcomes.

It may involve the measurement of current exposure and/or historic exposure.

cross sectional study1
Cross-Sectional Study

This design is valuable for providing descriptive information about prevalence --- it is well suited to the goal of describing variables and their distribution patterns.

cross sectional study2
Cross-Sectional Study

This design may also be used for examining associations, although the choice of which variables to label as predictors and which as outcomes depends on the cause-and-effect hypotheses of the investigators.

cross sectional study4
Cross-Sectional Study

Uses for Cross-Sectional Study:

  • to assess burden of disease in a population and to assess need for health services
  • to compare prevalence of disease in different populations
  • to examine trends in disease prevalence or severity over time
cross sectional study5
Cross-Sectional Study

Strengths of Cross-Sectional Study:

  • allows study of several outcomes simultaneously
  • requires a relatively short duration
  • yields prevalence
cross sectional study6
Cross-Sectional Study

Weaknesses of Cross-Sectional Study:

  • does not establish sequence of events (temporality)
  • need for a large sample size
  • not feasible for rare predictors or rare outcomes
  • does not yield incidence or true relative risk
cohort study
Cohort Study

Cohort studies involve following groups of subjects over time. There are two primary purposes:

  • descriptive: typically describes the incidence of certain outcomes over time
  • analytic: analyze associations between predictors (exposure) and outcomes
cohort study1
Cohort Study

Cohort studies establish sequence of events and can study several outcomes. This study yields incidence and relative risk.

cohort study2
Cohort Study

There are two sub-types:

  • Concurrent / Prospective
    • follows up cohorts from exposure to the occurrence of the effect
  • Non-Concurrent / Retrospective
    • both exposure and effect have occurred prior to the time of investigation
cohort study4
Cohort Study

Incidence Rates:

  • exposed: IRexposed = A ÷ (A + B)
  • unexposed: IRunexposed = C ÷ (C + D)

Relative Risk (RR):

  • RR = (IRexposed) ÷ (IRunexposed)
  • RR = [A ÷ (A + B)] ÷ [C ÷ (C + D)]
cohort study5
Cohort Study

Strengths of Cohort Study:

  • establishes sequence of events (temporality)
  • can study several outcomes
  • yields incidence, relative risk
  • prospective cohort studies avoid bias in measuring predictors
  • retrospective cohort studies are less expensive and have shorter duration
cohort study6
Cohort Study

Weaknesses of Cohort Study:

  • often requires a large sample size
  • less feasible for rare outcomes
  • prospective cohort studies are more expensive and longer in duration
  • retrospective cohort studies have less control over selection of subjects and measurements
case control study
Case-Control Study

A case-control study is a design in which individuals with an event or condition of interest (i.e. cases) are identified and then compared with regard to one or more exposures to individuals without the event or condition of interest (i.e. controls).

case control study1
Case-Control Study

A case-control study cannot yield estimates of incidence or prevalence of a disease, but it can provide descriptive information on the characteristics of the cases and an estimate of the strength of association between predictor variables and the presence or absence of disease.

case control study3
Case-Control Study

Estimates of strength of association are in the form of odds ratio (OR).

OR = (AD) ÷ (BC)

case control study4
Case-Control Study

Interpretation of OR:

  • OR = 1: exposure is not related with disease
  • OR > 1: exposure is positively related with disease
  • OR < 1: exposure is negatively related with disease
case control study5
Case-Control Study

Exposure is determined in a retrospective manner; thus, one must look back in time to assess exposure status before a person developed the disease (and became a “case”).

Ideally, exposure must be measured in a blinded manner,, to minimize bias.

case control study6
Case-Control Study

Types of Bias:

  • Selection Bias
  • This represents a distortion in the relationship between exposure and outcome, that results from selection of study participants.
case control study7
Case-Control Study

Types of Bias:

A. Selection Bias

  • The relation between exposure and outcome is different for those who participate and those who do not participate but would theoretically be eligible for the study.
case control study8
Case-Control Study
  • Information Bias
  • This is a distortion in measuring exposure or outcome data that results in different quality (i.e., accuracy or reliability) or frequency of information between comparison groups.
case control study9
Case-Control Study

C. Recall Bias

  • Differential recall of exposure between cases and controls in a study may be evident.
case control study10
Case-Control Study

Strengths of Case-Control Study:

  • useful for studying rare conditions
  • short duration
  • generally inexpensive
  • relatively small
  • yields odds ratio
case control study11
Case-Control Study

Weaknesses of Case-Control Study:

  • potential for bias and confounding from sampling two populations
  • does not establish sequence of events
  • limited to one outcome
  • does not yield prevalence or incidence
clinical trial
Clinical Trial

In clinical trials, the investigator applies a treatment (termed intervention) and observes the effect on an outcome.

Clinical trials are essentially cohort studies, except that the groups being studied differ from each other only in the presence of a characteristic or exposure to some factor that is artificially induced.

clinical trial1
Clinical Trial

The major advantage of a trial over an observational study is the ability to demonstrate causality.

Clinical trials are considered as the gold standard for studying interventions, specifically, randomized clinical trials.

In clinical trials, biases are minimized but not totally eliminated.

clinical trial2
Clinical Trial

In particular, randomly assigning the intervention can eliminate the influence of confounding variables.

Blinding eliminates the possibility that the observed effects of the intervention are due to other treatments or to biased ascertainment.

clinical trial3
Clinical Trial

Randomization:

  • intervention group – which will receive the experimental treatment
  • control group – which will receive the non-experimental treatment, either placebo or standard method of treatment
clinical trial5
Clinical Trial

There are several variations on the randomized trial design that can substantially increase efficiency, under the right circumstances:

  • matched-pair randomization
  • time-series design
  • cross-over design
clinical trial6
Clinical Trial

Matched-Pair Randomization

This is a strategy for balancing baseline confounding variables that requires selecting pairs of subjects who are matched on important factors like age and sex, then randomly assigning one member of each pair to each study design.

clinical trial7
Clinical Trial

Time-Series Design

In this design, each participant serves as his own control to evaluate the effect of treatment.

Innate characteristics, such as age, sex, and genetic factors, are not merely balanced, but actually eliminated as confounding variables.

clinical trial9
Clinical Trial

Cross-Over Design

Half of the total participants are randomly assigned to start with the control and then switch to active treatment; the other half to do the opposite.

This approach permits between-group, as well as within-group, analyses.

clinical trial10
Clinical Trial

Cross-Over Design

This may control for confounding and minimize the required sample size if carry-over effects are not a problem.

To reduce carry-over effect, untreated wash-out periods may be introduced.

clinical trial13
Clinical Trial

Measures of Effect in Clinical Trials:

  • cure rate
  • relative risk / risk ratio
  • risk difference
clinical trial14
Clinical Trial

Relative Risk (RR):

  • RR = (RiskTreatment) ÷ (RiskControl)

For positive outcome:

  • RR < 1 treatment is harmful
  • RR = 1 no significant difference
  • RR > 1 treatment is beneficial
clinical trial15
Clinical Trial

Relative Risk (RR):

  • RR = (RiskTreatment) ÷ (RiskControl)

For negative outcome:

  • RR < 1 treatment is beneficial
  • RR = 1 no significant difference
  • RR > 1 treatment is harmful
field trial
Field Trial

This design is very similar to clinical trials, except that, interventions in field trials are preventive rather than therapeutic.

field trial1
Field Trial

Measures of Effect in Field Trials:

  • risk ratio
  • risk difference
  • protective value
field trial3
Field Trial

P1: disease rate in experimental group

  • P1 = A ÷ (A + B)

P2: disease rate in control group

  • P2 = C ÷ (C + D)

Protective Value (PV):

  • PV = (P2 – P1) ÷ P2
experimental designs1
Experimental Designs

Strengths of Clinical / Field Trials:

  • the ability to demonstrate causality
  • control over subject selection, actual interventions to be implemented, and define outcome to be measured
  • biases may be diminished (through blinding) but not totally eliminated
experimental designs2
Experimental Designs

Weaknesses of Clinical / Field Trials:

  • generally expensive
  • time-consuming
  • address a narrow clinical question
  • possibility of exposure of subjects to potential harm (adverse effect); need for informed consent
summary
Summary

Epidemiologic research designs are either observational or experimental in character.

Each research design is suited for different objectives and purposes, and each has its own strengths and weaknesses.