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Smart designs Case control studies FETP India

Smart designs Case control studies FETP India. Competency to be gained from this lecture Design a case control study

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Smart designs

Case control studies

FETP India

Competency to be gained from this lecture

Design a case control study

Key areas

• Analytical case control studies • Population base of case control studies • Case and control recruitment • Measurement of exposure

Case control study

• Recruitment of: Case-patients affected with a disease Unaffected control-subjects

• Comparison of exposure status• Observation of the in past presence of

one or more potential risk factors

Analytical case control studies

Objective of a case control study

• Case control studies are analytical in nature

• Case control studies compare in terms of exposure status : Case-patients affected by a disease Unaffected control-subjects

Analytical case control studies

Exploratory case control studies

• Risk factors for a disease are unknown • The case control study explores

potential risk factors for further investigation

• Risk of multiple comparisons! If the p value is set at 0.05, every 20 tables

will generate a “significant” association

Analytical case control studies

Case control studies designed to test a limited number of hypotheses

• Risk factors for a disease are better framed Established risk factors Unclear risk factors Possible risk factors

• A limited number of hypotheses are examined Unclear risk factors Possible risk factors

• Ideal situation from a methodological point of view

Analytical case control studies

Elements defining a case control study

• Study participants Selected on the basis of their disease status

• Logic Retrospective examination of potential

exposures

• Logistic Prospective Retrospective

Analytical case control studies

Cases Controls Total

Exposed a b -

Non-exposed c d -

Total a+c b+d -

Presentation of the data of a case control study in a 2 x 2 table

Analytical case control studies

All case control studies come from a theoretical cohort

• Cohorts follow exposed and unexposed subjects for the development of illness

• Cases and controls can be thought of as extracted from a theoretical cohort in which they are “nested”

• Thinking of case control studies as nested in a theoretical cohort help investigators in designing them appropriately

Population base

Representation of a cohort study

One year

Study subject developing the illness

Study subjectcensored

Study subject followed up

Observation

Legend

Nesting a case control study in a cohort for

a disease with a one year referent exposure period

Case

Control

Legend

Case control study with two cases and three controls

Population base

Time comparability of cases and controls

• Cases have an onset date• Controls have no onset dates

The need to identify a referent exposure period is less obvious

Controls must nevertheless be observed over a referent exposure period that needs to be clarified

Population base

Characteristics of the two cases and three controls

• Come from the same population

• Can be exposed the same way

• Can develop the disease the same way

• Could have been identified as cases the same way

• Have identical exposure windows

Population base

Case Control Total

Exposed a.f1 b.f2 N/A

Non exposed c.f1 d.f2 N/A

Total C1.f1 C0.f2 N/A

Impossibility to calculate a relative risk in a case control study

Cases are sampled from all cases (sampling fraction: f1)

Controls are sampled from all controls (sampling fraction: f2)

f1 and f2 are unknown, risks cannot be calculated Population base

Unexposed and exposed study subjects in the cohort Legend

Subject exposed

Subject unexposed

a= ?

b= ?

c= ?

d= ?

ill Non-ill Total

Exposed 1 2 3

Non-exposed 1 4 5

Total 2 6 8

Presentation of the data of the analytical cohort study in a 2 x 2

table

Relative risk = (1/3) / (1/5) = 33% / 20% = 1.7

Population base

Sampling fraction for cases and controls in the example Legend

Subject exposed

Subject unexposed

f1 =

f0 =

Population base

Case Control Total

Exposed 1x1=1 2x0.5=1 N/A

Non exposed 1x1=1 4x0.5=2 N/A

Total 2x1=2 6x0.5=3 N/A

Calculation of the odds ratio in a case control study

Odds ratio = (1x2) / (1x1) = 50 / 100 = 2Higher than the relative risk? Why?

The disease is not rare! Attack rate: 25%Population base

Prospective case control studies

• Identification of cases prospectively Surveillance Recruitment in a health care facility Recruitment with health care providers

• Recruitment of controls prospectively • Investigators look at exposure

retrospectively

Population base

Retrospective case control studies

• Identification of cases retrospectively Surveillance data Health care facility registers Case records

• Recruitment of controls retrospectively • Investigators look at exposure

retrospectively

Population base

Specific case control study designs

• Truly “nested” case control studies Set of cases and controls identified

prospectively from a cohort to obtain intermediate results

• Case-cohort studies Cases obtained from surveillance data Controls selected from a cohort study

Population base

Case definitions in case control studies

• Person Signs and symptoms Biological criteria Demographic characteristics

• Time Time of onset

• Place Place of residence

Cases and controls

Control recruitment strategies in case control studies

• Population based Sampling of the general population Random digit sampling

• Health care facility based Hospital based Patients with other diseases

• Case-based (Beware of matching) Friends Neighbourhood

Cases and controls

Defining the recruitment strategy in case control studies

• Person Signs and symptoms (or absence of…) Biological criteria

(e.g., susceptibility) Demographic characteristics

• Time Referent exposure period

• Place Place of residence

Cases and controls

Collecting good data on exposure

• Objectively Reproducibility of exposure measurement

• Accurately Information reflecting as closely as possible

the effect of exposure

• Precisely Quality management in exposure

measurement

Exposure

Measuring the dose of exposure

• Dichotomous exposure measurement Exposed / unexposed

• Measurement of the dose of exposure Accurate measurement of the dose of

exposure(e.g., Cumulated number of cigarettes smoked)

Exposure categories Dose / response effect

Exposure

Understanding the basic relation between exposure, time and

outcome when designing a case control study

Exposure

Outcomes(e.g., Disease)

Time

Referent exposure

period(Time during which

exposure occurs)

Time at risk for exposure effects

Exposure

Take home messages

• Case control studies refine or test hypotheses

• Case control studies come from cohorts• Case definition and control recruitment

are the keystone of the design • Information on exposure is collected

retrospectively