Case Control Design

7/28/2019 Case Control Design

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Case-Control Studies


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Objectives

1. Describe the case-control study design and therationale for its use

2. Define source population

3. Discuss elements of case and control selection4. List potential sources of cases and controls

5. Describe types of case-control studies

6. Discuss primary design concerns in case-controlstudies

7. List the strengths and weaknesses of case-

control studies


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Primary design issues: selection of cases and controls

collection of accurate exposure data control of extraneous factors


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Rationale for Case-Control Study

Used to answer the same research question as in

cohort studies:

Is the rate/risk of disease among the exposeddifferent than that among the non-exposed? If yes,

in what direction and by how much?

Used as an efficient version of a cohort study

Used to estimate the IDR/CIR with the OR


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Efficiency of a case-control study - example:

Cohort studycalculate rate of disease in the exposed:

population cases P-Y at risk

E 10,000 50 9,975

E 100,000 50 999,75

Total 110,000 100 109,950

IDR = 10.02


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Efficiency of a case-control study - example:

Cohort Design:Diseased (cases) PT

E 50 = A 9975 = C

E 50 = B 99975 = D

Case-control design:

Cases Controls

50 x 1.0 = 50 9975 x .005 ~ 50

50 x 1.0 = 50 99975 x .005 = ~ 500

OR = 10.0 ~ IDRHOW DOES THIS WORK and

does it always work?


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Recall.

OR ~ IDR/CIR when either,

The disease is rare in the population

(prevalence 0.05)

Controls are selected to represent the same

source population that gives rise to the

cases, not just the non-cases


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For valid case-control studies

Cases must be representative of all cases in the

source populationthe same ones who would be

considered cases if a cohort study was done. Controls selected so that their exposure

distribution reflects the exposure distribution

among the person time in the source population,

i.e. the same source cohort (population) as the cases.

Both cases and controls must be selected

independent of exposure status


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Source Population

The Source Population is:

The source of subjects for a particular study

Defined by the participant selection methods of

your study.


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Selection of Cases

Clearly define the source population

Establish strict diagnostic criteria for case definition,

independent of exposure (cases really cases)

Either incident or prevalent cases, but incident are

ideal

Can be selected cross-sectionally (at a point in time) or

longitudinallylongitudinally is a better choice

Can use all cases within the population or a sample of

the population


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Selection of Controls

Without a well defined source population, it

is difficult or impossible to select unbiased

controls.


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Selection of Controls, Cont.

Is critical and can be difficult

Controls must come from the same source population

that gives rise to the cases Controls must have the same exposure distribution as in

the source of the cases

Chosen independent of exposure status, i.e. the same

sampling rate for exposed and unexposed controls

If sample size is large enough, problems due to

sampling error are avoided


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Goal is to choose cases and controls so that their proportion

with the risk factor (E) in the study does not vary much more

than sampling error from the source population.

Example: Cohort study:

Cases Population Person-Time

E 50 = A 10000 9975 = CE 50 = B 100,000 99975 = D

IDR = 50 / 9975 = 10.02

50 / 99975


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Cases PT

E 50 = A 9975 = C

E 50 = B 99975 = D

Cases Controls

E 50 x 1.0 = 50 9975 x .005 ~ 50

E 50 x 1.0 = 50 99975 x .005 = ~ 500

OR = 10.0 ~ IDR

Sampling fraction for cases = 100%

Sampling fraction for controls = .5%


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Sampling Strategies to Select Controls

When selecting the controls we want to minimize

selection bias and maximize the potential for the OR ~~

the RR

If a disease is rare, all sampling strategies will give thesame result (OR ~ IDR/CIR)

If disease is common, different sampling strategies will

give different results

Types of Sampling strategies:1. Traditional (cumulative) sampling

2. Density Sampling


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Types of Case-control Studies Case-based case-control study (traditional):

cases and controls are selected at a given point in timefrom a hypothetical cohort (i.e. at the end of follow-up).

Case-control study within a cohort (hybrid,ambidirectional): Case cohort study: controls are selected from the

baseline cohort.Nested case-control study: controls selected at timewhen each case occurs (incidence density sampling).


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1. Case-Based (Traditional):

Cumulative Sampling Typically, cases identified as diagnosed during

study period from a stated source population

Controls (non-cases) identified from the samesource population from among the non-cases at

the end of the study period (cumulative sampling).

Exposure to the risk factor of interest is

measured/gathered

OR is calculated as an estimate of the IDR/CIR


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Case- Based Case-Control Study:

(cumulative sampling)


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1. Case-Based (Traditional):

Cumulative Sampling Selecting controls from those disease-free at the end of the

observation period during which cases are identified.

Primarily used only when the disease is rare, otherwise OR

doesnt estimate the IDR/CIR

Selecting controls with this method, they do not representthe source population from which cases come, represent

only non-cases (although they do still come from the same

source population).


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1. Case-Based (Traditional) Sampling:

Issues Selection bias may occur when cases and

non-cases are not selected from the same

source population, or populations withsimilar relevant characteristics.

Selection bias may occur if loss to follow

that happens before the study groups are

selected affect their comparability.


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Bias in a case-based case-control study with a cross-sectional

ascertainment: only cases with long survival are included.


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Selection bias in a case-based case-

control study A cross-sectional ascertainment identifies primarily

prevalent cases, that is, those with the longestsurvival. Cases and controls who die before they can

be included in the study may have a different

exposure experience compared with the rest of thesource population.

It is preferable to ascertain cases concurrently, i.e. toidentify and obtain exposure information from cases

as soon as possible after diagnosis. Same rules applyto controls.


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Case-control Studies within a Cohort

Controls may be selected from the baselinecohort, i.e. case-cohort design.

Controls may be selected from individuals at risk

at time each case occurs, i.e. nested case-controldesign.

Likelihood of selection bias diminished witheither approach compared to case-based study

design.


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2. Case-control studies within adefined cohort: Case Cohort

C-C study conducted within the framework of existing,

defined cohort, which becomes the source population

Cases are selected from the cohort (all or a sample) as they

develop Controls are selected by random sample of the total cohort

atbaseline

Controls have potential to become a case

OR ~ CIR, no rarity assumption needed

Selection bias is reduced due to control selection within the

source population


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Case-Cohort Study

Case-control study in which the controls are selected from the

baseline cohort


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2. Case-Cohort Example

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Potential controls: A random sample of the total cohort at

baseline.

Time

X = occurrence of outcome of case control study


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Case-Cohort Example

Cardiac Autonomic Function and Incident Coronary Heart

Disease: A Population-base Case-Cohort Study(AJE1997;145:696-706)

Cohort: Atherosclerosis Risk in Communities Study (4

centers)

Baseline cohort = 15,800 men and women 45-64 years old

Case-cohort sample:

Cases = 137 incident cases of CHD

Controls = stratified random sample of 2,253 examinees free of

CHD at baseline


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2. Studies within a defined

cohort: Nested Case-Control Within framework of existing, defined cohort, the source

population

Controls are a random sample of the cohort (non-cases) at

the time the case occurs

Called incidence density sampling or risk set sampling

Matching on duration of follow-up Controls have the potential to become a case

OR ~ IDR, no rarity assumption needed

Hybrid Design: Nested Case Control study


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Hybrid Design: Nested Case-Control study

the controls are selected at each time when a case occurs

(incidence density sampling).


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Incidence Density Sampling

When a case occurs, a control (non-case) is selected

(controls selected longitudinally)

Matches control to case based on time

Controls have the potential to later become a case

Ensures that controls represent the source population

from which cases come

Rare disease assumption not needed, OR ~ IDR/CIR

for both common and rare diseases using this strategy


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3. Nested Case-Control Example

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Potential controls: individuals at risk of developing Case-

Control outcome at time ti, when a case occurs.

Example: For case #1 (subject 3), all other subjects are potential

controls, even though some of them later become cases

Time

X = occurrence of outcome of case control study


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Nested Case-Control Study Example:

Levels of Maternal Serum AFP in Pregnant Women and

Subsequent Breast Cancer Risk(AJE 1998;148:719-727)

Univ. of Ca. Berkeley Child Health & Development Studies (CHDS)

1959-1994

Cohort of 12,552 pregnant women

Follow-up conducted by using license records from the department of

motor vehicles, and review of death certificates

Nested design

Cases women in the CHDS cohort who developed breast cancer, identifiedthrough the California Cancer Registry

Controls were members of the cohort who had not been diagnosed at that

point in time with breast cancer

Exposure assessment: Frozen sera accrued between 1959-1966

Data analysis: logistic regression


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Advantages of Case-Control Studies

within a Cohort

The estimated exposure odds ratio is a statistically

unbiased estimate of the relative risk since cases

are included in the sampling frame for the

selection of controls.

Efficient when need additional information

(particularly detailed exposure information) thatare not available for the entire cohort.


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Measure of Association for a Case-

Control study: Odds Ratio ORdis = ORexp

There is a built-in bias away from the null

OR can approximate the RR in specific

situations


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Rationale for Case-Control Study

Used to answer the same research question as in

cohort studies:

Is the rate/risk of disease among the exposeddifferent than that among the non-exposed? If yes,

in what direction and by how much?

Used as an efficient version of a cohort study

Used to estimate the IDR/CIR with the OR


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OR ~ RR

Only used when you wantto estimate RR

Rare = disease < 0.10

Most diseases are rare

If controls are selected to represent the

source population

In a case cohort study OR ~ CIR

In a nested case-control study OR ~ IDR


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Primary design concerns with the

case-control design Selection Bias

can occur when cases and controls are not selected from

the same source population When selective survival occurs

Information Bias

can occur when there is bias in the measurement of

exposure resulting in misclassification since exposure is

ascertained after disease has occurred.


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Strengths of Case-Control Design

Less expensive and time consuming than cohort design

Good for studying the etiology of rare diseases

Good for studying diseases with long latency periods

Possible to study many different exposures with

respect to outcome of interest


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Weaknesses of Case-Control Design

Causal inference less clear (temporal ambiguity)

Often cannot estimate the frequency of disease in

a population Insufficient for studying rare exposures

Particularly susceptible to both selection and

information biases

Documents

Case Control Design