HTLH 207 Week 6 Asynchronous Work (ONE)

Controls

group of individuals who should be selected from the same source population as the cases, and who should provide an estimate of the frequency of exposure(s) in the source population

3 main sources from which to select controls

1. Population-based controls

2. Hospital and clinic based controls

3. Relatives, neighbors, or friends of cases

Population-based controls

 occurs in primary base studies and is the most robust approach to identify controls

Population-based controls method

Investigators have access to complete list of the source population, which is often defined by a geographic area

Advantage of population-based controls

frequency of the exposure(s) among controls randomly selected from a population-based roster should be similar to that of the entire source population

2 disadvantages of population-based controls

1. May not always be feasible

2. Individuals selected from a population-based roster may be less likely to agree to participate in a research study than those identified via other approaches

Hospital- and clinic-based controls

When cases are identified at a healthcare facility, investigators may enroll hospital- or clinic-based controls

Source population in hospital- and clinic-based controls

The source population is conceptualized as a group of individuals who would be treated at a particular facility if they were to develop the outcome of interest

Control group in hospital- and clinic-based controls

It is assumed that the control group would receive treatment at the same facility as the cases if they actually had the outcome of interest

2 advantages of hospital- and clinic-based controls

1. May be easier to find, more motivated to participate than controls recruited using other methods

2. May be more similar to cases than population-based controls on confounders

Limitation of hospital- and clinic-based controls

These controls may not accurately represent the frequency of exposure in the source population

Relative, neighbors, or friends of cases method

In instances where population-, hospital-, or clinic-based controls cannot be identified, relative, neighbors, or friends of the cases may be selected as a control group

3 advantages of relative, neighbors, or friends of cases method

1. Do not have to enumerate the source population

2. May be more motivated to participate given the social connection to cases

3. May be more similar to the cases on confounders

2 limitations of relative, neighbors, or friends of cases method

1. Reliance on cases to provide contact information for potential controls

2. Frequency of exposure(s) among these controls group may be more similar to the cases than to the source population due to proximity

Defining feature of a cohort study

a group of individuals who are at-risk for the outcome of interest are followed over time to see who develops the outcome of interest

What changes if historical data is used to conduct a cohort study?

the underlying structure is the same

Outcome frequency in cohort studies

Outcome frequency can be measured in all types of cohort studies

3 characteristics of case-control study that is different from cohort study

1. Does not follow a cohort of at-risk individuals over time

2. First classified by outcome status

3. Outcome frequency cannot be estimated using case-control data

Matching

occurs when investigators select controls who have specific attributes that correspond to those of the cases

Requirements of matching attrivutes

must be factors that are likely to be confounder of the relationship between exposure and outcome

Confounders

factors that are associated with both the exposure and the outcome and may partially or completely explain an observed exposure-outcome association

What happens (in terms of data analysis) if confounders are ignored?

EOR will be biased or incorrect

What happens in terms of matching once a case is identified?

Once a case is identified, investigators may seek to identify a control or set of controls that has (have) the same matching factors characteristics (i.e. age) as the case

4 types of matching

1. Pair-matching

2. Exact matching

3. Category matching

4. Caliper matching

Pair-matching

occurs when one control is matched to each case while n-to-one matching means more than one control is matched to each case, where n is the number of controls

Exact matching

matching on the exact same value of the matching factors; however, this may be challenging for certain factors

Example of exact matching

exact matching on age and sex means a 36-year-old female case is matched to a 36-year-old female control

Category matching

mutually exclusive categories for the matching factor are identified and a control is selected that falls in the same category as the case

Caliper matching

controls with a value within a specified range of the case are identified

Advantage of matching in case-control study

Control for the confounding by the matched factors

2 limitations of matching in case-control study

1. More difficult to identify controls for inclusion in the study

2. Can be time-consuming and costly because investigators must identify and recruit controls who have the specific characteristics required to be matched to a case

What happens to a factor once it is matched on?

Once a particular factor is matched on, it can no longer be considered as a potential exposure because matching has forced the cases and controls to have the same frequency of the matched factor

How is the data layout fro a pair-matched case control study different from an unmatched case control study?

each cell represents the number of pairs with a given exposure pattern

Label the following case control 2×2 table

1. Exposure status of the case

2. Exposure status of the control

3. Exposed (E+)

4. Unexposed (E-)

5. Exposed (E+)

6. Unexposed (E-)

7. W

8. X

9. Y

10. Z

W (on case-control 2×2 table)

both the case and control are exposed

X (on case-control 2×2 table)

the case is exposed and the control is unexposed

Y (on case-control 2×2 table)

the case is unexposed and the control is exposed

Z (on case-control 2×2 table)

both the case and control are unexposed

2 exposure patterns/statuses

1. Concordant

2. Discordant

Concordant exposure pattern

the exposure status is the same for the case and control (W and Z)

Discordant exposure pattern

the exposure status is different for the case and control (X and Y)

What can we evaluate when the exposure status of the case and control are concordant?

we don’t gain any information to evaluate the relationship between the exposure and outcome

What can we evaluate when the exposure status of the case and control are discordant?

e can evaluate whether there is an association between exposure and outcome

Pair-matched odds ratio (mOR)

ratio of discordant pairs: X/Y

Pair-matched odds ratio (mOR) null value

1

What can we conclude if the pair-matched odds ratio is greater than 1?

there are more pairs where the case is exposed and the control is unexposed

What can we conclude if the pair-matched odds ratio is less than 1?

there are more pairs where the case is unexposed and the control is exposed

Interpretation structure for pair-matched odds ratio

After controlling for the matching factors, the odds of exposure among cases is [pair-matched OR] times the odds of exposure among control

3 strengths of case control designs

1. Allows for the study of multiple exposures, which is particularly useful for outbreak investigations or when the cause of an outcome is unknown

2. Well-suited for studying rare outcomes, outcomes with long latency periods, exposure-outcome relationships with long inductions periods, and outcomes that have already occurred

3. Investigators can obtain the estimate of the frequency of exposure in the source population without having to measure exposure on the entire source population, and thus these studies are generally smaller, less resource intensive, and quicker

4 limitations of case control designs

1. Inefficient for the study of rare exposure because a very large number of cases and controls would be required

2. Since the sample population is selected based on outcome status, case-control studies are not suitable for the study of multiple outcomes

3. Not possible to directly estimate outcome frequency

4. May not always be possible to establish temporality in a case-control study