Class 20-21 Flashcards
(17 cards)
Case-Control Studies
Observational studies allowing researcher to be a passive observer of natural events occurring in individuals with the disease/condition of interest (Cases) who are compared with people who do not have the condition of interest (controls)
The Control group supplies information about the expected baseline risk-factor profile in the population from which the Cases are drawn
Useful with studying a rare disease or investigating an outbreak
Commonly generates an odds of exposure for each, then an Odds Ratio (OR) as a measure of association
***Researchers are NOT forcing people into groups
How are group-assignments made in Case-Control Studies?
Group-assignments are based on DISEASE STATUS; presence or absence of disease
Reasons to select a Case-Control design
1) Unable to force group allocation (‘randomize’)
- Unethical/Not feasible
2) Limited resources
- Time/Money/Subjects
3) The disease of interest is rare in occurrence and little is known about its associations/causes
4) Prospective exposure data, derived from prospective Cohort study, is difficult/experience to obtain and/or very time appropriate
Case-Control studies are customarily conducted in a RETROSPECTIVE fashion (we already know the outcomes, that’s how we put ppl in groups)
Strengths of Case-Control Studies
- Good for assessing multiple exposures of 1 outcome
- Useful when diseases are rare
- Useful in determining Associations (NOT Causation)
- Less expensive (money/time) than Interventional trials and prospective Cohort studies
- Useful when ethical issues limit Interventional studies
- Useful when disease has a long induction/latent period
***Weaknesses of Case-Control studies may be the opposite of these general points listed above
Selection of Cases
Defined by the investigator using accurate, medically-reliable, and efficient data sources
-Applied to all study participants
~Objectively, Consistently, Accurately, and with Validity
~Clinically-supportable/definable criteria are best!
**from published, professionally-recognized and accepted diagnostic criteria and/or from multiple sources of data
***Labeling patients CORRECTLY is ideal, but always-present is the risk of “misclassifying” subjects (into wrong group)
Counterfactual theory
All else being equal (in the same group), the outcome if something DIDN’T occur
Counterfactual outcome for Smokers estimated by Non-Smokers (surrogate representative group)
- requires assumption of Exchangeability - exchangeability=comparability
Control selection
Most difficult part***
Control selection: Goal
To assess for the presence of an association between exposure and known condition of interest by selecting non-disease individuals from the same population which produced the Cases
-Expectation is the Controls represent the baseline risk of exposure in general or reference population
The way the controls are selected is a MAJOR DETERMINANT in whether any conclusion is valid:
~Internal validity
~Selection bias
How to select the Control study population
Make groups as close as possible EXCEPT the presence of the disease (outcome) of interest
-If exposure truly has no effect, then odds will be exactly the same for both groups and OR will be 1.0 (no difference)
- Controls must be selected irrespective of exposure status!*
- blinders, we don’t know who is exposed
Control group can come from several sources
1) ‘Population’ (State/Community/Neighborhood)
- Can be obtained via numerous avenues, even RANDOMLY!
2) Institutional/Organizational/Provider
- Illness(es) of controls should be unrelated to exposure(s) being studied
3) Spouse/Relatives/Friends
- Genetic, Environmental, Socio-Economic, etc…similarities
4) Outbreak-sources of Controls:
- Participated in same event (ex: picnic, convention)
Being Exposed & Unexposed
*An individual can actually function as BOTH an exposed individual AND an unexposed individual in the SAME STUDY
Can be associated with an outbreak investigation with multiple exposures, OR….
In a situation of brief (acute) change in risk of the outcome of interest (hazard period, aka flu season)
This is called a ‘Case-Crossover’ design
- Type of Observational Design
- Subjects are their own controls during the other times they don’t have the acute change in risk
- The only Case-Control design able to adequately attempt to address issue of “temporality”
Nested Case-Control Studies
Studies conducted after, or out of, a prospective Cohort study
Subjects in Cohort study ultimately developing disease are defined as Cases for the subsequent Case-Control study
- Diseased used in a new (different) study
- Used to evaluate other exposures
Selection of Controls used for Nested Case-Control studies or when ‘sampling’ necessary from Cohort (source population)
1) Survivor sampling
- Sample of non-diseased individuals (survivors) at end of study period
2) Base sampling
- Sample of non-diseased individuals at start of study period
3) Risk-Set sampling
- Sample of non-diseased individuals during study period at same time when Case was diagnosed
Common Biases in Case-Control
1) Selection bias is related to the way subjects are chosen for study (usually more of a concern for Control selection)
- Less concern during Case-Crossover study designs
2) Recall bias is related to the amount/specificity that Cases or controls recall past events DIFFERENTLY
- More-commonly Cases more likely to recall past exposures and levels of exposure (or their timing)
Matching
In some studies, Cases are matched to Controls (in a 1:1 or higher, ratio)
Individual matching or Group matching
Individual matching
Matches individuals based on specific patient-based characteristics
Useful for controlling confounding characteristics
Group matching
Proportion of Cases and proportion of controls with identical characteristics are matched
Requires Cases to be selected first
Example: 41% Cases are male, so 41% of controls are male
DON’T MATCH ON ANYTHING THAT MIGHT BE A RISK FACTOR!!!!
