Case Control Studies and VTE in Long Distance Travel Flashcards
What is the difference between as cause and risk factor?
Cause
A cause is a factor which, of itself, increases
the risk of a disease occurring
- “An event, condition, or characteristic without*
- which the disease would have been less likely*
- to have occurred”*
- (Kenneth Rothman)*
OFTEN REFERRED TO AS AN “Exposure”
Risk Factor
ANY characteristic which IDENTIFIES a group of
People at increased (decreased) risk of disease,
now or in the future
A risk factor need NOT be:-
- causal
- independent
- modifiable
What are the three types of comparative studies (AKA ‘Analytic’ studies)?
Case control study: Observational
Compares disease cases with non-diseased, did they have different degrees of exposure to the potential cause?
Study involves selecting cases of disease and controls (non-cases) and then studying their previous exposure
Sometimes referred to as a Retrospective Study
Cohort (longitudinal) study: Observational
Compare exposed with unexposed, do they have different risks of developing disease?
Study involves following these groups forward over time, providing disease incidence.
Sometimes referred to as Prospective Study
Randomized controlled trial: Experimental
Also compares exposed with unexposed, do they have different risks of developing disease?
Involves intentionally controlling the level of exposure to a random selection of participants (experimental)
See image for more info…
What is the difference between an observational and an experimental study?
Observational studies do not interfere with levels of exposure, whereas as Experimental studies do.
What are the strengths and weaknesses of Case Control studies?
Strengths of Case Control Studies….
Quick to carry out
Relatively cheap
A good approach where disease is uncommon (studying existing cases is efficient)
Can look at several possible exposures (though only one disease!)
Weaknesses
CCS only provides a relative risk estimate, no measure of incidence/attributable risk
High risk of confounding
High risk of bias (systematic error)
Confounding and bias can happen in both case control studies and in cohort studies, but are particularly likely in a case control study….
What is a confounding factor?
A confounding factor is a factor associated both with the exposure being studied and with the disease outcome, so that it can cause a spurious association
Name two common examples of systemic error in CCS?
And how can they be avoided?
How is a systemic error different from a random one?
Selection bias
In which the selection of either the cases or the
controls (or both) is systematically related to the
exposure being examined (here air travel)
Minimising Selection bias:
Cases and controls drawn from a similar population insofar as possible, and in a way which will not affect their risk of exposure
Information bias
In which the information on exposure obtained from the cases and controls is not comparable and systematically influences exposure assessment
Minimising Information bias:
Ensure information on exposure is obtained from
cases and controls in exactly the same way, both
have the same opportunity to recall exposure
Why is the size of the study important? And what criteria would we use to decide on an appropriate size?
Need to ensure that we design a study big enough to have a good chance of finding an association of expected strength if present – many studies too small (scope for random error)
To decide how big a study….
- How strong an association? (relative risk)
- How common is the exposure?
- What p value will be statistically significant?
- What chance do you want to have of detecting an association if it is really present? (often 80-90%)
What are the advantages of choosing only incident cases as opposed to prevalent cases when doing a CCS?
- Incident cases = newly diagnosed
- Prevalent cases = Established cases
Using incident cases has advantages….
- Closer to causes of disease
- Less chance of exposure changes
- Not assessing determinants of survival
What criteria are important when choosing control subjects?
The ideal control is a person who, were they to develop the disease, would have become a case
- Selection – not related to key exposure (flying)
- Participation – willing to take part?
- Information gathering – can it be same as in cases?
- Confounding – similar confounder exposure as in cases, consider `matching’ to cases
What 4 criteria are important to ensure that cases and controls have equal opportunity to correctly recall exposure?
Give some examples of ways to ensure objectivity and lack of confounding
Objectivity
- Participants should be blind to hypothesis; if an interviewer/observer used, should be blind to hypothesis and case-control status if possible….
- Use an objective assessment method if possible
- Self-administered questionnaire ideal
- Standard protocol, interviewer training etc
To manage confounding at the design stage as effectively as possible…
(Aim here is to make sure that confounding factor is as evenly shared between comparison groups as possible)
- Match each case and control so that level of confounder exposure similar – as in Ferrari study
- Do the whole study in people at the same level of confounder (e.g. for smoking, do the study in non-smokers completely)
The estimate of the relative risk in a case control study is provided by the `odds ratio’ (OR)
How does this work? And what is the formula?
Give four examples of factors that could inhibit any causal interpretation of a positive result:
- Could an association be due to chance?
- Could an association be due to bias?
- Could an association be due to confounding?
- Could there be reverse causation? (presence of disease has affected exposure, or the estimation of exposure)
Give three examples of factors that could inhibit a null association?
- Could the study be too small to detect an association? (limited statistical power?)
- Could the measurement of the exposure have been inaccurate?
- Could the absence of association reflect bias or confounding which have obscured an association?
What is the benefit of ‘Attributable’ Risk as opposed to relative risk, and vice versa?
Relative risk is important for defining causality –
….but not much help as a guide to the
individual in deciding what action to take….
Attributable risk (excess risk) is more helpful for
decision making in the individual patient….
