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Observational Studies and RCT. Libby Brewin. What are the 3 types of observational studies?. Cross-sectional studies Case-control Cohort. Cross-Section Studies. How many people are diseased right now? Can calculate prevalence. Case Control Studies. Retrospective study
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Observational Studies and RCT Libby Brewin
What are the 3 types of observational studies? • Cross-sectional studies • Case-control • Cohort
Cross-Section Studies • How many people are diseased right now? • Can calculate prevalence
Case Control Studies • Retrospective study • Identifies groups of cases & non-cases (controls) • Ascertains previous exposure status of cases & controls and compares the level of exposure in both groups • Can compare prevalence of risk factor between the 2 groups Exposed? Cases (diseased) Time Controls (not diseased) Exposed?
Nested Case Control Studies • ‘Nested’ within a cohort study • Collection of data before disease has developed (from pre-existing records or biological samples) *Healthy as disease hasn’t developed. • Advantages over conventional case control: • Incidence rates can be calculated • Population for sampling of controls already defined • Recall bias eliminated as data obtained before disease has developed Time ‘Controls’ ‘Cases’
Cohort Studies • Prospective studies • Identifies groups of exposed and non-exposed • Follows them over time to determine incidence of becoming diseased • Measures frequency of occurrence of the disease in exposed & non-exposed
Historical/Retrospective Cohort Studies • Recruit disease-free individuals and classify them according to their exposure status from historical records
Randomised Controlled Trials • Interventional study • What sort of things need to be considered when designing a RCT?
RCTs • What is meant by the term ‘randomised’? • A random allocation of treatment. There is an equal chance of receiving the treatment & the placebo. • Why should RCTs be randomised? • -Minimise selection (allocation) bias • -Minimise confounding: known & unknown confounders are distributed equally between the groups
RCTs • What is meant by the term ‘control? • A control group has the ‘standard’ treatment or a placebo against which the experimental treatment is compared. • What is a placebo? • An inert substance which looks, tastes and is packaged identically to the comparison drug. • What is the placebo effect? • The psychological benefit from being looked after better or from being on a new special treatment, even if the treatment is not effective or if no treatment is given.
RCTs • What is single blinding? • When the patient doesn’t know the treatment allocation. • What is double blinding? • When 2 out of the patient, clinician and/or assessor doesn’t know the treatment allocation. • Why are RCTs blinded? • Minimises bias: -Clinician may alter other treatment -Patient may change behaviour & expectations (placebo effect) -Assessor may alter approach when assessing outcomes (information or measurement bias)
RCTs • What is clinical equipoise? • Reasonable uncertainty about which treatment (including non-treatment) is better. • What are the important aspects of informed consent? -Explained what the alternative treatments are (side effects) -That the treatments will be allocated at random -That patients may withdraw at any time -Information given verbally & in writing by a knowledgeable informant with a ‘cooling off’ period
2 ways to analyse RCTs: • Explanatory Trial: ‘As-treated’ analysis: only analyses data of those that completed the treatments VS • Pragmatic Trial: ‘Intention to treat’: ignores whether patient took the drug or not (real life situation) Take new treatment As-treated analysis New treatment Didn’t take treatment Take control treatment Intention to treat analyses Standard Treatment Didn’t take control treatment
Significance • What is the difference between results being statistically significant and clinically significant? • It is possible to get treatment effects that are statistically significant but are so small that they are clinically insignificant i.e. no worthwhile benefit to the patient.
ESA Style Questions • A cohort study is designed to look at the association between exposure to an industrial solvent and the development of hypothyroidism. Give TWO strengths and TWO weaknesses of cohort studies Strengths: -Can monitor multiple outcomes from one exposure -Good for rare exposures -Can measure incidence (IRR) Weaknesses: - Expensive, long follow up -Loss to follow-up: survivor bias -Useful for rare diseases
A case control study of cot deaths or sudden infant death syndrome (SIDS) studied the association of SIDS with coffee drinking in mothers. • State the null hypothesis. No association between coffee drinking and cot death (OR = 1) • 2. Explain what a case control study is in this context. Starts with cases who have had a cot death and a control group without a cot death, and then look back at exposure to coffee drinking in pregnancy, and compare this for cases and controls.
The odds ratio for cot death in infants of mothers who were heavy coffee drinkers during pregnancy (4 cups / day) was 2.4 with 95% CI of 1.2 to 6.0. Interpret these findings, in relation to the null hypothesis. -Exposure to heavy coffee drinking in pregnancy was 2.4 times higher in cases that controls. -The 95% CI indicates that that we are 95% confident that the true underlying OR could be between 1.2 (i.e. just above the null hypothesis) and 6 fold higher. -The CI does not include 1 (the null hypothesis), and thus we can reject the null hypothesis at the 5% level. -There is a statistically significant association between SIDS and heavy coffee drinking (p<0.05).
Other than chance, what other factors would you have to consider when interpreting these results? • Bias – Selection Bias i.e. how were the controls selected ? • Information Bias – recall bias in case control studies. • Confounding – Smoking and social class may be related to both the exposure (coffee drinking) and the outcome (SIDS) and may account for the association seen between coffee drinking and SIDS. • How can confounding be reduced? • -Matching the population for sex, age etc. at selection • -Adjust for effect in regression analysis