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Experimental studies/ intervention
Phase 1,2,3,4
drug development and drug approval
Observational studies
descriptive studies e.g. case reports, case series
secular trend analysis: look at how disease trends change over time
cross-sectional studies
drug utilisation
Analytical studies
cohort studies: cohort, large simple, registries
case control studies
examples of under representative patient groups
women, pregnant
children
alcoholics
What is an observational study
Non-experimental
No risk to patients
No control over exposures assigned but can select subjects
Cohort study
Recruit people in a population without the disease (without the disease of interest)
collect exposure information (some people do, some don’t)
collect information on incident outcome
Follow up
analysis is split into exposed vs not exposed
Find risk ratio: exposed/unexposed
What does exposure mean
exposure of interest
e.g. alcohol intake some don’t drink, some drink more in different seasons
misclassification may lead to underestimate or overestimate
Outcomes design
outcome of interest needs to be clearly defined
length of follow up
how many years do we run the study
what about people lost to follow up, bias
Misclassification
Non-differential: to the same degree for all groups
Differential: misclassification applied to one group
misclassification of the wrong patient group
What are covariates
other variables that may influence the results of the study e.g.
age
gender
other diagnoses
other medication
smoking, BMI, socioeconomic status
What is confounding
an external factor than can influence the variables in the study
can lead to bias
have to evenly distribute population
Channelling
a type of selection bias that occurs when patients with different prognoses or risk factors are disproportionately assigned to different treatments within a study
How can we control confounding
randomisation : even distribution
restriction
matching: match exposure vs non-exposed group
Stratified analysis
multivariate analysis: –Takes into account a number of factors simultaneously