All Topics Flashcards
Definition of incidence of a disease
– The rate at which new cases occur in a population at risk during a specific time period – The measure of the populations average risk of disease
Definition of prevalence
The proportion of a population who have a disease at a specific moment of time (Lowered by death and cure)
Define the relationship between incidence and prevalence
Prevalence = incidence x mean duration of disease
How do you compare the incidence in two different groups?
Incidence rate ratio
How do you interpret the incidence rate ratio?
IRR = (8/40000) / (3/30000) = 2Therefore, you are 2 times as likely to die in an exposed region than in the unexposed region
What is a confounding factor?
A factor which is linked to both the outcome and the exposure but is not on the causal pathway
How do you deal with confounding from age and sex?
Use a standardised mortality ratio or standardises morbidity ratio
Define variation
Difference between the observed value and the actual value
What allows for variations?
Error factors
What are confidence intervals?
The values between which we are 95% confident that our actual value lies between
How do you obtain confidence intervals?
- Calculate incidence rate/incidence rate ratio/SMR2. Calculate error factors3. Calculate confidence intervals 4. Interpret confidence intervals
How do you calculate confidence intervals?
Upper bound value = value x error factor Lower bound value = value/error factor
Interpreting a 95% confidence interval when null lies within values
– is null hypothesis within CI (Yes)– are 95% confident that the true value lies within values as it includes the null hypothesis– p>0.05– cannot reject the null hypothesis– results are not statistically significant
Interpreting a value that lies outside the CI
– null hypothesis within CI (no)– 95% certain that true value lies within CI which does not contain hull hypothesis value – p
What does the rate measure?
Absolute risk
What does a ratio measure?
Relative risk
What does a p value
Data is not due to chanceSubstantial evidence against null hypothesisShould reject null hypothesisObservations are statistically significant
What does a p-value > 0.05 signify?
Data is due to chanceNo evidence to reject null hypothesis (can’t accept though) Results are due to chanceObservations are not statistically significant
What is bias?
The deviations of results from the truth via certain processes
What is selection bias?
Error due to systematic differences in the way that the data was collected – allocation bias– healthy worker effect – non-random sample of the population
What is information bias?
Bias due to measurement errors– recall bias – publication bias
What are cohort studies?
Recruit disease-free individuals and classify based on their exposure. Follow up for extended periodsCalculate incidence rates
Advantages of cohort studies
- Compares outcomes based on one exposure2. Can study a range of outcomes for each exposure3. Limits bias4. Measures incidence directly 5. Establishes that exposure precedes the outcome 6. Good for rare exposures
What are the types of cohort studies?
Prospective – recruit disease free individuals then follow upRetrospective – calculate exposure status from historical records then follow up
Disadvantages of cohort studies
- Expensive – large sample sizes2. Not good for rare diseases3. Time consuming4. Prone to losses to follow up
What are the benefits and disadvantages of retrospective studies?
Are quickerMore likely to be affected by confounding
What type of comparisons can you have with cohort studies?
Internal and external
What are the differences between internal and external cohort studies?
Internal has sub-cohorts within the original cohort and you compare an exposed group with an unexposed group e.g. Gulf war syndrome in army vets External compares the cohort with the rest of the population – uses SMR to remove co founders
What is a case control study?
Identify cohort on basis of disease (cases) Identify a cohort of controls who do not have the disease (controls)Compare the exposure status of both the cases and the controls
How do you analyse case control studies and how do you increase the precision of it?
Odds ratio– increase the number of controls up to five per case
Advantages for case control studies
- Good for rare disease but not rare exposures2. Quicker to perform so are cheaper3. Can study multiple exposure for one disease4. Can do nested case control studies (case control within cohort)
How do you calculate the odds ratio?
Exposed cases X unexposed control/ exposed control X unexposed cases A x D/ B x C
What is a nested case control?
A case control study within a cohort study – calculate incidence rate
What is the definition of Bradford Hill’s Criteria?
Minimum conditions needed to establish a causal relationship between two items
What are the nine Bradford Hill’s Criteria?
- Strength of association - stronger association = more likely2. Specificity of association - only with specific factor3. Consistency of association - observed in different studies4. Temporal sequence - exposure proceeds outcome5. Dose response - different levels of exposure lead to different risk of getting outcome 6. Reversibility - removing exposure reduced risk of outcome7. Coherence of theory - association conforms with current knowledge8. Biological plausibility - biologically plausible mechanism is demonstrated 9. Analogy - analogy exist with other disease (similar disease has similar outcome)
Define clinical trial
Planned experience involving patients to find the most appropriate method of treatment for future patients with a given medical condition
What is the difference between controlled trial and cohort study?
Controlled trial – investigator does somethingCohort study – investigator observes only
Purpose of a clinical trial
Provide reliable evidence of treatment efficacy and safety
What are the requirements of a clinical trial?
Must be fair, controlled and reproducible– gives a fair comparison of safety and efficacy
How can two factors be linked?
Due to:1. Unknown confounders2. Common cause3. Reverse causality (think X causes Y but really Y causes X)4. True causal association