Clinical Epidemiology Flashcards
epidemiology
science of distribution and causes of disease in populations
clinical epidemiology
science making predictions about patients using tools of epidemiology
sensitivity
the extent to which the test is accurate for those who have the disease in question, avoiding false negatives
specificity
the extent to which the test is accurate for those who do not have the disease, avoiding false positives
positive predictive value
the extent to which a positive test indicates the presence of disease
negative predictive value
the extent to which a negative test indicates the absence of disease
Receiver Operator Characteristics (ROC)
y-axis (sensitivity- true positives) and x-axis (specificities- false positives)
Where is the most accurate test overall located on the ROC (reciever oerater characteristic) graph and why?
upper left corner becuse test is most specific and sensitive
Label each letter and number
A. Positive for the disease
B. Negative for the disease
C. Positive test
D. Negative test
- Sensibilty; True positives
- False positives
- False negatives
- Specificity; True negatives
prevalence
the probability of having a disease at a given point in time also known as pre-test probability
cumulative incidence
new cases of disease in the population at risk of getting the disease over a period of time; (number of new cases of disease over a period of time)/(number of people at risk of getting disease)
prevelance equation
incidence x average duration
attack rate, mortality rate, and case fatailty rates
types of cummulative incidence
results of a test can/cannot be interpreted correctly without knowing the pre-test probability
cannot
four factors that determine how thresholds are set
- accuracy of test
- risk of test
- seriousness of the illness and the benefit of treatment
- risk of treatment
what would you do if the pre-test probability was below the test threshold
dont test or treat
what would you do if the pre-test probability is above the treat threshold
dont test just treat
risk differences
(incidence of disease in population 1)- (incidence of disesae in population 2)
two types:
Attributable risk and Absolute risk reduction
attributale risk
(incidence in exposed population)- (incidence in unexposed population)
“the risk (incidence) of disease attributable to harmful exposure”
attributable risk percent
(IE(incidence of exposed) - IUE(incidence of unexposed)) / IE
precentage of risk in the exposed group that is attributed to the exposure
absolute risk reduction (ARR)
Ic (incidence of control)- Irx (incidence of treated)
tells us the proportion of patients who were spared an adverse outcome due to treatment
relative risk (RR)
IE/IUE or Irx/Ic
risk of outcome given exposure
relative risk reduction (RRR)
(Ic-Irx)/Ic = ARR/Ic
the amount of risk removed as result of therapoy
number needed to treat (NNT)
the number needed to treat to prevent one outcome
1/ARR = 1/(Ic-Irx)
When risk reduction is equal to one…
the exposure/treatment does not increase or decrease the risk of the disease
When risk reduction is greater than one….
the treatemtn/exposure increases the risk of disease
when risk reduction is less than 1…
the risk of treatment/exposure decreases the risk of disease
p-value
probability of finding an outcome as extreme or more extreme than the one we found assuming the null hypothesis is true
type I error
false positive
type II error
false negative
null hypothesis
there is no difference
