FA 2 Flashcards
epidimiology - RRR AR ARR
Relative risk reduction Attributable risk
Absolute risk reduction
Odds ratio
Odds that the group with the disease (cases) was exposed to a risk factor divided by odds that the group without disease (controls) was exposed
Odds ratio equation (and explanation)
OR=(a/c)/(b/d)=ad/bc = X
the risk of the disease is X times higher for exposed then non exposed in population
Relative risk
Risk of developing disease in the exposed group divided by risk in the unexposed group
epidemiology - RR equation
(a/(a+b))/(c/(c+b))
if prevelance is low –> RR? OR?
RR=OR
RR: greater/lower/=1
=1: no association between exposure and disease
greater: exposure increases the occurrence disease
lower: decreases
Relative risk reduction (RRR)
The proportion risk reduction attributable to the intervention as compared to a control
(how much the risk is reduced by the intervention)
RRR - ex.
2% of patients who received flu shot develop the flu, while 8% of unvaccinated patients develop flu then RR=2/8 = 0.25
RRR=1-RR = 0.75
Attributable risk (AR) - definition example
The difference in risk between exposed and unexposed groups
or,
The proportion of disease that are ATTRIBUTABLE to the exposure
- If risk for lung cancer is 21% in smokers and 1 in nonsmokers, then 20% of the lung cancer risk in smokers is attributed to smoking
Attributable risk (AR) - example
If risk for lung cancer is 21% in smokers and 1 in nonsmokers, then 20% of the lung cancer risk in smokers is attributed to smoking
Relative risk example
21% smokers develop lung ca and 1% of non smoker
RR=21/1 = 21
Absolute risk reduction - definition
The difference risk (not the proportion) attributable to the intervention as compared to control)
Absolute risk reduction example
8% placebo flu - 2% vaccine flu = 6% = 0,6
Number needed to treat (NNT)
Number of patients who need to be to be treated for 1 patient to benefit
1/ARR
Number needed to harm
Number of patients who need to be exposed to a risk factor for 1 patient to be harmed
1/AR
of 200 patients, 50 have lung Ca. Of these, 45 are smokers. Of remaining 150 patients (no Ca) ,60 are smokers –> Odds Ratio
(45/5)/(60/90) = (45x90)/(5x60) = 13.5
The risk of Lung Ca is 13.5 times higher for smokers than in nonsmokers in this population
Accuracy
The trueness of test measurements (validity)
The absence of SYSTEMIC ERROR or BIAS in a test
(How close is the measured value to the true value)
Systemic error - accuracy
Systemic error decreases accuracy in a test
Presicion
-the consistency and reproducibility of a test (reliability)
-the absence of random variation on a test
(How close the values are each to other)
Precision - standard deviation
Increased precision –> decreased standard deviation
Precision - statistical power
Increased precision –> increased statistical power (1-β)
random variation - precision
Random variation decreases precision of a test
interrated vs test-retest precision
- interrated –> similar results when the test is administrated by a different rater or examiner
- Test-retest –> similar results when the sybect is tested as a second or third time
Bias And Study Errors types
- Recruiting participants
- Performing study
- Interpreting results
Bias And Study Errors - recruiting participants
Selection bias
Bias And Study Errors - performing study
- Recall bias
- Measurement bias
- Procedure bias
- Observer-expectancy bias
Bias And Study Errors - Interpreting results
- Confounding bias
- Lead time bias
- length time bias
Selection bias (type and definition)
Type: Recruiting participant bias
Error in assigning subjects to study group resulting in an unrepresentative sample. Most commonly a sampling bias
Selection bias examples
- Berkson bias (from hospitals)
- Healthy worker effects
- Non-response bias
Strategy to reduce selection bias
- Randomization
2. Ensure the choice of the right comparison/reference group
Recall bias (type and definition)
Type: performing study
Awareness of disorder alters recall by subjects. Common in retrospective studies
Recall bias example
Patients with disease recall exposure after learning of similar cases
Recall bias strategy to reduce
Decrease time from exposure to follow up
Measurement bias (type and definition)
Type: performing bias
Information is gathered in a way at distorts it
Measurement bias example
Miscalibrated scale consistently overstates weights of subjects
Measurement bias strategy to reduce
Use objective, standardized and previously tested method of data collection that are planned ahead of time
Procedures bias (type and definition)
Performing study
Subjects in different group are not treated in the same way
Procedure bias example
Patients in treatment group spend more time in highly specialized hospitals units
Procedure bias strategy to reduce
Blinding and use of placebo reduce influence of participant and researchers on procedures and interpretation of outcomes as neither are aware of group allocation
Observer-expectancy bias (type and definition)
Type: Performing study
Researchers belief in the efficacy of the treatment changes the outcome of that treatment (aka Pygmalion effect, self-fulfilling prophesy)
Observer-expectancy bias example
If observer expects treatment groups to show signs of recovery, then he is more likely to document positive outcomes
Observer-expectancy bias strategy of reduction
Blinding and use of placebo reduce influence of participant and researchers on procedures and interpretation of outcomes as neither are aware of group allocation
Bias And Study Errors - Interpreting results
- Confounding bias
- Lead time bias
- length time bias
Comfounding bias (types and definition)
Type: Interpreting bias
When factor is related to both exposure and outcomes, but not to the causal pathway –> factor distorts or confuses effects on outcome
Confounding bias example
Pulmonary disease is more common in coal workers than the general population. However, people who work in coal mines also smoke more frequently than the general population
Confounding bias strategy of reduction
- Multiple/repeated studies
- Crossover studies (subjects act as their own controls –> persons in group 1 receive the drug and group 2 placebo. Later they swich)
- Matching (patient with similar characteristics in both treatment and control groups)
- Restriction
- Randomization
Lead time bias def/example
Early detection makes it seems as though survival has increased, but the natural history of the disease has not changed
Lead time bias strategy of reduction
Measure “back end” survival (adjust survival to the severity of disease at the time of diagnosis)
Length time bias - type and definition
type: interpreting results
screening test detects diseases with long latency period, while those with shorter latency period become symptomatic earlier
Length time bias - example
a slowly progressive cancer is more likely detected by a screening test than a rapidly progressive test
Length time bias - strategy to reduce it
a randomized controlled trial assigning subjects to the sceening program or to no screening
