Biostats Flashcards
Measures the frequency of disease at a particular point in time
Cross-sectional study
*Only established prevalence, not causality
Measures the frequency with which twins develop the same disease
Twin concordance study
-Pretty self-explanatory
Clinical Trial Phases
I- Is it safe? (toxicity, pharmacokinetics)
II- Does it work? (treatment effficacy, ADRs)
III- Is it as good or better? (compares)
IV- Can it stay? (rare or long-term effects; “post-distribution surveillance”)
Odds Ratio
OR= ad/bc (a/c)/(b/d)
Represents the odds that the group with the disease was exposed to a risk factor DIVIDED BY the odds that the group without the disease was exposed
Relative Risk
RR= [a/(a+b)]/[c/(c+d)]
Represents the risk of developing disease in the exposed group DIVIDED BY the risk in the unexposed group
Example= If 21% of smokers develop lung cancer vs. 1% of nonsmokers, RR=21/1
Attributable risk
AR= [a/a+b]-[c/c+d]
Represents the difference in risk between exposed and unexposed groups
or the proportion of disease occurrences attributable to exposure
example= if risk of lung cancer in smokers is 21% and risk in nonsmokers is 20%, AR= 20%
Relative Risk Reduction
RRR=1-RR
Represents the proportion of risk reduction attributable to the intervention as compared to control (1)
Example= If 2% of pts. who receive a flu shot develop the flu while 8% who don’t develop the flu, then RR=2/8=.25 and RRR=1-.25=.75
Absolute Risk Reduction
AFF= c/c+d - a/a+b
Represents the difference in risk attributable to the intervention as compared to the control
Example= If 8% of people who receive a placebo vaccine develop the flu while 2 % who receive a flu vaccin due, ARR= 8%-2%= 6%
Number needed to treat
NNT=1/ARR
Represents the number of patients who need to be treated for 1 patient to benefit
Number needed to harm
NNH= 1/AR
Represents the number of pts. who need to be exposed for 1 patient to be harmed
Berkson bias
Study population selected is less healthy than the general population
Is a form of selection bias
Confounding bias
When one factor is related to both exposure and outcome but no on the pathway =» distortion of observable effect of exposure
Example= Coal miners more commonly have pulmonary disease BUT they also more frequently are smokers
Fix? - Multiple studies, crossover studies
Standard Error
SE= SD/n^1/2
Represents an estimate of how much variability exists b/w the ample mean and the true population
Ways to decrease Type II error
Increase sample size
Increase expected effect size
Increases precision of measurements
Confidence interval calculation
CI= mean +/- Z(SE)
95% CI, Z=1.96
99% CI, Z= 2.58
What happens to calcium concentrations in alkalosis?
They decrease due to increased protein binding to Ca2+
Lymphatic drainage of the leg
Lateral foot and posterior leg =» Popliteal nodes
Medial foot and leg =» Superficial inguinal nodes
GLP-1 analogs
Exenatide, Liraglutide
- Increase insulin and decrease glucagon release
- Can only be used in Type II DM
