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93 Cards in this Set

  • Front
  • Back
define epidemiology
atudy of occurence and distribution of diseases in POPULATION
clinical approach vs publich health approach

epi is a metho of which one?
clinical- individual level

public health- studies disease at population

epi is method of public health-pop.
epi's 3 factors
define environment
all other factors inhibit OR promote disease transmiss.
obvious ones, then u got genetic traits, chemicals, radiation
some of the host factors
personal behaviors
immunization status
physicologic states(preg) puberty
environmental factors
physical-weather, geology

biological-food, water, air

social + cultural- crowding, war
what did epidimiologist start out focusing on?

what are they focused on now
in past- infectous diseases

now-chronic diseases
infectous diseases are characterized by
single, known identifiable cause
pharmaco-epi studies what
drug use patterns, drug use effects, and adverse drug effects
whats whats diff in adverse event and adverse drug reaction
adv event- error while pt is taking med, but doesn't necess. mean it caused event

drug reaction- outcome thats harmful or unpleasent-theres a casual link to drug
define side effect

medication error
S.E- dose dep effect predicatble + maybe desirable or undesirable

Med Errrr-any preventable event may cause harm to pt
FDA uses what to approve new drug

Clinical trials

1-determines safety
2-small group-for intended pts, tests efficacy
3-thousands of pts, RCT, 1-4 yrs
limitations of clinical trials
only studies on hundreds/thousnads of ppl-rare SE will show later

can't see long term effex

decay effect
efficacy vs effectivness
whats decay effect?

efficacy vs effectivness?
decay-overtime effect decre. -trial can't show this

efficacy- intended effect doesn't necessarily have effectivness (out of study ppl will have compliance issues) 15 tabs/day
define postmarketing surveillance
needed to see long term effects of drugs

means of gathering data about product after approval
T or F
some drugs need to do phase 4 clinical trials AFTER approval
examples of pharmacovigilance
medwatch-info on serious SE reported by HCP

VAERS- vaccine A.E.
define pharmacovigilance
science of detecting, assessing, and preventing A.E. of meds
whats ultimate goal in establishing relationships between drugs and outcomes
establishin a casual relationhip (casuality)
whats criteria for causality
1) correlation-consist pattern of change
2) temporal ordering
3)rule out alternative explanations
whats internal validity
approx truth of inferences for cause-effect relationships
what kind of variable is independent
predictor- its variable being manipulated durr
what kind of varibale is dependent
outcome -whatever result of changing indep durr again
define confounding
extraneous varibale that correlates with indep and dep variable (unforseen correlation factor)

need to control for this
type 1 error
false positive
null is true but reject null
type 2
false negative
null is false but accept null
define sampling
selecting units(ppl) from population so you can later generalize results back to population
random selection
different units are selected by chance
parameter vs statistics
para-mean if you were able to sample entire POPULATION

statistic- value estimated from sample data
obsv vs experiment study
obsv-no intervention or exp

exp- manipulation of factor(exposure) and randomization of ppl
in regards to data collection
define primary

define secondary

give examples
primary-investigator is 1st to collect info
-medical exams, interviews, observations

seondary- data collected by OTHERS of other purposes than study
-medical/employ records, census data
define a study design
translate conceptual hypothesis into operational one
goal of study may be? (3)
exploratory- when knowledge is poor, small scale

descriptive-from hypothesis, ex-cross sect, case study

analytical-test hypotheses, ex case control, RCT, cross sect.
spectrum for causality
estab. cas-----Gen hypothesis
RCT>Cohort>casecontrol>cross sect.
observational design-

alt to exp design, good for drug use patten+ outcome-S.E.

1)case report-clinical exp of 1 pt on drug
2)case series- same but mult. pts
case series are of value cuz they
study cases of similar disease
and give clinical education, audit and resarch value
give an example of case series mentioned in class
HIV epidemic
dr's saw pts with kaposi's sarcoma- but not in normal pts(mediaterrian men with cancer)
whats an ecologic study

whats missing in this design
utilizes aggregate data or combine data with individual data

missin relationship btwn exposure and outcome at individual level(incomplete design)

study must be interpreted carefully to avoid eco fallacy
define ecological fallacy
taking aggregate data and applying to specific individuals

CAD higher in richer cities
cross sectional study
disregards length of time (done at 1 pt in time)

provide estimates of prevalence of condition but not incidence

useful in developing new hypothesis not causuality(cause inabillity to determine if exposure was before outcome)
case-control study
whens it useful?
useful in rare outcomes

study sample of ppl with cancer and group without outcome of interest as control

temporal order of exp + outcome is paramount**
whats a common element used in case-control to avoid possible confounding

drawbacks of case-control

selection bias
recall bias
longitudinal study
2 or MORE observations are collected for every unit in study

offer ability to see changes in study unity and across units
2 studies used widely in epidemiology
whats common application of cohort
used when its unethical or impossible to intentionally expose pt to drug or intervention
cohort drawbacks

viewed as
exp+time consuming
not for rare outcomes

as modified approach to RCT-but no random assign
TEMPLES neighbor OSMAR isnt trying to find job, TEMPLES thinks all hispanics are lazy (true story)

is this ecological fallacy?
individual->group = stereotype

group->individual= ecolog fallacy
what are traditional epidemiologic studies
observational- no intervention or tx
Random assigment?
if yes-experiemntal
if no, is there control grp or multiple measures?

if yes-quasi exper.
no- non-exp(observ.)
experimental designs are G.S. in terms of establishing...
internal validity
random selection vs random assignment
rand sel- collecting ppl from population to sample (external validity)

rand assign- 2 grps will preform same, any diff is cuz chance
determines internal validity
experimental design classified into
signal to noise approach

signal-related to key variable tying to measure
noise-all factors(confounders) make it hard to see signal

want signal to be higher than noise
T or F
increasing the signal is better than decreasing the noise
they both increase the quality of research
signal-enhancing designs are called...

whats prototypical factorial design
factorial designs

what are 2 major types of noise-reducing designs
covariance and blocking designs
for assignment to group, what does:
R, N,C stand for
N-nonequal grps
is everyone in a factorial design (2x2) getting same tx?
some get X11, others get X22
for a 2x2..how many factors are there?
for a 2x2x3 how many factors?
2 factors(prolly dose + duration)

3 factors
how many levels are there in 2x2?

how many groups?
F1-2, F2-2= 4 groups

F1-2, F2-2, F3-3= 12 groups
if we are given a pre-intervention test and score avg is 90....what is the score once the pts are broken up into groups
about same approx 90
what is the null effect
its situation where diferent tx combos have NO effect

all scores for tx and setting =90
for a factorial design of 3x3x2 how many effects will there be
there will be 3 effects,
there is 1 effect for every factor
whats a main effect

vs a interaction effect
main- you look at 1 factor at time + # in particular lvl is lower than any number(regardless of lvl) it has main interac on outcome variable

if no level with the lowest # the factor has interaction effect on outcome
RCT most commonly studies info abou...
ADV. DRUG RXS and EFFICACY or EFFECTIVNESS of healthcare services or health technologies(med dev, surgery)
randomization ensures equal distibution of
main goal of randomized block design

what kind of strategy is this?
to reduce noise or variance in data

analytical- it doesnt affect anything with research participants, it groups ppl in data analysis
you can't do a block design unless
you collected data on potenetial confounders
what seperates regression discountinuity (quasi experimentl design) apart from other prepost designs
method of participants are assigned to condidtions

assigned based on cutoff score or preprogram measure
what are steps in doing a regression discontinuity design
1- measure QOL for everyone pre and post w/o txing
2-set cutoff-tx ppl <50QOL, and no tx >50QOL
3- see if results <50QOL line moved up or down compared to the line for >50QOL
what is the difference between the cutoff groups regression lines
its the discontinuity...its in the regression lines at the cutoff point
what is a maturation threat

how to correct
something that changes naturally (ex-kids taking math class in school+ tutoring)
is tutoring helping or is it really learning over time form school

add a control group

R---O---X---O (orig study)
R---O---X---O tutoring grp
R---O--------O non tutoring
how do you address an instrumentation threat

add another observation

ex-kids learn prof always has B as answer
do new study with both exams being B, then change last exam randomly
correlation indicates

its purpose
degree of association btwn 2 variables, "r" but not if one caused the other

to make a prediction about 1 variable based on known v.
what are 2 correlation directions
positive- x incr. y incr

negative xin and y dec.
education + prejudice
positive r
negative 1

is a negative # strong or weak?

doesn't indicate strength, just look at number (-.8>-.2)
does correlation establish causation?
need temporal order, correlation, and rule out alt
pearsons correlation coefficient (r) determines
stregnth and direction btwn x and y, measured at INTERVAL LEVLS
steps to do a correlation problem
1) calc r..make sure denom is done by summing (x-x1)^2 each the multiply total by total y^2

2) calc t value
3) compare t value to table, if > then its statis signif.
what are requirements for using pearsons r
straight line
interval data
random sample
normally distributed x + y
simple regression analysis
like correlation, but we are interested in seeing if changes in x CAUSES change in y
what is R^2
coeffiecent of determination
its % of variance x(dep) accounted by variablitiy in y(indep)
what are residuals
HINT** its not the left over cum on your moms mouth

diff btwn predicted values and actual value of dependent variable (y)

errors we can't predict
error =

what does a + error mean
Y(actual value) - y^(predicted)

+ means y^ is under predicting

- is over predict compared to Y
if you don't know x
how do you determine error
Y(actual)- y (avg)
if you have x
how do you determine error
y(actual)- y^(predicted)
how do you determine SStotal
you do this when don't know x
its the numerator in r
or _
E(y-y) ^2
how do you determine SSerror
this is done when you know what x is

E(y-y^ )^2
what the equation for SSreg
SSreg= SStotal - SSerror
whats equation for Proporionate reduction in error or PRE
SSreg/ SStotal
how do you determine r2
and what does it express
well can do r squared
find PRE and then put in percentage

it expresses % of variance in y explained by x
how do you test statistical sig of regression coeff (r^2)
SSreg/dfreedom (1)

SSerror/ N-2

this is equal to F, compare this umber to Ftable to determine sig or not
steps in making a simple regressio formula
1)use formula to determine b(slope) SP/SSx and intercept a=y(avg)- bx(avg)

2) make new table-use x to determine y^(predicted)

3)do SStotal equat and SSerror (its y- new predicted)

4) find SStotal

5) calc PRE = r2

6) calc F and compare to table to determine signif.