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77 Cards in this Set

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Fixed population
Membership is based on an event and is permanent
Dynamic population
Membership is based on a condition and is transitory
3 factors to consider in measurement of disease frequency
1. # of people affected
2. # of people in population from which cases arise
3. length of time followed
Incidence
-occurence of new cases over a specified period of time
-measured in a candidate population
Cumulative Incidence
# new cases/ # in candidate population over a specified period of time
-used in fixed populations, few losses to followup
-research causes, prevention, treatment of disease
- CI=IR*t
Incidence Rate
# new cases / person-time in candidate population
-measure of transition between health/disease of dynamic populations
-research on causes, prevention, treatments
Prevalence
# of existing cases / # in total population
-point or period
-resource planning
- P=IR*D
(D = duration)
Organization in a 2 x 2 table
Disease on x-axis
Exposure on y-axis
Absolute measures of comparison
Risk difference, incident rate difference, etc.
Risk difference
RD=Re-Ru
e = exposed
u = unexposed
Population risk difference
PRD=Rt-Ru
PRD=RDxPe
Pe = proportion exposed
-excess # of cases in total pop
Attributable proportion among the exposed
APe=[(Re-Ru)/Re]x100
-etiologic fraction
-proportion of disease among exposed that would be eliminated if exposure were eliminated
Prevented factor
PF=[(Ru-Re)/Ru]x100
-used when exposure is thought to be protective
Relative Risk
RR=Re/Ru
Excess Relative Risk
ERR=(RR-1)x100
Direct method of standardization requires...
1) Age-specific rates in each group
2) Age structure of a standard population
Experimental study
-studies prevention and treatment
-active manipulation
Observational study
-studies causes, preventions, treatments
-passive
-cohort, case-control,
Cohort study
-examines multiple health effects
-good for rare exposures
-followed according to exposure levels and followed for disease occurrence
-observational
Case-control study
-good for rare diseases
-examines multiple exposures
-exposure histories compared
-observational
Cross-sectional study
-examines relationship between exposure and disease prevalence in a population at a single point in time
-observational
Ecological study
-examines relationship between exposure and disease with population-level data
Validity
lack of bias and confounding
Bias
error committed by investigator in design or conduct that leads to a false association between exposure and disease
Confounding
reflects on the fact that research is on free living humans with unevenly distributed characteristics
Precision
lack of random error, which leads to false association
Randomization
an act of assigning or ordering that is the result of a random process
Masking
unawareness of treatment assignment of patient
purpose of placebos
to match as closely as possible the experience of the comparison group with that of the treatment group
purpose of run-in period
to ascertain which potential participants are able to comply with the study regimen
Intent-to-treat
-treatment assignment analysis
-all individuals in treatment group are analyzed
Efficacy analysis
determines treatment effects under ideal conditions (i.e. compliance)
Cohort
a group of people with a common characteristic or experience
Referent group
unexposed, or comparison group
Closed cohort
fixed cohort with no losses to followup
Possible timing of events in a cohort study
-prospective
-retrospective
-ambidirectional
sources for comparison group
-internal
-general pop
-comparison cohort
pros and cons of using Health Records as sources of info
pros: low expense, high accuracy
cons: other key characteristics missing
cohort study occurrence outcome measure
-cumulative incidence
-incidence rate
purpose of case-control study
provide information on exposure distribution in population
problem with using prevalence in case-control studies
impossible to tell if exposure is related to the inception of the disease, its duration, or a combination
"would" criterion
a member of the control group who gets the disease under study would end up as a case
advantage to using hospital controls
-easy to identify
-good participation rates
-less expensive to identify
-come from the same population
-recall is similar to cases
cons of using dead controls
-not representative of living population
-more likely to have used tobacco, alcohol, drugs
How may biased results come about as an outcome from "special" controls (e.g. siblings)?
if study hypothesis involves a shared activity
survivor sampling
select controls from non-cases at the end of the case diagnosis and accrual period
risk set sampling
-controls selected from population at risk as cases are being diagnosed
-may include future cases
case-based or case-cohort sampling
-select controls from population at risk at the beginning of case diagnosis and accrual period
-may include future cases
purpose of case-control study
investigate risk of disease in relationship to a wide variety of exposures
odds ratio
- prob will occur/prob will not occur
- (a/b)/(c/d) = (ad)/(bc)
Case-crossover study
-used when risk of outcome has a short window
-cases serve as own controls
why use an experimental study?
-high degree of validity from randomization (control for confounders)
-prevention or treatment with small effect
issues in experimental study design
-noncompliance
-must maintain followup rates
-high costs
-reluctance to participate
-ethical issues (equipoise)
why use an observational study?
study effects of a wider range of exposure
why use a cohort study?
-little is known about health consequences of exposure
-rare exposure
why use a case-control study?
-little is known about disease etiology
-less time, $ than a cohort
-rare disease
-diseases with long induction and latent periods
-when exposure data is difficult to obtain
cons of case-control study
-greater chance of bias
-not good with weak associations
-difficult to establish temporal relationship
cons of retrospective cohort study
-minimal info is available on exposure, outcome, confounders
-difficult to establish temporal relationship
cross-sectional study
-measures exposure prevalence in relation to disease prevalence
pros of cross-sectional study
-highly generalizable
-short time
-low cost
cons of cross-sectional study
-no temporal inference when exposure is changeable
-bias: identifies high proportion of cases w/ long duration
-healthy-worker effect
why do a cross-sectional study?
-for PH planning
-etiologic research
ecological study
-examines rates of disease in relation to a factor described on a population level
-identifies groups by place/time
cons of ecological study
-ecological fallacy or ecological bias: not generalizable to individuals
-inability to detect subtle or complicated relationships
pros of ecological study
-quick
-inexpensive
-simple, easy to understand
-wider-range of exposure
a study is considered valid only when what 3 things are eliminated?
-bias
-confounding
-random error
When evaluating a study for the presence of bias, investigators must:
-identify its source
-estimate its magnitude
-assess its direction
selection bias
an error due to systematic differences in characteristics between those who are selected for study and those who are not
best way to avoid self-selection bias
obtain high participation rates among both groups
observation bias
a flaw in measuring exposure or outcome data that results in different accuracy between comparison groups
Key features of observation bias
-occurs after subjects have entered study
-pertains to data collection
-it often results in incorrect classification
recall bias
-differential level of accuracy in the info provided by compared groups
ways to minimize recall bias
-select a diseased control group
-comprehensive questions for exposure ascertainment
-self-administered questionnaire
-rely on measurements and records
avoiding interview bias
-mask interviewers to subjects' disease or exposure status
-closed-ended questions
tips for writing understandable questions
-avoid ambiguous wording
-avoid 2 questions in one
-avoid jargon
-avoid impossible questions
-avoid questions that are not self-explanatory
-avoid questions w/ too many ideas
problem of loss to follow-up
-reduces power of study to detect associations
misclassification
-"measurement error"
-occurs when broad definitions are used
-can reduce by using multiple measurements, validation, or using sensitive and specific criteria