Disease
Descriptive Studies- Not hypothesizing cause and effect, Nested-Case Control (Incidence Density Sampling)
only determining how measures relate to each other within Controls can later become cases. KEY: Controls are
certain groups.
identified AT THE SAME TIME a case is diagnosed. So you
Correlational-units of analysis are populations or groups of know how much time it takes for a case to become a case.
people .Use pre-existing data. Useful in evaluating effects of OR approximates RATE ratio (Incidence density ratio).
interventions at the population level You don’t necessarily Allows calculating risk directly without a rare disease
know if you are measuring the same people . Can’t
assumption.
generalize to individuals or smaller sub-populations.
Cross Sectional: Compares presence of exposure in persons Conditions for the odds ratio to approximate the risk
with or without existing disease OR Compares presence of ratio
disease in persons with or without existing exposure. Disease Incident cases of disease, Unbiased selection of subjects,
Outcome is rare
status and exposures are observed at one point in time,
without respect to time. Can’t draw temporal associations Proportion-A type of ratio that relates a part to a whole
numerator is included in the denominator
Case Report
Ratio-Numerator and denominator where two separate and
Case Series
distinct quantities. – Expression of the relationship between
Analytic Studies- Must have a control group
a numerator and denominator where the two can be related
Observational
or unrelated
*Cohort- Risk Ratio, Rate Ratio
easier to establish temporality, can study several diseases, Cumulative Incidence-Often multiplied by 100,000 (or 1000
good for rare exposures. Can calculate measures of disease or 100) and reported as “Incidence per 100,000” .
frequency. Forward directionality
I
# of new cases of disease during follow up (I)
CI =
=
*Prospective Cohort-not good for rare disease, long
N # of disease - free subjects at start of follow up (N)
induction period, long latency period
*Retrospective Cohort- data collection issues. Can
calculate OR for cohort studies.
Incidence Density-The rate of developing a specific disease
*CACO-odds ratio, matched odds ratio
backwards directionality- Good for rare diseases, multiple in a defined, disease-free population within a specific period
exposures, efficient. Not good for multiple diseases, rare
I
IR × Δt =
exposures, cannot directly estimate disease frequency
#"# %&' ()*&* "# +,*&)*&
N
of time. IR =
*Cross-sectional-Prevalence
#"# -. /%,0*
Can evaluate several exposures and diseases at same time, Ranges from 0 to infinity
good for estimating disease or exposure burden. Cannot
When individual follow up time is not known, PT=𝑁 ∗ 𝑥 𝛥𝑡
establish etiologic relationships, only identify prevalent not where N* is the average size of the population and PT is
incident cases, miss diseases or exposures with short
equal to the average number of people in the population
duration.
multiplied by the length of the study period
Experimental-investigator assigns exposures
Point Prevalence
2
Hybrid Designs
𝑃 = 3 where C= # of prevalent cases at time t, N=
Case-cohort studies
Randomly sample controls from non-cases in original cohort population at time t
Period Prevalence
You have a particular cohort. KEY: Select a sub-set of
245
controls AT THE BEGINNING of follow-up. Follow them PP= 3 where C= # of prevalent cases at beginning, I = # of
through the study period and identify cases as they arise.
incident cases that develop, N= size of population
Controls may later become cases . OR approximates RISK
ratio (cumulative incidence sampling)
Risk Ratios
Case-crossover studies You start with a cohort of people.
Exposure
KEY: Each person acts as their OWN CONTROL by having
Yes (E+) No (E-)
data on 2 different periods with different outcomes, Compare
Yes
(D+)
a
b
m1
an individual’s exposure immediately before disease
(“hazard period”) to exposure during a similar period which
No (D-)
c
d
m0
did not end in disease (“control period”).A causal exposure
should occur more frequently during a hazard versus control
n1
n0
N
period. Best for acute diseases or brief exposures. Analyze
)
)
Risk among exposed=
or
like a MATCHED case control study (i.e. use OR = b/c)
)4(
%!
6
6
Nested case-control studies- (Cumulative Incidence
Risk among unexposed= 64+ or %
"
Sampling) KEY: Controls are selected from non-cases AT
THE END of follow-up. OR approximates RISK ratio
;(3! = >! )
Risk Ratio: The risk of [describe outcome] is [risk ratio]
times higher/lower among [describe exposed] compared to
[describe unexposed].
Risk Difference
Age-Adjustment =
;3!
N1 is standardized population r1 is rate
Bradford-Hill criteria for causation
Strength of Association (magnitude of effect?)
a
!b
Risk%Difference%="CI1 !!CI0 !=!Risk%in%exposed%–!Risk%in%unexposed!=" n1 − n0 !
The excess risk of [describe outcome] for [describe exposed Consistency (different studies – similar result?)
Specificity (one exposure – one disease?)
group] compared to [describe unexposed groups] is [risk
Temporality (exposure preceded disease?)
difference].
Biological Gradient (dose-response?)
Biological Plausibility (mechanistic explanation?)
Rate Ratio
Experiment (e.g., what happens after cessation of exposure)
Exposure
Analogy (has a similar relationship been observed with
another exposure and/ or disease?)
Yes (E+) No (E-)
Cases
Person-time
I1
I0
I
PT1
PT0
PT
Rate among exposed=
5!
-.7
5"
Rate among unexposed= -.
8
Rate Ratio
The [type of rate] rate among [describe exposed group] is
[rate ratio] times higher than [type of rate] rate among
[describe unexposed groups].
Rate Difference:
IDD#="Rate"in"exposed − Rate%in%unexposed%%=%%
I1
PT1 − !
!I0
PT0 !
The [type of rate] rate among [describe exposed group] is
increased by [rate difference] (Units) compared to [describe
unexposed groups].
Odds Ratio
Exposure
Case status
Case
Control
Yes (E+)
a
b
m1
No (E-)
c
d
m0
n1
n0
N
Odds of exposure among the cases = a / c
Odds of exposure among the controls = b / d
)+
Odds ratio = 6(
Odds Ratio
The odds of [describe exposure] is [odds ratio] times
higher/lower among [describe cases] compared to [describe
controls].
Matched Case-Control
Controls
Cases
Exposed (E+) Unexposed (E-)
Exposed (E+)
W
X
Unexposed (E-)
Y
Z
9
Matched odds ratio = :