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Epidemiology > cohort studies > Flashcards

cohort studies Flashcards

1
Q

start with

cohort studies

A

environmental exposure
then find association with disease or outcome

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2
Q

temporality

A

timing of info about cause and effect
we want info about cause and effect gathered at the same time

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3
Q

which studies have no temporality

A

observational studies:
cohort
cross-sectional
case-control

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4
Q

which studies have temporality

A

randomized controlled trial

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5
Q

limits of cross-sectional studies

A

hard to distinguish exposures and outcomes

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6
Q

limits of case-control studies

A

case’s recall of past exposures may be different than that of controls

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7
Q

start with

cohort studies

A

exposed and not exposed group (neither group can have disease)
folow up and categorize by disease or no disease

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8
Q

2 observation points

cohort studies

A
  1. determine exposure status and eligibility
  2. determine incident (new cases
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9
Q

variable of interest

cohort studies

A

incidence
we can find risk!

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10
Q

exposure-based cohort studies are good for

cohort studies

A

rare exposures
occupational groups may have more exposure to certain things
compare to non-exposed group of similar demographics

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11
Q

are cohort studies randomized?

A

no!

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12
Q

no randomization means

A

unclear whether exposure caused disease
or whether a confounder is involved

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13
Q

prospective cohort study

cohort studies

A

start with exposure status in present disease free population, then follow forward to future

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14
Q

retrospective cohort study

cohort studies

A

start with exposure status from past and track forward to present
follow-up has already taken place
reconstructed from records

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15
Q

prospective cohort pros

cohort studies

A
  • exposure assessed before disease occurs
  • can get incidence rate, cum. incidence, RR
  • can study several outcomes to 1 cause
  • NO RECALL BIAS
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16
Q

prospective cohort cons

cohort studies

A
  • slow, expensive
  • large samples (unless risk period is long: since we look at person-years)
  • loss to follow-up
  • not for rare disease
  • not easy to reproduce
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17
Q

retrospective cohort pros

cohort studies

A

rare exposures
cheaper
occupational studies or rare events
may be quick

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18
Q

retrospective cohort cons

cohort studies

A

bad for rare disease
hard to get outcome
hard to get exposure
need to determine duration and intensity of exposure

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19
Q

combined retro and pro cohort

cohort studies

A

exposure from past objective records, may gather more info overtime and follow forward into future

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20
Q

design: assembling the cohort

cohort studies

A

all must be at risk
exclude ppl with history
maybe limit to higher risk (certain age group)
collab with other areas to increase sample size and generalizability

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21
Q

determine exposure status

cohort studies

A

questionnaires
lab tests
physical measurements
special procedures
hawthrone effect

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22
Q

hawthorne effect

cohort studies

A

be careful about asking about diet every visit, they may begin to eat differently
study begins to influence behaviors

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23
Q

measurement of exposures

cohort studies

A

must be comparable for exposed and unexposed
performed by someone blinded to exposure
examine at predetermined intervals
establish diagnostic critera BEFORE study begins

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24
Q

incidence in exposed

cohort studies

A

a/a+b

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25
Q

incidence in non-exposed

cohort studies

A

c/c+d

26
Q

cumulative incidence

cohort studies

A

avg probability an individual in the cohort will develop disease over follow-up period

cum incidence = all incident cases over follow-up / all ppl at risk at baseline

27
Q

when should we not use cumulative incidence?

cohort studies

A

when we lose a lot of people to follow-up

28
Q

incidence rate

cohort studies

A

incidence rate = all incident cases over follow-up / person-years

29
Q

measures of association

cohort studies

A

relative risk
rate ratio
attributable risk

30
Q

relative risk

cohort studies

A

cum incidence in exposed / cum incidence in nonexposed

31
Q

relative risk = 3 means

cohort studies

A

disease in exposed is 3 times that in unexposed

32
Q

rate ratio

cohort studies

A

incidence in exposed / incidence in nonexposed

33
Q

RR =

cohort studies

A

(a/a+b) / (c/c+d)

34
Q

RR < 1

cohort studies

A

risk in exposed < risk in nonexposed
neg association
may be protective

35
Q

RR = 1

cohort studies

A

no association, no risk

36
Q

RR > 1

cohort studies

A

risk in exposed > risk in nonexposed
pos association
may be causal

37
Q

attributable risk aka

cohort studies

A

risk difference

38
Q

attributable risk

cohort studies

A

cum incidence exposed - cum incidence in nonexposed

shows total increase in incidence

39
Q

absolute measures

A

greater public health importance bc they tell us incidence and risk difference

40
Q

relative measures

A

determine causality
how strong association is

41
Q

study population

A

actual study members

42
Q

target population

A

population you want to generalize your results to

43
Q

generalizability aka

A

external validity

44
Q

good generalizability =

A

can generalize results to other populations

45
Q

internal validity

A

is association btwn exposure and disease a good estimate of real life

46
Q

what is internal validity impacted by

A

confounding, bias, chance

47
Q

exchangeability

A

even distribution of confounders
unexposed and exposed should be same aside from exposure
lower exchangeability = more confounders

48
Q

confounding issue in cohort studies

A

subjects choose their exposure
also smoking

49
Q

other bias in cohort studies

A

outcome ascertainment bias

50
Q

outcome ascertainment bias

cohort studies

A

no blinding so clinician may be influenced

51
Q

information bias

A

quality of info obtained from each group must be equal
hard with retrospective

52
Q

loss to follow up

A

we hope loss from all groups is equal

53
Q

if loss to followup from group a is greater,

A

relationship is underestimated

54
Q

if loss to followup from group c is greater,

A

relationship is overestimated

55
Q

unequal loss leads to

A

bias of RR and AR

56
Q

analytic bias

A

investigators and statisticians have preconceptions about findings

57
Q

dangers of big sample size

A

more likely to see association even if it doesn’t exist

58
Q

power

A

probability of finding a statistically significant association in data, given that association exists in population

59
Q

survival analysis

A

product limit analysis

60
Q

product limit analysis

A

1 - probability of not developing disease in any time interval

61
Q

product limit analysis = 0.395

A

in absence of withdrawal, death, loss to followup, 39.5% of cohort would develop disease by time t

Epidemiology (13 decks)

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