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Epi I > Exam2 > Flashcards

Exam2 Flashcards

1
Q

Advantages to randomization

A

1) Assignment of a patient to a study group is determined by chance
2) Unpredictability
3) Rules out self-selection of subjects
4) Provides control over confounding, even by factors that are hard to measure or unknown to the investigator
5) Distributes potential confounders similarly across comparison groups (exposed/non-exposed)
6) Randomization does not guarantee the comparability of groups – therefore stratified matching

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2
Q

Effects of non-compliance

A

Drop-outs do not take the treatment, either knowingly or unknowingly when they shouldn’t while drop-ins either knowingly or unknowingly the treatment when they shouldnt. The effect is that there is less difference seen in treatment effect, the groups will be less different than they should have been.

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3
Q

Intention to treat analysis

A

Analytical method for randomized trials. primary type of analysis done, all individuals randomly allocated to treatment are analyzed regardless of whether they received treatment or not.

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4
Q

Efficacy analysis

A

Analytical method for randomized trials. Used for reduction of risk. Determines the treatment effects under the ideal conditions in those who take the full treatment as directed (with compliance) but excludes those without compliance. excluding non-compliers usually over-estimates the effectiveness of a therapy

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5
Q

Matching in case control

A

individual matching
frequency matching - case and control groups
DISADVANTAGES
cannot study the effect of the matching factor
may reduce statistical power
matching factor must be included in the analysis
may be difficult and time consuming to match

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6
Q

Advantages of intention to treat

A
  1. It preserves the benefits of randomization
  2. Maintains the statistical power of the original study
  3. Helps ensure that the study results are unbiased
  4. Gives info on the effectiveness of a treatment under everyday practice condition
  5. Excluding non-compliers would over-estimate the success of intervention (conservative approach)
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7
Q

Number needed to treat

A

number needed to treat = number of patients who need to be treated in order to prevent one additional bad outcome
NNT = 1/(rate in untreated – rate in treated)
Rate = mortality, incidence (?)

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8
Q

Efficacy

A

used to analyze the extent of the reduction in outcomes by treatment - vaccines
(Rate in controls – rate in treated)/(rate in controls)
AKA reduction in risk

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9
Q

type I errors

A

The treatments do not differ but we conclude that they do (alpha)

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10
Q

type II errors

A

The treatments differ but we conclude that they do not (beta)

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11
Q

alpha

A

probability of making a type I error, concluding that treatments differ when they don’t
the level of statistical significance

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12
Q

beta

A

the probability of making a type II error, concluding that the treatments do not differ when they do differ

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13
Q

Strengths of randomized trials

A

1 - Control over the assignment of the treatment
2 - Randomization ensures the treatment and control groups are balanced, reducing bias and confounding
3 - Blinding minimizes bias
4 - Prospective design allows for temporality and causal relations
5 - Provides firm basis for statistical hypothesis testing - gold standard

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14
Q

Weaknesses of randomized trials

A

1 - generalizability - testing is done on a small number of motivated volunteers
2 - close monitoring may not be the case in a community setting
3 - expensive and labor intensive

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15
Q

When does the odds ratio approximate the risk ratio?

A

when the incidence is low, when the disease is rare

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16
Q

cohort effect

A

the influence of membership in a particular cohort - shared temporal experience or common life experience

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17
Q

Advantages of cohort studies

A

temporality
Direct determination of risk
Can design the study to follow the exposures you specifically want
Size of the cohort under control by study investigators
Can study rare exposures

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18
Q

Disadvantages of cohort studies

A 
Takes a long time
Expensive
Need a lot of justification and supporting scientific data
Not great for studying rare outcomes
Subjects lost to follow up
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19
Q

Biases for cohort studies

A

Information bias on exposure and related factors
Bias in assessing outcomes
Bias in analysis and reporting
Bias from non-response and loss to follow up

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20
Q

Advantages of retrospective cohort

A

Faster – you don’t have to wait for cases to accrue
Less expensive than cohort study
You have a lot of exposure data to choose from

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21
Q

Advantages for case control studies

A

Rare diseases
Disease with long induction/latency periods (cancers)
Lower cost than cohort studies
Faster than cohort, no follow-up time needed
Less expensive than cohort studies
Can be exploratory (little known about disease)
Can assess multiple exposures – good for diseases about which little is known
Tend to use smaller sample sizes than cohort studies
Good for dynamic populations
Good for when exposure data are expensive or difficult to obtain

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22
Q

Disadvantages of retrospective cohort study

A

relies on available exposure info only, may not be in info that you want/need

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23
Q

Disadvantages of case control studies

A

No incidence or temporality
Information on previous exposures may not be available or accurate
Difficult to obtain appropriate controls
Representativeness of cases and controls is often unknown – selection bias

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24
Q

case-control biases

A

Information bias – interview cases more than controls
Recall bias: controls don’t remember as well
Misclassification bias (differential vs. non-differential)
Response bias: some groups of people may respond better than others
Selection bias -
Control selection – controls should be cases if they had been exposed
Controls should be from the same place as cases, or else there will be bias

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25
Q

Why try to choose incident cases for case control?

A

incident cases have less chance of change of exposure
difficult to assess temporality with prevalent cases
survivorship bias for prevalent cases - tend to be longterm survivors

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26
Q

how to choose controls - case-control

A

controls should be comparable to cases except with no disease and exposure experience
potential for exposure should be the same
controls should come from the same population as cases
controls should represent those who would have been cases if they were exposed

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27
Q

hospital based controls - pros and cons

A

easy to ID, more willing to participate, if from the same source population, minimal bias

However, not population based, may be from different source populations, exposure of interest may be associated with other diseases that are used as controls

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28
Q

Cross-sectional advantages

A

Estimate the magnitude and distribution of a health problem
Good for hypothesis generation
Useful for planning interventions
Repeated cross-sectional studies can show changes in trends in disease and risk factors
Low cost and generalizable

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29
Q

Cross-sectional disadvantages

A

No incidence data
No temporality
Healthy worker survivor effect – long term prevalence – long term survivors favored
Not good for disease with low prevalence (rare or short duration)

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30
Q

ecologic fallacy

A

association observed at an aggregate or group level does not necessarily represent the exposure-disease relationship at an individual level

31
Q

Ecologic studies Advantages

A

estimates disease rates at population level or global measures
good approach for generating hypotheses when a disease is of unknown etiology
quick, simple, inexpensive

32
Q

Ecologic studies disadvantages

A

ecologic fallacy

imprecise measurements of exposure and disease

33
Q

non-concurrent prospective study

A

retrospective cohort

34
Q

prevalence study

A

cross sectional study

35
Q

Relative risk and odds ratio vs. attributable risk

A

relative risk = strength of association and potential for causation - important for deriving causal inference - etiology studies
Attributable risk = the potential for prevention if the exposure were eliminated, how much of the disease that occurs can be attributed to exposure? good for elimination strategies

36
Q

attributable risk = risk difference

A

incident rate of disease in exposed - incident rate of disease in unexposed

37
Q

etiologic fraction

A

used in conjunction with attributable risk

use only when there is certainty of causation

38
Q

excess fraction

A

used in conjunction with attributable risk

use when there is no absolute certainty of causation

39
Q

Attributable risk interpretation

A

1) the excess risk of disease associated with exposure is xx or xx*100%.
2) xx of the yy incident cases of disease with exposure are attributable to their exposure
where xx = attributable risk and yy = incident cases of disease in exposed
3) If there were a prevention program for exposure, we could hope to eliminate xx of yy incident cases of disease that experience exposure

40
Q

Percent attributable risk

A

(incident rate of disease in exposed - incident rate of disease in unexposed)/incident rate of disease in exposed
What proportion of the risk in exposed people is due to exposure

41
Q

Percent attributable risk interpretation

A

xx% of the cases of disease with exposure can be attributed to the fact that they were
If prevention programs were 100% effective, there would be xx% fewer cases of disease

42
Q

Population attributable risk = population risk difference

A

Incidence in total population must be known or proportion of exposed in total population
incidence in total population = incidence in exposed prevalence of exposure + incidence in unexposedprevalence of unexposed
PAR = incidence in population - incidence in unexposed

43
Q

Population attributable risk interpretation

A

if there was an effective prevention program, we could hope to prevent xx of the yy incident cases of disease in the total population

44
Q

Population attributable risk percent

A

(incidence in total population - incidence in unexposed)/incidence in total population

45
Q

Population attributable risk percent interpretation

A

xx% of cases of disease in the total population may be attributable to exposure and could be eliminated by eliminating exposure in the population

46
Q

attributable risk using relative risk

A

[(RR-1)/RR]*100%

47
Q

attributable risk using odds ratios

A

[(OR-1)/OR]*100%

You can only assume that the exposure caused the disease

48
Q

Population attributable risk using odds ratios

A

Pe(OR-1)/Pe*(OR-1)+1
where Pe = exposure prevalence in the target population
Can only assume that the exposure caused the disease

49
Q

Infectious disease model

A

host > environment > agent > (vector)

50
Q

chronic disease model

A

multifactorial model - can be very complicated

risk factor epidemiology > modifiable vs. non-modifiable risk factors

51
Q

genetic disease model

A

multiple genes -> multiple environmental factors -> disease
clusters of disease in one family do not necessarily imply genetic disease
descriptive epi > family based studies > population based studies (best)
genes can be determinants of disease or determinants of environmental susceptibility leading to disease

52
Q

social epidemiology model

A

look at many different factors to see if there is a development of a certain outcome
look at the material and social conditions of life

53
Q

correlation

A

changes in two factors are related

54
Q

association

A

there is a relationship between an independent factor and an outcome

55
Q

effect

A

a causal action of a factor on an outcome

56
Q

causal inference steps

A
  1. develop evidence - observations of people, human experiments, other research
  2. synthesize - systematic reviews, meta-analysis, other evidence
  3. evaluate - expert judgment, causal criteria
57
Q

necessary

A

must be present to cause disease

58
Q

sufficient

A

can independently cause disease

59
Q

Causal criteria

A
  1. strength of the association
  2. temporality
  3. dose response
  4. consistency
  5. specificity
  6. plausibility
  7. replication
  8. cessation of exposure
  9. consideration of alternate explanations
60
Q

Causal criteria: specificity

A

x

61
Q

Causal criteria: dose response

A

x

62
Q

Causal criteria: temporality

A

x

63
Q

Causal criteria: replication

A

Other people following your methods can replicate your findings - you can replicate the findings of others’ work by following their methodology

64
Q

Causal criteria: biological plausibility

A

there is a biological basis in the theory

65
Q

Causal criteria: cessation of exposure

A

x

66
Q

Causal criteria: consideration of alternate explanations

A

x

67
Q

Causal criteria: strength of association

A

x

68
Q

Causal criteria: consistency

A

x

69
Q

why randomize?

A

1) rules out self-selection of subjects
2) provides control over confounding, even over factors that are unknown
3) distributes potential confounders similarly across comparison groups

70
Q

non-compliance types

A

drop-out: people in treatment group do not take the treatment intended, either on purpose or by accident
drop in: take the treatment, either on purpose or by accident if they are supposed to be controls

71
Q

Analytical approaches to randomized studies

A

Intention to treat: analysis comparing outcomes between comparison groups that were formed by randomization, all individuals are analyzed regardless of whether they completed the treatment or not, most popular
Efficacy analysis: reduces risk, determines the treatment effects under the ideal conditions in those who take the full treatment as directed but excludes those without compliance
Subgroup analysis: used to determine the treatment effects among different subgroups - treatment/intervention may work better in one group than another, predetermined subgroups

72
Q

Risk ratio interpretation - cohort study

A

1) the risk of the outcome is xx times greater in exposed compared to unexposed
2) there is a xx-1*100% greater or lesser risk of outcome in exposed compared to non-exposed

73
Q

Odds ratio interpretation - case control

A

the odds of exposure is xx greater in cases compared to controls

74
Q

power

A

1-beta

the probability of correctly concluding that the treatments differ

Epi I (1 decks)

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