Epidemiology (du coup) Flashcards

1
Q

What are the 2 main types of descriptives studies ?

A
  1. Individual level
  2. Populational level (ecological)
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2
Q

What is the goal of descriptive studies? What information is crucial for that kind of studies ?

A
  • Goals
    • Hypothesis generating
    • Demonstrating trends
    • Resource allocation
    • Need for education
  • Question
    • Who : age, sex, race
    • What : diseases usually, programs sometimes (before/after implementing it)
    • When : calendar type, season
    • Whre : country, povince, city
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3
Q
  • What is the main limitation of ecological or correlationnal (aka descriptive study at a population level) descriptive study?
  • How is this kind of study done ?
A
  • Ecologic fallacy : interpretation of statistical data where inferences about the nature of individuals are deduced from inference for the group to which those individuals belong
  • It’s basically a superposition of 2 descriptive studies : one of disease and one of exposure to make an hypothesis about those 2 things at the population level
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4
Q

What are the advantages of analytical: observational studies?

A
  • Representative populations
  • Represents routine clinical practice
  • Usually more time and cost-efficient than clinical trials
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5
Q

What are the limitations of analytical: observational studies?

A

More susceptible to bias

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6
Q

What are the 3 types of observational studies?

A
  1. Cohorte
  2. Cross-sectional
  3. Case-control (includes nested studies)
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7
Q

What is a cohort study and its advantages?

A
  • Designated group of individuals, who are followed or traced over a period of time. We compare those exposed and those NOT exposed
    • we also classify by exposure and compare outcome/event rates
  • Advantages
    • Can study multiple diseases/outcomes
    • Exposure more clearly precedes disease
    • May be only way to study rare exposures
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8
Q

What are the limitations of a cohort study?

A
  • Major difficulty is loss to follow up
  • Not efficient for rare diseases, long latency
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9
Q

What is a cross-sectional study and its advantages/disadvantages?

A
  • Gather data on exposure and disease simultaneously
  • Limitation: What came first? Exposure or disease?
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10
Q

What is a case-control study? What’s its main advantages ?

A
  • Subjects are selected based upon the OUTCOME: presence (case) or absence (control) of a particular disease
  • Advantages
    • Only rare diseases
    • Mimics the clinical paradigm
    • Simultaneous assessment of multiple exposures
    • Should include all incident cases and come from and represent the same population
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11
Q

What are the limitations of a case-control study?

A
  • Not good for rare exposures
  • Often a challenge in field study to have the same population of origin
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12
Q

What are the goal and the 2 types of analytical: experimental studies?

A

Goal: Try to determine causality, studies of prognosis

Types:

  1. RCT
  2. Systematic review
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13
Q

What is Rate Ratio?

A

Incidence in exposed

___________________

Incidence in unexposed

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14
Q

What is hazard ratio?

A

Time to event in exposed

____________________

Time to event in unexposed

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15
Q

What is risk ratio?

A

Cumulative incidence in exposed

__________________________

Cumulative incidence in unexposed

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16
Q

What is Odds ratio? How do you calulate it ? How do you interpret it ?

A
  • Odds of exposure in cases / odds of exposure in controls
    • = ad / bc
  • people who have an injury (cases) have (insert odds ratio number) times more chance of having the exposure
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17
Q

What is attributable risk?

A

Attributable risk of exposed population – attributable risk of un-exposed population

  • gives you a number of cases we could have prevented without the exposure / time on which the incidence rate is calculated
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18
Q

What is Attributable fraction?

A

Incidence in exposed - incidence in unexposed

______________________________________

Incidence in exposed

*the numerator is actually the attributable risk

  • gives you a sense of the impact of removing the exposure (X% numbers of cases are caused by the exposure)
19
Q

What is Pop attributable risk (PAR)?

A

Incidence in all - incidence in unexposed

20
Q

What is Pop attributable fraction (Pop attributable risk percent)?

A

PAR / incidence in all

21
Q

What is a bias?

A
  • A bias is a systematic error(s) in the design and/or conduct of studies. It is unaffected by study size and results in deviation from the truth (may create or mask associations).
    • Only precision in affected by size.
  • We have to consider the direction and magnitude of the bias.
22
Q

Define selection bias.

A
  • Selection IN and OUT
    • Systematic differences between groups being compared arising from
      • method of selection or
      • reasons for participation
    • = over - or under - representation between comparison groups
  • Lost to follow-up
    • error due to systematic differences in the retention of subjects between the groups being compared
    • one of the most important threats to study validity
23
Q

How do we minimize selection bias?

A
  1. Clear inclusion and exclusion criteria.
  2. Include all new (incident) cases.
  3. Assure high participation and low dropout rates.
  4. For selection bias to occur, selection of subjects or loss to follow up has to be associated with both the exposure and the outcome
24
Q

Define information bias.

A

Misclassification or error of exposure or outcome, can be due to the source of data or an investigator error

Two types :

  1. Non-differential : same error between the test and control groups
  2. Differential : error affects one of the groups being compared more than the other
25
Q

How do we minimize information bias?

A
  1. Use identical measures in groups being compared (case/control, exposed or not)
  2. Blinded assessment of exposure and outcome.
26
Q

Define cofounding bias?

A
  • Results from a third factor that distorts the association between exposure and outcome. Error due to systematic differences in baseline characteristics of the groups being compared “Comparing apples & oranges”.
    • can completely hide the association
    • common cofounding factors : age, sex, SES
27
Q

How do we minimize cofounding bias?

A

Occurs in observational studies of drug benefits and risks

At the design stage:

  • Randomization
  • Restriction
  • Matching

At the analysis stage:

  • Stratified analysis
  • Multivariate analysis
28
Q

What are the 2 main type of study designs in epidemiology ? How are they different ?

A
  • Descriptive
    • hypothesis generating
    • demonstration of trends
  • Analytical
    • hypothesis testing
    • provides evidence to establish causality
29
Q

Can you conclude a link or causal relation from an ecological study ?

A

Nop. Hypothesis generation only

30
Q

What are the 2 kinds of study designs in analytical studies ?

A
  • experimental/interventional
    • systematic reviews/meta-analysis
    • randomized controlled trials
  • observational
    • cross-sectional studies
    • cohort studies
    • case-control studies
    • other designs
31
Q

What are the 2 kinds of cohort studies and what’s their difference ?

A
  • Prospective and retrospective
    • both prospective and retrospective cohort studies asses exposure first and outcome second, however this is done in different time frames
32
Q

what should be your odds of exposure in both the control group and the cases groups in a case-control study ?

A

The same (you should have the same proportion of exposed people on unexposed people)

33
Q

what is a nested case-control study ?

A

An efficient way to select your cohort population so that controls come from and represent the same population than your diseased persons

34
Q

what are the different measure of association in analytical studies ?

A
  • all are sometimes termed relative risks : RR
    • rate ratio : incidence rate in exposed/incidence rate in the unexposed
    • hazard ratio : time to event in exposed / time to event in non-exposed
    • risk ratio : cumulative incidence in exposed/cumulative incidence in unexposed
  • odds ratio : odds of exposure in the cases/ odds of exposure in the controls
35
Q

in well designed studies, what measures of association are equivalent ?

A
  • all the relative risks (RR)
    • rate ratio
    • risk ratio
    • odds ratio
36
Q

when should the odds ratios be equivalent to the relative risk ?

A
  • if the disease is rare (<10 % pop.)
  • if controls are sampled at equivalent times to when cases are occuring (risk set sampling, aka a subject chosen as a control at one point in time may later become a case)
37
Q

What are the different possible measures of impact (it’s ACTUAL NUMBERS !) in studies and their significance ?

A
  • attributable risk : difference in incidence rates or in risks (cumulative incidence)
    • amount of disease we could prevent by removing the exposure
  • attributable fracion (aka attributation risk %) : incidence in exposed minus in unexposed (attributable risk) / incidence in exposed
38
Q
A
39
Q

what is a better measure of public health impact : relative risk or attributable risk ?

A

attributable risk

40
Q

can impact measure be calculated in case of case-control studies ?

A
  • Attributable risk (risk difference) cannot be calculated
  • Attributable fraction = odds ratio - 1 / odds ratio (OR-1/OR)
  • Population attributable fraction (PAF) = AF x prevalence of exposure in cases
41
Q

How could you measure how much a disease in the whole population can be attributed to a certain exposure ? What do they mean ? What is it dependant of ?

A
  • by the population attributable risk and population attributable fraction
    • ​PAR : incidence in all - incidence in unexposed
    • PAR% : PAR / incidence in all
  • Both are dependant on the prevalence of exposure in the population
42
Q

What are the different biais seen in class for design study ?

A
  1. selection biais
  2. information biais (measurement)
  3. confounding biais

Not all observed associations are causal; they may result from errors in selection* of subjects, or in *measurement* of exposure and outcome, or result from *confounding.

43
Q

What can cause information bias ?

A
  • source/quality of data
    • imperfect measurements
  • investigator error
    • incorrect choice of exposure window
    • incorrect definition or timing of the outcome
    • prior knowledge of exposure or outcome status
44
Q

What are the criteria for a confounder (exam question so you better learn it or you’re gonna fail it)

A
  1. Confounder is associated with outcome
  2. confounder is associated with exposure
  3. confounder is not in a causal pathway
    1. aka not : cocaine causes rise in blood pressure causes stokes (rise in blood pressure wouldn’t be a cofounding factor

ALL 3 CRITERIA REQUIRED !