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LMAP YR2 > Epidemiology > Flashcards

Epidemiology Flashcards

1
Q

What is Epidemiology?

A

the study of the distribution and determinants of health-related states/events in specified populations, and the application of this study to the control of health problems

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2
Q

What is a punitive exposures in the context of population health?

A

The variable being tried to associate with a change in health status

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3
Q

What is outcomes in the context of population health?

A

The associated change in health status

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4
Q

What is a primary population level intervention?

A

Preventing disease through control of exposure to risk factors

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5
Q

What is a secondary population level intervention?

A

The application of available measures to detect early departures from health and to introduce appropriate treatment and intervention (slows progression)

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6
Q

What is a tertiary population level intervention?

A

The application of measures to reduce/eliminate long term impairments and disabilities, minimising suffering caused by existing departures from good health and to promote the patients adjustments to their condition

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7
Q

Define a statistic

A

A fixed value, derived from a sample that estimates the value in the population

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8
Q

Define a parameter

A

A fixed, often unknown value, which describes an entire population

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9
Q

Define a point estimate

A

Estimate of a parameter

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10
Q

Define a confidence interval

A

The range of values in which there is a 95% confidence that true value lies within these

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11
Q

Define effect modification

A

Exists when the strength of an association varies over different levels of a third variable

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12
Q

What should happen when effect modification is detected?

A

conduct stratified analysis

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13
Q

How do you test for effect modification?

A
  • Breslow-Day test
  • Q test
  • interaction terms in regression
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14
Q

What is synergism?

A

Effect modifier potentiates exposure effect

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15
Q

What is an antagonism?

A

Effect modifier diminishes exposure effect

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16
Q

Define confounding variable

A

A third variable which leads to bias in the estimate of association between outcome and exposure

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17
Q

Define confounding

A

The effect of an extraneous variable that wholly/partially accounts for the apparent effect of the study exposure or masks an underlying true association

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18
Q

Define internal validity

A

When association truly exists within study participants

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19
Q

Define external validity/generalisability

A

When association observed within a study can be extended to the wider population

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20
Q

Define bias

A

Any trend in the collection /analysis/interpretation/publication/review of data that can lead to conclusions that are systemically different from the truth

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21
Q

Define correlation

A

A linear relationship

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22
Q

Define association

A

Exposure A and exposure B follow similar trends

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23
Q

Define causation

A

Exposure A leads to outcome B

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24
Q

What are the 2 different types of error?

A
  • Type 1

- Type 2

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25
Q

What is a type 1 error?

A

False positive finding

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26
Q

What is a type 2 error?

A

False negative finding

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27
Q

Define selection bias

A

When participation in a study is associated with the exposure and the outcome

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28
Q

What are the variations of selection bias?

A
  • Berkson’s bias

- healthy worker effect

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29
Q

What is Berkson’s bias?

A

Hospital based case control study with controls selected among the hospitals patients

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30
Q

What is the healthy worker effect?

A

Active workers are more likely to be healthy than those who have stopped working

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31
Q

How can selection bias be minimised?

A
  • controls representative of the target population
  • minimise the non-response of patients
  • compare respondents to non-respondants
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32
Q

Define information bias

A
  • misclassification of the exposure and/or outcome

- due to I’ll-defined variables/flaws in data collection

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33
Q

What are possible flaws in data collection?

A
  • interviewer bias

- recall bias

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34
Q

Define interviewer bias

A

Prevented by interviewer being blind/strict protocol when collecting data

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35
Q

Define recall bias

A

Bias when participants self report exposures between cases and controls

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36
Q

How can you prevent recall bias?

A

Use objective ways to assess exposure

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37
Q

What are the different types of misclassification?

A
  • non-differential

- differential

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38
Q

What is non-differential misclassification?

A

When misclassification occurs equally across all groups of study

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39
Q

What does a non-differential misclassification result in?

A

Bias towards the null hypothesis

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40
Q

What is a differential misclassification?

A

When misclassification occurs disproportionately towards cases or controls

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41
Q

What domes a differential misclassification result in?

A

Bias towards or away from the null

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42
Q

What is hazard ratio?

A

Using arbitrary time points to see if trial participants are alive - loss of statistical precision

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43
Q

What is an alternative to a hazards ratio?

A

Survival analysis

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44
Q

What is survival analysis?

A

Whenever a patient dies, their death will be recorded at that time and a survival time will be calculated (range of survival times)

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45
Q

What is a Kaplan Meier plot?

A

Displays survival analysis

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46
Q

What does a Kaplan Meier chart show?

A

The proportion of participants alive at any particular time

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47
Q

Evaluate primary data

A

+ collected for the purpose

  • time consuming
  • expensive
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48
Q

Evaluate secondary data

A

+ faster
+ cheaper
- have to make assumptions as data wasn’t collected for the new purpose

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49
Q

What is data linkage?

A

Joining 2 or more data sets together

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50
Q

Evaluate data linkage

A

+ find out more than from each data set individually

  • technical issues
  • privacy concerns
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51
Q

What are examples of non-routinely collected data?

A
  • surveys

- bespoke data sets

52
Q

Evaluate non-routinely collected data

A
  • limited use
  • expensive
  • time consuming
53
Q

What are examples of routinely collected data?

A
  • census
  • electoral register
  • first language of reception children
  • hospital episode statistics
  • prescribing data
54
Q

What is a narrative review?

A

Puts published literature into a single article

Literature review/scoping review/non-systematic review

55
Q

Evaluate narrative reviews

A

+ easier
+ faster
+ good when starting research
+ good when there is a lot of variation in research

  • bias, works may be unbalanced/evidence could be missed by chance
56
Q

What is a systematic review?

A

Highly structured approach to searching + including + summarising the literature
- basis for meta-analysis

57
Q

What is the process involved in a systematic review?

A
  • research question
  • structured search
  • indices and registries
  • screening (PRISMA flow diagram)
  • reporting
  • writing
  • submission
58
Q

Evaluate systematic reviews

A

+ aims to collate all available evidence
+ specific protocol and inclusion criteria allows for reproducibility

  • only as good as the method/indices/evidence used
  • very quickly out of date as time consuming
59
Q

Define endpoint

A

An outcome that is usually clinically meaningful

60
Q

Define efficacy

A

How well a therapy works in achieving a desired outcome

61
Q

Define primary endpoint

A

The endpoint for which the study has been powered

62
Q

Define secondary endpoint

A

A slightly different endpoint to the primary that is examined as well (may be proven even if primary is not)

63
Q

Define safety

A

How well a therapy works in not causing adverse effects

64
Q

What must be taken into account when assessing safety?

A

Judge whether the safety profile is offset by the efficacy

65
Q

Define phase composite endpoint

A
  • Multiple potential endpoints added together
  • when the outcome is uncommon
  • eg: MI + ischaemic stroke = cardiovascular event
66
Q

Define descriptive epidemiology

A

Describes the problem (often aggregate level) and can be used to inform analytic research

67
Q

What are some examples of descriptive epidemiology?

A
  • case report
  • case series
  • cross-sectional
  • longitudinal
  • ecological
68
Q

What is a case report?

A

Used for new diseases/presentations/findings

69
Q

What is a case series?

A

Multiple case reports

70
Q

What is a cross-sectional study?

A

Describes the prevalence of an exposure/outcome across a population at a single point in time
(No follow up and only prevalence)

71
Q

What is a longitudinal study?

A

describes the prevalence/incidence of an exposure/outcome over time (can be aggregate/person-level)

72
Q

What is an ecological study?

A

compare groups rather than individuals (can be longitudinal/corss-sectional)

73
Q

Define analytic epidemiology

A
  • deploy and test hypotheses

- allows to measure association and infer causation

74
Q

What are the different types of analytic epidemiology?

A
  • observational

- experimental

75
Q

What is an example of experimental analytic epidemiology?

A

randomised controlled trials

76
Q

What is an example of an observational analytic epidemiology?

A
  • case control studies

- prospective cohort studies

77
Q

Define detection bias

A

differences between groups in how outcomes are determined

78
Q

Define performance bias

A

differences between tested groups in either provided care or exposure to factors not being investigated

79
Q

What are the advantages of double blind trials?

A

prevents:
+ performance bias
+ detection bias

80
Q

What does including blinding in a study prevent?

A

prevents or reduces withdrawal from study

81
Q

When is blinding not possible?

A
  • ethically
  • if surgery is involved
  • if the drug needs titrating
82
Q

What do randomised control trials do?

A

evaluate the impact of an intervention on an outcome

83
Q

What is included in a randomised control trial?

A
  • tests 2 or more treatments to see which is better
  • always need controls (existing treatment/placebo)
  • include all patients in analysis irrelevant if they followed treatment
84
Q

In the context of odds, what is the output number above which it becomes more likely an event takes place than does not take place?

A

1.0

85
Q

Define prevalence

A

the proportion of individuals in a population who have the attribute at a specific timepoint

86
Q

What is the epidemiological definition of cumulative incidence?

A

The proportion of the population with a new event during a given time period.

87
Q

How do you calculate cumulative incidence?

A

Cumulative incidence = number of those with the incident / those susceptible to the incident

88
Q

How is incidence rate calculated?

A

The count of new cases during the follow-up period, divided by the total person-time.

89
Q

What are the limitations of a crude rate?

A

It is adjusted for the size of the population (count divided by persons), but not for the age or sex variation within that population – if it were, a standardisation approach would have been used. Crude is sometimes also termed ‘raw’ or ‘unadjusted’.

90
Q

What is a confidence interval?

A

The range of values within which we are 95% confident the true value lies.

91
Q

Describe the relationship between the size of the confidence interval and the number of observations.

A

inversely proportional

92
Q

What characterises a historical cohort study?

A

both the exposures and outcomes are known at the start of the study

93
Q

What is a major limitation of observational study designs?

A

The observed groups may differ in characteristics other than the variable of interest

94
Q

What is an intention to treat analysis?

A

The process of statistically analysing patients’ outcomes using the original groups to which they were allocated, irrespective of whether they took the medicine or not

95
Q

Describe a single blind trial?

A

A trial where the participants (the patients) are not aware which arm of the trial they are in (intervention vs. control).

96
Q

Describe a double blind trial?

A

A trial where the participants AND attending clinicians are not aware which arm of the trial participants are in.

97
Q

Describe a triple blind trial?

A

A trial where the participants / patients AND attending clinicians AND analysis team are not aware which arm of the trial participants are in.

98
Q

What is the intention of allocation concealment?

A

The step in randomisation that attempts to prevent persons involved in the trial from knowing the allocation of participants to study arms.

99
Q

Define the statistical power of the study

A

The ability to detect a difference if a difference exists.

100
Q

What are the 3 main factors that impact sample size?

A
  • power of at least 80%
  • low alpha (0.01)
  • the difference in arms (bigger = smaller sample)
101
Q

Define internal validity

A

The extent to which findings accurately describe the relationship between exposure and outcome in the context of the study

102
Q

Define information bias

A

Misclassification of the exposure, outcome or both.

103
Q

What are different forms of information bias?

A
  • recall bias
  • interviewer bias
  • response bias
  • diagnostic bias
104
Q

Where cases and controls unequally mis-report their exposures AND in such a way that the overall consequence is an association that tends away from the null, this is best described as:

A

information bias

105
Q

What is an unwarranted variation?

A

variation from the norm or the expected, without any explanation - RED FLAG!!

106
Q

What is an explained variation?

A

a variation from the norm that can be explained

107
Q

What is a statistical artefact?

A

when the variation is due to differences in recording or reporting

108
Q

Define ecological fallacy/aggregation bias?

A

the assumption that associations between groups hold between individuals

109
Q

Evaluate ecological studies

A

+ useful when there is limited variability in the group (more confidence asssociations)
+ first step and can be used to explore hypotheses
- uses secondary data
- unsure if exposure preceded outcome

110
Q

What is the implication of a difference of interest?

A

the smaller the difference of interest, the bigger the sample size

111
Q

Define power in epidemiology?

A

the ability to detect an effect/association if one exists (minimum 80, ideally 90)

112
Q

What can cause an increase in power?

A

an increase in sample size

113
Q

What does a 90% power mean?

A

10% chance that the study won’t detect an effect if it exists

114
Q

Define alpha

A

how much chance can be ruled out to cause a positive finding

115
Q

What is alpha?

A

specifying p-value and connect to 1 and 2 tail testing

116
Q

What is the impact of decreasing alpha from 0.05 to 0.01?

A

increasing sample size

117
Q

What are the disadvantages of using p values?

A
  • if multiple analyses are run, one is likely to come back as less than 0.05 despite being false
  • mistaken for clinical significance
118
Q

What is a meta-analysis?

A

combines the quantitive findings of separate studies into a pooled estimate of association

119
Q

What is a forest plot?

A

the way that meta-analysis is presented

120
Q

Define publication bias?

A

studies with more positive findings are more likely to be submitted/published

121
Q

What can be used to assess for publication bias?

A

publication funnel plot

122
Q

What are the differences in studies that can be combined in a meta-analysis?

A
  • patient/selection criteria
  • study design/blinding/intervention approach
  • reporting differences
  • whether the effects are random or fixed
123
Q

How could a population with an upward pointing triangle shaped population be described?

A

High levels of infant mortality and infectious diseases

124
Q

What is the most appropriate method to compare age-specific data between 2 different populations?

A

Direct Standardisation

125
Q

How does the UN see global health?

A

As critical to ensuring international order, peace, stability and security

LMAP YR2 (10 decks)

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