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LMAP 2 > designing epidemiological studies > Flashcards

designing epidemiological studies Flashcards

1
Q

what is descriptive epidemiology?

A

describe problem at aggregated level

can be used to inform later analytic research

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2
Q

what is analytic epidemiology?

A

deploy and test hypotheses, often at a person-level through which association can be measured and causation inferred

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3
Q

what are the 5 types of descriptive epidemiological study?

A

case report

case series

cross-sectional

longitudinal

ecological

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4
Q

what is descriptive epidemiology about?

A

characterising disease in 1 or more of 3 epidemiological dimensions

  • person
  • place
  • time
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5
Q

what are some examples of demographics that may be investigated in the ‘person’ epidemiological dimension of descriptive epidemiology?

A

age

gender

occupation

disease status

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6
Q

what are some examples of areas that may be investigated in the ‘place’ epidemiological dimension of descriptive epidemiology?

A

at a hospital

in a geographical area

among a certain community

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7
Q

what are some examples of areas that may be investigated in the ‘time’ epidemiological dimension of descriptive epidemiology?

A

a point in time

over a specified period of time

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8
Q

what factors can be considered exposures?

A

age, gender, occupation (‘person’ dimension)

living in a particular area (‘place’ dimension)

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9
Q

what outcomes are often focused on?

A

morbidity and mortality

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10
Q

how can exposure and outcomes be measured?

A

incidence

prevalence

(often point estimates with a confidence interval around them)

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11
Q

what is a statistic?

A

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

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12
Q

what is a parameter?

A

fixed, often unknown value, which describes an entire population

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13
Q

why are case reports important?

A

used to communicate new diseases, new presentations, new findings

can be structured as a bulletin or learning opportunity so-called Continuing Medical Education (CME) or in the UK, Continuing Professional Development (CPD)

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14
Q

what is a case series?

A

in new diseases (e.g. COVID-19) more than one case reported becomes a case series

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15
Q

what is a cross-sectional study?

A

describes prevalence of a condition across a population at a single point in time

takes into account both exposure and outcome

e.g. survey

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16
Q

what are the disadvantages of a cross-sectional study?

A

prevalence measured may be an exposure, outcome or both

lacks follow-up

  • risk and temporal relationships (e.g. incidence rate) cannot be easily determined
  • only cases of disease present at time of survey assessed (if someone dies of the disease they are not counted) - limits ability to measure disease’s true extent

might be unclear whether the exposure preceded the outcome

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17
Q

what is a longitudinal study?

A

describe prevalence or incidence of an exposure or outcome over time

may be made up of more than one cross-sectional analysis (aggregated data)

may follow same participants over time (person-level data)

(term can also be applied to any study - descriptive or analytic - that involves measurement at more than one time point)

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18
Q

what is an ecological study?

A

compare groups, rather than individuals

only analyse aggregate data (not linked to a specific person)

can be descriptive or analytic

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19
Q

what is ecological fallacy/aggregation bias?

A

assuming that associations between groups hold true between individuals too

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20
Q

why are ecological studies useful?

A

usually first step in exploring a research question - can generate hypotheses about disease aetiology

suitable when variability of exposure within each group is limited

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21
Q

what are the advantages of an ecological study?

A

use secondary data sources to complete - therefore relatively inexpensive and quick to complete

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22
Q

what are the disadvantages of an ecological study?

A

subject to ecological fallacy

relies on secondary data collected for different purposes - may not always be comparable between countries or time periods

might be unclear whether the exposure preceded the outcome

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23
Q

what is primary data?

A

collected by the researcher first-hand

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24
Q

what is the advantage of primary data?

A

collected for a pre-specified purpose (test hypotheses or answer the research question(s))

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25
Q

what are the disadvantages of primary data?

A

significant cost (financial and in terms of time)

collecting and cleaning data will often take a very large proportion of an overall research project’s duration and budget

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26
Q

what is secondary data?

A

data that have been collected for another purpose

potentially ‘recycled’ for a different purpose

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27
Q

what are the disadvantages of secondary data?

A

analyses may have to make a series of assumptions because data analysed weren’t intended for the new purpose

introduces critical limitations on how the findings of such a study are interpreted

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28
Q

what is the advantage of secondary data?

A

usually faster and cheaper to carry out

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29
Q

what is routinely collected data?

A

form mainstay of day-to-day demography and epidemiology in the field

large administrative datasets that allow us to understand populations and their health (e.g. census)

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30
Q

how can understanding of a local area be improved through routinely collected data?

A

looking at the number of patients registered at a GP or on the electoral register

(in areas with rapidly changing populations - e.g. London) first language of reception-class school children can often give good understanding of changing ethnic diversity

emergency department attendances, hospital admissions, outpatient attendances

prescribing data from billing data of local pharmacies

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31
Q

what is non-routinely collected data?

A

corollary to primary data

include surveys, other bespoke datasets

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32
Q

why is the use of non-routinely collected data limited outside research?

A

prohibitively expensive

time consuming to operate

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33
Q

what is data linkage?

A

involves joining two or more datasets together

in doing so, finds out more than was possible by analysis of either original dataset alone

e.g. link emergency department attendances with GP records - could look for common characteristics of frequent users of both (identify opportunities for intervention, take pressure off urgent care system)

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34
Q

what are the 2 reasons for which data linkage between primary and secondary care doesn’t exist on a meaningful scale?

A

technical issues - no technological platform or solution has been developed as yet

privacy concerns - ethical and legal constraints on holding, exchanging and analysing private health information (however, patients are often frustrated at having to provide the same information multiple times to multiple organisations that are both regarded to be part of the NHS)

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35
Q

what is an observational analytic study?

A

involve investigator observing populations or individuals

do not involve interference in or manipulation of exposure

e.g. case control study

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36
Q

what is a case control study?

A

compares individuals with a particular condition/disease (cases) to another population with the same general characteristics but without the condition (controls)

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37
Q

how is a case control study carried out?

A

information on past exposure to possible risk factors (both cases and controls)

frequency and intensity of exposure in cases is compared to controls

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38
Q

what must be done prior to selecting cases in a case control study?

A

clear eligibility criteria defined based on objectives of study (“case definition”)
- e.g. only people within a certain age bracket

cases should be representative of everyone with the disease under investigation although they are sourced from a variety of places (hospitals, clinics, community setting) (e.g. not just advanced cases that need surgery)

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39
Q

what 2 things must be considered when selecting controls for a case control study?

A

source of controls

  • should come from the same study population as the cases
  • should be representative of population at risk

assessment of exposure
- should be measurable with similar accuracy to exposure in cases

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40
Q

what are some limitations of a case control study?

A

recall bias - self reported recall of behaviour may not be comparable in cases and controls

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41
Q

how are the numbers of cases and controls determined in a case control study?

A

number of cases can be limited by rarity of disease

statistical confidence can be increased by having more than 1 control per case (studies usually allocate 2 or more controls per case)

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42
Q

what are the advantages of case control studies?

A

good for studying rare diseases - can identify all of the existing cases that have already built up over many years

relatively cheap

quick to obtain data - can assess exposure and outcome at the same time

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43
Q

what are the disadvantages of case control studies?

A

bias associated with exposure assessment - presence of a disease may affect how an individual reports past exposure

difficulty selecting good control group

limited to assessing one chosen outcome

no information about temporal relationship between exposure and disease

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44
Q

why can incidents not be calculated in a case control study?

A

case control study begins with disease status, then explores exposure

already know outcome, so cannot calculate incidents based on exposure

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45
Q

how is an odds ratio in a case control study calculated?

A

odds of exposure amongst cases (i.e. ratio of exposed cases to unexposed cases) over odds of exposure amongst controls (i.e. ratio of exposed controls to unexposed controls)

case control study estimates likelihood of having exposure in those who have the disease relative to those who do not

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46
Q

what are the features of a cohort study?

A

involves a group of people without disease who are observed over a period of time to see what happens to them

defining characteristic: track people forward in time from exposure to outcome

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47
Q

what is important when selecting a target population for a cohort study?

A

appropriate age group (e.g. don’t recruit teenagers to investigate Alzheimer’s)

exposure of interest may be rare, may need to target a specific population

should initially attempt to identify as many subjects as possible without invoking restrictions to make study findings generalisable

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48
Q

what are some examples of factors by which cohorts can be assembled in a cohort study?

A

geographic region

occupation

disease

risk group

birth cohort

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49
Q

why are multiple exposures often assessed in a cohort study?

A

need to control for other exposures during analysis phase

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50
Q

what is important when determining exposure in cohort studies?

A

exposure must be well defined (e.g. binary, all individuals exposed at different levels)

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51
Q

how are exposures assessed in a cohort study?

A

self report (e.g. questionnaire)

taking physical measurements

using existing records (e.g. medical records, census data)

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52
Q

how can outcomes be ascertained in a cohort study?

A

routine surveillance

registry data

death certificates

medical records

directly from patients

(method must be identical in both exposed and unexposed groups)

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53
Q

how is relative risk calculated in a cohort study?

A

incidence in exposed over incidence of unexposed

i.e. risk of developing outcome in exposed group over risk of developing outcome in unexposed group

54
Q

what is a prospective cohort study?

A

identifies a cohort and their exposures

prospectively follows them up to observe their outcomes

55
Q

what is a historical cohort study?

A

a group of individuals form the cohort, with a distribution of exposures and outcomes which are measured contemporaneously or extracted from health records

56
Q

why are historical cohort studies typically lower quality than prospective cohort studies?

A

greater risk of selection bias

greater risk of information biases

57
Q

what are the two basic approaches for assessing whether an exposure is associated with an outcome?

A

experimental studies

observational studies

58
Q

how is the strength of an association judged?

A

robustness of evidence

59
Q

what is a major problem with observational studies?

A

observed groups may differ in many other characteristics in addition to the one being investigated

60
Q

what is the consequence of the major problem with observational studies (observed groups may differ in many other characteristics in addition to the one being investigated)?

A

clinical medicine puts most emphasis on robust evidence from experimental studies/clinical tries

61
Q

what are randomised controlled trials?

A

experimental studies which compare and assess the effectiveness of two or more treatments to see if one is better than the other

either a drug or method of care

treatments being tested could be compared with no treatment (i.e. placebo control) or existing treatment

62
Q

what is necessary to have in a randomised controlled trial?

A

comparative control group

follow up of control group - can see see if treatment is more or less effective than placebo/existing treatment

63
Q

what should be done before using a prescribed treatment to treat any condition?

A

testing with clinical trials

64
Q

what is a placebo controlled trial?

A

placebo ideally identical to active drug but without active drug used in randomised controlled trial

65
Q

what characterises a randomised trial?

A

study subjects are allocated by the investigator to the different study groups through randomisation

investigators intervene differentially on participants

66
Q

what is the relationship between a randomised relationship and bias?

A

incorrect analysis of data can introduce bias

67
Q

why is it important to preserve the advantages of randomisation during the conduct and analysis of a study?

A

can reach incorrect or biased assessment of results by not evaluating patients according to the group to which they were originally assigned

68
Q

how are the advantages of randomisation preserved during the conduct and analysis of a study?

A

if patients withdraw, they must be included in analysis

must find out outcome, include them in original groups (even if they didn’t take drugs, follow instructions etc.)

69
Q

what is intention to treat analysis?

A

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

70
Q

what does random allocation mean during a randomised controlled trial?

A

all participants have an equal chance of assignment to each of the available interventions

71
Q

what are the 2 steps of randomisation?

A

generation of allocation sequence

implementation of allocation

72
Q

what does implementation of allocation during randomisation require?

A

allocation concealment

73
Q

how is the allocation sequence generated during randomisation?

A

use random numbers table or computer software programme that generates random sequence as long as the number of participants in the study is large enough

74
Q

why is allocation concealment necessary?

A

implementation of random allocation sequence occurs without anyone knowing which patient will receive which treatment

knowledge of assignment could influence whether a patient is included or excluded based on perceived prognosis

75
Q

what is a commonly used method of allocation concealment?

A

sequentially numbered opaque envelopes concerning allocation opened by recruiting clinician on participant enrolment

76
Q

what is the problem with using concealed envelopes during allocation concealment?

A

cannot guarantee that envelopes have not been opened in advance to allow strategic scheduling of patient appointments to match the recruiter’s preferred allocation

77
Q

how is the problem with concealed envelopes overcome?

A

central randomisation

usually involves the investigator on recruiting a patient telephoning essential randomisation service, which issues a treatment allocation

78
Q

what is blinding?

A

procedure whereby one or more parties (i.e. participants, staff administering and assessing treatment) in a trial are kept unaware of which treatment participants have been assigned to

79
Q

why is blinding performed?

A

avoid and prevent conscious/unconscious bias in design and delivery of a clinical trial

80
Q

what are the 2 types of blinding?

A

single - only one party blinded

double

81
Q

why is double-blinding useful?

A

prevents performance and detection bias

82
Q

what is performance bias?

A

systematic differences between groups in care provided or in exposure to factors other than the interventions of interests

e.g. if the investigators know that an experimental group have been given an active drug, they may focus their attention on that group

83
Q

what is detection bias?

A

systematic differences between groups in how outcomes are determined

e.g. participants might receive more frequent exams and more diagnostic tests - experimental group has a greater chance of positive outcome

84
Q

what does blinding of those who assess trial outcomes achieve?

A

reduce the risk that knowledge of which

intervention was received rather than the intervention itself affect outcome measurement

85
Q

when can blinding be especially important (when assessing outcomes)?

A

anyone who trusts in the effect of a specific intervention may perceive/detect enhanced treatment’s effect (unconsciously or intentionally)

important for assessment of subjective outcomes e.g. degree of post-operative pain

86
Q

how can blinding help outcome data?

A

can help prevent withdrawals from studies - which would lead to incomplete outcome data

87
Q

why does blinding prevent withdrawal from studies and therefore help outcome data?

A

if a patient knows what treatment they are receiving and feel like it’s an inferior treatment they may be more likely to drop out or not follow the directions of the trial

if someone reacts negatively to the placebo, you can monitor them to find out whether it is a negative reaction to the “treatment” rather than just taking them out of the study straight away knowing that it is an adverse reaction to the placebo

88
Q

what must be taken into account when calculating sample size?

A

anticipated dropout rates

power of study (increases with sample size - priority to be at least 80%, preferably 90%)

89
Q

what is the power of a study?

A

ability to detect an effect or association

power of 90% - means if the true difference between treatments is equal to the one planned there is only a 10% chance that the study will not detect it

90
Q

why is blinding not always possible?

A

e.g. surgical technique - cannot blind surgeon, ethical complication of blinding patient

costly - complicated to keep things blinded

if drugs require titrating - if a drug requires that you increase or decrease the dose blinding can add difficulties

91
Q

what are the 3 main statistical factors that affect sample size?

A

difference between the groups that would be investigated
- e.g. if investigating blood pressure, may look for 5 mmHg or 10 mmHg difference - larger difference will requires smaller sample size

study’s power

  • aim for 80%
  • as power increases, sample size increases

study’s alpha (how much you want to rule out chance causing a positive finding)

  • equivalent of specifying p-value
  • connected with one- and two-tailed testing
  • decreasing alpha from 0.05 to 0.01 will increase your sample size
92
Q

what is a type I error?

A

‘false positive’ finding

93
Q

what is the p-value?

A

probability of obtaining a result as extreme as the observed results of a statistical test, assuming the null hypothesis is correct

i. e. probability of getting your results if there is no real difference, probability of a false positive
0. 05 is usual threshold below which statistical significance is inferred

94
Q

why can p-values sometimes not be useful?

A

running multiple analyses

  • likely that at least one analysis will come back around the p = 0.05 mark
  • data will eventually come back with p <0.05 even if no underlying difference between your groups

p-value does not imply clinical significance

  • p-value tells you is how likely findings are due to chance alone
  • possible to have highly ‘statistically significant’ findings of a clinical difference which is entirely clinically meaningless (e.g. 0.15 mmHg difference in blood pressure after 12 months of treatment for an individual is clinically meaningless but may be highly statistically significant)
95
Q

what is a type II error?

A

‘false negative’ finding

96
Q

how do you determine that the results of a study are not due to a type II error?

A

look at power of study design (80%/90%)

going from 80 to 90% halves risk of false negative

97
Q

what are the 2 types of literature review?

A

narrative review

systematic review

98
Q

what is a narrative review?

A

brings together the published literature into a single article

enables reader to rapidly understand issues

99
Q

what is a systematic review and how does it differ from a narrative review?

A

sets out highly structured approach to searching, sifting, including and summarising literature

more systematic than narrative

100
Q

why are systematic reviews important in epidemiology?

A

underpinning basis for meta-analysis

101
Q

what are the strengths of narrative reviews?

A

agile, normally easier and faster to write (therefore usually more up to date)

useful when looking at areas with limited research/high levels of variation in research (interdisciplinary interaction - potentially broad research questions)

102
Q

what are the weaknesses of narrative reviews?

A

subject to potential bias - authors free to select works included

can be speculative/unbalanced despite peer review

103
Q

what are the strengths of systematic reviews?

A

collates all available evidence relating to highly focused research question

implemented in highly specified protocol - enables reproducibility

include evidence based on pre-specified criteria (inclusion/exclusion criteria)

104
Q

what are the weaknesses of systematic reviews?

A

can take months to design search, review all sources, synthesise findings

only as good as the method employed - if a less comprehensive search strategy used some literature will be missed

only as good as indices searched

only as good as the evidence incorporated

goes out of date quickly (worsened by delay in publication) - always look at search date, not publication date

105
Q

what is the process of a systematic review?

A

research question

structured search

indices

screening/inclusion

reporting

writing

submitting, revising, publishing

106
Q

what is a structured search?

A

terms/phrases put into a search engine

formally structured

working to develop an approach and a series of searches which can later be combined

107
Q

what is important to make clear when searching indices during a systematic review?

A

which search indices are used

time period involved

108
Q

why is it important to make clear which search indices are used during a systematic review?

A

ensures transparency and reproducibility

109
Q

what is the difference between indices and registries?

A

indices: based on published research
registries: registration of research yet to be completed or published (earlier stage of process)

110
Q

why are registries important?

A

don’t overly duplicate research (don’t end up doing multiple randomised controlled trials or systematic reviews simultaneously - would render some of the work redundant)

prevents or precludes risk of publication bias (risk of people not reporting negative findings/overly reporting positive findings)

111
Q

what does the PRISMA diagram show (used in screening)?

A

how many articles have been found through the initial search

how many articles have been removed as duplicates (i.e. come up in multiple indices)

112
Q

what occurs during the screening process of a systematic review?

A

look at the abstracts or titles

go into full text to review eligibility

determine how many studies are going to be included in the meta-analysis or systematic review

PRISMA diagrams often used to show numbers at each stage of the process

113
Q

what is grey literature?

A

evidence is not always published in journals - evidence may not be peer-reviewed or searchable (e.g. government reports, evaluations of particular programmes)

114
Q

how can grey literature be accessed?

A

search engines (e.g. Open Grey, Google Scholar)

115
Q

what is important to bear in mind while using grey literature?

A

not peer reviewed

not the same level of evidence as a randomised trial or other peer reviewed work

116
Q

when is grey information/grey literature particularly challenging?

A

public health/global health

implementations and programmes are reported but accuracy varies greatly

117
Q

why is grey literature useful?

A

can rapidly understand a topic or see what has already been done even if it is not written up for peer-reviewed publication

118
Q

what is snowballing?

A

take a systematic review/narrative review

look at the references that are included

go back through the literature to look at those papers too

119
Q

what is meta-analysis?

A

quantitative, formal epidemiological study design used to systematically
assess previous research studies to derive conclusions about that body of research

combines quantitative findings from separate studies into a pooled estimate

120
Q

what is required in meta-analysis in order to be successful?

A

pooled studies are sufficiently similar (otherwise results are meaningless)

121
Q

what are the 3 types of heterogeneity considered in meta-analysis?

A

clinical heterogeneity
- different patient groups, different selection criteria

methodological - study design, blinding, intervention approach

statistical - reporting differences

122
Q

what are the 2 different ways of weighting studies during meta-analysis?

A

fixed effects

random effects

(both give slightly different weightings, therefore may change findings)

123
Q

what can be used to assess publication bias?

A

publication funnel plot

shows balance of evidence between studies assuming an overall effect side - more publications on one side of the line may suggest that some studies have not been reported

124
Q

what is a trial endpoint?

A

outcome that usually describes a clinically meaningful outcome

125
Q

how can clinical trial outcomes be classified?

A

efficacy – how well a therapy works in achieving a desired outcome

safety – how well a therapy works in not causing adverse events

126
Q

what are the 2 types of efficacy endpoint?

A

primary endpoint
- endpoint for which the study has been powered (i.e. sample size will have been recruited based on pre-specified power and difference)

secondary endpoint
- studies often examine a slightly different endpoint in addition to the primary endpoint (e.g. may measure recurrence of disease/ hospital admission in addition to survival rates - primary endpoint)

127
Q

if the secondary endpoint is proven but the primary endpoint is not, what does that mean for the study?

A

findings may still contribute to understanding of disease

128
Q

how are safety endpoints commonly judged?

A

major issues (e.g. mortality, anaphylaxis etc.) should usually be detected early in the trial process (before roll-out to large numbers of patients)

measuring commonly observed adverse events (AEs) and grading them into a hierarchy of significance - large proportion of patients reporting AEs will require investigation

129
Q

what is a composite endpoint?

A

multiple potential endpoints have been added together

common when outcomes are uncommon

e.g. MI + ischaemic stroke = cardiovascular event

130
Q

what is the effect of arbitrary timepoints on statistical precision in a study?

A

loss of precision

131
Q

how can loss of statistical precision due to arbitrary timepoints be overcome?

A

survival analysis

follow participants in all arms of study for set amount of time - if a patient dies, record

gives a range of survival times, can compare likelihood of survival between arms

display findings using Kaplan-Meier plot (time vs. overall survival)

LMAP 2 (4 decks)

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