Observational epidemiological studies Flashcards

1
Q

Definition of incidence rate?

A
  • Number of new cases of a specific disease arising within a popn over a specified time period divided by the person-time accumulated
    = (no. new cases) / (no.s of person-years accumulated)
    = #new cases/ #ppl at risk in a given time frame
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2
Q

Definition of risk?

A
  • Number of new cases of a specifc disease arising within a popn over a specified time period divided by the number of persons at risk at the beginning of the time period
    = (no new cases) / (no of persons at risk at beginning of obs period)
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3
Q

Definition/ formula for point prevalence

A

= (No of persons with disease at some time point) / (total popn at risk of disease at the same time point)

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4
Q

What are descriptive studies

A
  • Descriptive studies characterise disease in terms of time, place and person with several aims.
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5
Q

When would a cross-sectional study be undertaken?

A
  • If in a particular geographical region we were to determine the point prevalence of a particular disease -> then undertake cross sect. study (snapshot of region at one point in time)
  • Describe what is happening at the present moment
  • Used to determine the prevailing chara. in a popn at a certain point in time
  • How many exposures and outcomes can we count???
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6
Q

Advantages of a cross-sectional study

A
  1. Inexpensive
  2. Quick
  3. Gather info about diff groups in short amount of time - study multiple exposures and outcomes
  4. Can identify cohort for follow up
  5. Few ethics
  6. Can use entire popn
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7
Q

Disadvantages of a cross-sectional study

A
  1. Time sequence and causation (disease and exposure measured simultaneously and so sometimes hard to interpret results in terms of cause and effect)
  2. Cohort effects when interpreting relationships with age
  3. Problems with interpretation of prevalence which is a mixture of incidence and survival relating to a disease
  4. Large sample sizes necessary to generate usable information (reqs. entire popn to be studied to create useful data)
  5. Selection bias/ information bias/ confounding/ length bias (long disease courses have higher prevalence so it is overestimated)
  6. Does not address temporality
  7. Not for rare/ latent diseases
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8
Q

What are ecological studies

A

Studies in which the units of obs are groups of individuals rather than indiv themselves, for example, popns of diff countries, towns, health regions/ districts
- Associations between exposures and disease at popn level
- Measure rate of death or disease in popns and the popn rate of a RF
- can be used for hypotheses generation
- provides snapshot of the popn vs the indiv

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9
Q

Advantages of ecological studies

A
  1. Quick
  2. Inexpensive (uses routine data)
  3. Hypothesis generation
  4. Useful for popn exposure
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10
Q

Disadvantages of ecological studies

A
  1. The group of people described by disease data are often not the same people as those described by the exposure data
    - > Cannot assume from a relationship found amongst groups of indiv that the same relationship also holds at the indiv level - ECOLOGICAL FALLACY
  2. Outcome measures likely to be biased and inadequate as data not usually collected for all members of a popn?
  3. Subject to confounding which cannot be controlled
  4. Prone to sampling bias - as we can only use the info available to us which may not be representative of the whole popn
  5. Prone to information bias as recording may differ between popns
  6. The time relationship between the measurements for exposure and disease is often unclear - when was the data collected for exposure/ disease?
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11
Q

Definition of cohort studies

A

Studies in which a group of indivs who are defined on the basis of their exposure to a RF and are then followed up over time to determine who develops the disease of interest

-> can be defined either prospectively or retrospectively

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12
Q

Advantages of cohort studies

A
  1. Provide estimates of absolute and cumulative (+relative?) risks of disease
  2. Particularly useful for following up rare exposures
  3. Eliminate some of the sources of bias which are unavoidable in case-control studies which rely on recall of past events, i.e.g if carefully conducted then recall bias is eliminated
  4. Little doubt about cause and effect because exposure is measured before disease occurs
  5. Unlike case control studies that address a single disease, there is no limit to the disease for which the risk of occurrence may be related to exposure - investigate multiple outcomes
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13
Q

Disadvantages of cohort studies

A
  1. Not useful for v rare diseases - as few of the indiv exposed will develop the disease (case control would be better ) - a lot of exposed indivs would need to be recruited to be sure of enough outcomes occurring
  2. Often involves following up large numbers of people over decades they are are EXPENSIVE and DIFF to maintain, particularly from a funding stream perspective (need to wait for outcome to occur after recruiting on the basis of exposure) - loss to follow up problem for diseases with long latency periods
  3. If disease is rare and we only need relative risks assoc with different levels of exposure to RF then unnecessarily expensive
  4. Can only investigate ONE exposure
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14
Q

Definition of case-control studies

A

Studies in which a group of indiv with a particular disease (the cases) are retrospectively compared with an app. selected group of controls in relation to their previous level of exposure to the RF of interest (controls are individually matched) - cases have disease and the controls do not
- Observational retrospective

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15
Q

Advantages of case-control studies

A
  1. Effective use of resources to study the aetiological factors for rare diseases
  2. Explore multiple exposures (RFs) for a disease
  3. Can estimate relative risk of disease associated with different levels of exposure to a RF through the odds-ratio approximation to the relative risk
  4. Recruitment is based on presence or absence of outcome, so do not have to wait for this to occur - good for diseases with long latency periods
  5. Groups for comparison are based on the presence of the outcome: active case finding overcomes the problem of rare outcomes
  6. Quick/ cheap
  7. Small sample sizes
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16
Q

Disadvantages of case-control studies

A
  1. Recall bias, e.g. AXR and childhood cancer
  2. Address single disease only (can investigate only one outcome)
  3. Can’t estimate absolute risk or incidence rate
  4. Can’t calculate incidence or prevalence?
  5. Temporal relations?
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17
Q

Sources of controls in case-control studies

A
  1. From underlying cohort from which the cases were ascertained
  2. Hospital controls
  3. GP controls
  4. Neighbourhood controls
  5. Random digit dialling by telephone
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18
Q

What are the different sources of bias in case control studies?

A
  1. Recall bias
  2. Recording bias
  3. Interviewer bias
  4. Response bias
  5. Sampling bias
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19
Q

What is relative risk?

A

(Incidence rate of disease among those exposed to the factor)/ (incidence rate of disease among those unexposed to the factor)

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20
Q

What is the criteria for assessing causality (BRADFORD HILL CRITERIA)

A
  1. Biological plausibility - does it make biological sense
  2. Time - Logically a cause must PRECEDE its potential effect
  3. Strength of association - Stronger ass of an exposure with disease occurrence then the harder to conceive of likely confounders which might explain the association
  4. Biological gradient or does-response relationship - causality as a plausible interpretation is strengthened if there is a strong dose-response
  5. Consistency - Consistent with other studies in diff popns, places and times add weight to a cause-effect interpretation
  6. Specificity - if the supposed cause if ass. with one disease only, or the disease is ass with one cause only can add weight to a causal interpretation
  7. Coherence - should not contradict what is already known about the natural history and biology of the disease
  8. Experiments - occasionally natural experiments offer themselves, such as tap water fluoride levels and specific disease outcomes
  9. Analogy - v rare and potentially dangerous
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21
Q

What are the aims of descriptive studies?

A
  1. To alert the medical community to what types of persons (Age/ sex/ social class/ geographical region/ calendar year) were most/ least affected by disease
  2. To assist in the EB planning of health and medical care facilities (e.g. how many oncology beds are needed according to health region)
  3. To provide suggestion concerning disease aetiology for further investigation using analytic studies (hypothesis generation)
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22
Q

What are the sources of bias in cohort studies?

A
  1. Healthy worker effect

2. Lost to follow up bias

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23
Q

How can adjustment for confounding be achieved in cohort studies?

A
  • Achieved by use of standardisation, stratification or use of a suitable regression model
  • Indirect/ direct standardisation
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24
Q

What are the different possible regression models for cohort study analysis?

A
  1. Linear regression model
  2. Logistic regression model
  3. Cox regression model
  4. Poisson regression model
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25
Q

What is RECALL bias?

A

Among study subjects the extent of recall differs systematically between cases and controls

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26
Q

What is RECORDING bias?

A

More illnesses and more info recorded in medical records

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27
Q

What is INTERVIEWER bias?

A

Non-neutral approach to interview cases and controls

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28
Q

What is RESPONSE bias?

A

If response rate is LOW or differs between cases and controls

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29
Q

What is SAMPLING bias?

A

Ig not clear what comprises the underlying cohort

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30
Q

What is the Odds Ratio (OR)

A
  • There is INCIDENCE RATE in case-control studies
  • Instead, there is an approximation to the relative risk which can be estimated
  • OR approximates RR and outcome is rare (<10%) otherwise it tends to overestimate the odds
31
Q

How is odds ratio calculated?

A

(Odds of disease in exposed)/ (odds of disease in unexposed)
= ad/bc

32
Q

How might case control studies adjust for confounding variables (which type of models)?

A

Adjustment may be achieved by use of a suitable regression model:

  1. Unmatched case-control study - LOGISTIC REGRESSION
  2. Matched case-control study - CONDITIONAL LOGISTIC REGRESSION
33
Q

Definition of confounding?

A

A factor that is associated with exposure and independently outcome (independently affecting risk of the disease/ outcome)

  • The effects of additional variables that might be responsible for an observed association
34
Q

When do you use the Bradford Hill criteria?

A

Nine principles that can be useful in establishing epidemiologic evidence of a CAUSAL relationship between a presumed cause and an observed effect

35
Q

What is the difference between incidence and prevalence?

A

Incidence = the rate of new cases of a disease occurring in a specific popn over a particular period of time/ limited to NEW CASES ONLY (the total no. of new cases commencing during a specified period in a defined population)
Prevalence = includes all cases (new and pre-existing cases) in the popn at the specified time) (the total no. of individuals who have the disease at a particular time inc old and new(

36
Q

Definition of period prevalence?

A
  • The number of indivs identified as cases during a specified period of time, divided by the total no. of ppl in that popn
  • prevalence measured over an interval of time. It is the proportion of persons with a particular disease or attribute at any time during the interval.

no. of persons w/ disease at any time during a specified period/ total popn seen over the period of time

37
Q

Epidemiology definition

A

“The study of the distribution and determinants of disease in human popns and the application of this study to control of health problem”

38
Q

What are some design issues with case control studies?

A
  1. Need to tightly define DISEASE DEFINITION with criteria
  2. It is best to use INCIDENCE and not prevalence as prevalence may have had longer survival therefore may be systematically different
  3. Case selection
  4. Control selection - must be comparable to case selection - DO NOT exclude if they could not have been exposed, but DO EXCLUDE if they cannot develop the disease (i.e. males if studying ovarian cysts)
  5. Define exposure - methods and procedure should be repeatable
39
Q

Why would a case selection from the hospital for case control studies be good?

A
  1. Easier

2. Medical records access

40
Q

Why would a case selection from the hospital for case control studies not be good?

A
  1. Not generalisable
41
Q

Why would a case selection from the population for case control studies be good?

A
  1. Avoids bias
  2. Generalisable
  3. Direct control comparison
42
Q

Why would a case selection from the population for case control studies not be good?

A
  1. Relatively expensive

2. Diff to measure

43
Q

Why would a control selection from the hospital for case control studies not be good????

A
  1. ??
44
Q

Why would a control selection from the population for case control studies not be good?

A
  1. Expensive
  2. High refusal rate
  • SHOULD USE IF CASES ARE FROM GENERAL POPN)
45
Q

Why would a control selection from friends/ neighbours for case control studies be good?

A
  1. Healthy
  2. Cooperative
  3. Similar exposures
46
Q

What is a closed cohort study?

A
  • Same starting point with fixed follow up.
  • No loss to follow up.
  • Outcome is cumulative incidence or incidence rate/risk ratio or rate ratio.
47
Q

What is an open cohort study?

A
  • Participants enrolled at any point during follow up. Participants can leave at any point.
  • Measure incidence rate/rate ratio.
48
Q

What is a prospective cohort study?

A
  • Selected on current exposure with follow up
49
Q

What is a retrospective cohort study?

A
  • Selected based on previously recorded exposure then determine current disease status
50
Q

Example of study design controls for confounding?

A
  1. Recruit only one level of confounding, e.g. only those who drink 1 pint/ day???
  2. Match cases and controls for confounders (+cohort study)
  3. RCT - randomisation should randomise confounders
51
Q

Example of analysis control for confounding?

A
  1. Stratification - grouping analyses by confounder

2. Adjusted analyses - linear/ regression modelling to account for confounders

52
Q

Consequence of the confounding variable

A

The estimate of the association between the exposures and outcome is distorted because of the association with the exposure and another factor that is also associated with the outcome
Cause:
1. Cause spurious association
2. Exaggerate association
3. Mask an association between exposure and disease

53
Q

Functions of epidemiological studies?

A
  1. Describe patterns of disease in popns

2. Determine causes of disease and occasionally cures

54
Q

Formula to calculate prevalence?

A

Prevalence = incidence x duration of disease

55
Q

What are the uses of cross sectional studies?

A
  1. Determining need for specific health or social services
  2. Dev of hypotheses concerning risk factors for a disease
  3. Determining trends in prevalence (taken over a time sequence)
56
Q

Examples of random sampling

A
  1. Simple random sampling
  2. Cluster sampling
  3. Stratified sampling
57
Q

Examples of non-random sampling

A
  1. Systematic sampling
  2. Snowball sampling
  3. Street survey
  4. Convenience sampling
58
Q

What is simple random sampling?

A

Picking random no. from a list and correlating this to participants

59
Q

What is cluster sampling?

A
  • Natural clusters that occur in popn, i.e. schools, GP practices, households
  • Involves randomising groups, e.g. schools?
60
Q

What is stratified sampling?

A

Used to compare sub groups -> inc minorities in study

- Division of popn into smaller sub groups (aka strata) - strata is formed based on shared characteristics

61
Q

What is systematic sampling?

A

Allocating every second pt to each group for example

62
Q

What is snowball sampling

A

Asking participants to recommend friends and is useful when no frame available

63
Q

What is street survey?

A

Asking random people but there may be quota - i.e. certain no. of females and males to be asked

64
Q

What is convenience sampling?

A

Choose study participants on basis of being readily available
- Subject to volunteer bias

65
Q

What is the difference between incidence rate and risk?

A
  • Rate will contain a dimension of time hence the incidence rate measures the no. of new cases per unit time
  • Risk measures the number of new cases per person in the popn over a period of time
66
Q

What is incidence risk and how to calculate?

A

No. of new cases of a specific disease arising within a popn over a specified time period divided by the no. of persons at risk at the beginning of the time period

No. new cases/ no. of persons at risk at beginning of observation period

67
Q

What to consider when deciding whether the association is causal

A
  1. Chance –> p values and CIs
  2. Bias - selection/ info bias which are determined by the study design
  3. confounding - other risk factors?
  4. Bradford Hill criteria
68
Q

What are case resports/ studies

A

Careful detailed reports of indiv pts or a series of pts –> typically of an unusual disease
- Used to suggest hypotheses
- Have no control groups

69
Q

Which statistical analysis test to use in cross sectional study when comparing means between groups

A

t-test (e.g. is the mean BP in one area higher than the other?)

70
Q

Which statistical analysis test to use in cross sectional study when comparing proportions between groups

A

Chi-square (e.g. did more people die in a certain area)

71
Q

Which statistical analysis test to use in cross sectional study when assessing correlation

A

Pearson correlation coefficient - generates r value indiating the strength of the correlation

72
Q

What is ecological fallacy

A

Cannot assume from a relationship found amongst groups of individuals that the same relationship holds at the individual level

73
Q

What to use for analysis and interpretation of ecological studies

A
  1. Scatter plots - visually inspect the relationship between the exposure and disease
  2. Pearson’s correlation coefficient (stat significance?)