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2. EPIDEMIOLOGY > erin (L2) > Flashcards

erin (L2) Flashcards

1
Q

Types of epidemiological studies

A

TYPES OF STUDY DESIGN

  • experimental (like randomised controlled trial RCT)
  • observational (cohort [longitudinal], case control, cross sectional, ecological [population based])
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2
Q

define the experimental study

A

Examples: Clinical trial for a new antibiotic or impact of putting fluoride in the water.

Requirement:

  • Observational units are randomly assigned to one of two levels of an exposure
  • All other exposures are identical between the two groups (‘controlled’)

Subjects are as similar as possible or stratified

They maximise a researcher’s ability to observe one effect independent of other variables

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3
Q

define an observational study

A

Examples:
Natural exposures: compare disease in smokers vs. nonsmokers?
Historical controls: Compare obesity rates over time?

  • Data are collected without randomisation or artificial manipulation of predictor variables.
  • More difficult to identify causes because it is hard to tease out individual variable effects.
  • There are fewer ethical constraints on the research.
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4
Q

observational studies types

A

Observational studies may be
DESCRIPTIVE vs. ANALYTICAL

analytical studies:
- Randomized control trials
- Cohort studies
- Case-control studies
- Cross-sectional studies
(from strongest inference to weakest)

descriptive studies:
- case studies

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5
Q

DESCRIPTIVE STUDIES

A

ESTIMATION

These studies describe what is occurring and typically quantify a variable.
Do not identify causes

examples:

  • Proportion of women with breast cancer (prevalence)
  • The rate of cases of measles in one year (incidence).
  • Case studies describing a new disease or treatment
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6
Q

ANALYTICAL

A

TESTING STUDIES

Statistical comparisons are made to identify associations
can allow causal inference

examples:

  • Compare the symptoms and progression of Parkinson in patients taking a new vs old drug.
  • Compare pesticide concentrations (chlordecone, an endocrine disruptor) in individuals with and without prostate cancer
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7
Q

what is the interpretation of analytical studies?

and what risks should you consider?

A

Interpretation

  • Is the association ‘reaI’ or due to confounding?
  • Is the association causal?
  • RISK FACTORS = real associations, not necessarily causal

We will identify variables that are associated with a disease by comparing groups

We must consider the risk of BIAS and CONFOUNDING FACTORS throughout the investigation
Studies vary in how they minimize bias and confounding factors

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8
Q

EXPERIMENTAL (RCT)

A

Randomised Control Trial
Features: defined population; randomisation; timing.

RANDOM ASSIGNMENT

DIAGRAM IN L2 S17

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9
Q

when do you use experimental studies

A

Occur after we are fairly sure what is causing the differences that we have found in comparative, analytical studies.
Experimental design allows us to conclude that differences in the dependent variable are due to differences in the treatment.
Remains subject to bias in allocation of treatments if they are not random.

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10
Q

COHORT STUDY

A

Follow groups of exposures and unexposed individuals through time until the outcome happens in a defined proportion of the sample

NOT RANDOMLY ASSIGNED

They are prospective:
Look forward in time – can compare time sequence [Note that cohort studies may be retrospective, but this loses a lot of the plus points]

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11
Q

how is a cohort study different to a RCT

A

Different from Randomized Control Trial: Non-random assignment of exposures (ethics)
Can not rule out that a confounding factors

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12
Q

benefit of a cohort study

A

it permits the investigation of multiple exposures

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13
Q

Properties of cohort study (4)

A
  • Good at identifying causes because the change occurs after the observations (time sequence)
  • Data on exposures are gathered as the happen (no recall bias)
  • Expensive and time consuming
    “loss to follow-up”
  • Difficult to analyse (repeated observations)
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14
Q

case control studies

A

Take individual with disease (CASES) and compare them with individuals from the same population without the disease (CONTROLS).

Calculate proportion of cases that were exposed & proportion of controls that were exposed.

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15
Q

example

how would you make a case control study for breast cancer in women

A

Select cases - women with breast cancer

Select controls - women from

  • The same referral unit with another non-linked disease
  • The same GP practice list
  • The same town

Compare the diet, lifestyle, life experiences of the two groups

Match on age, race, social group

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16
Q

Properties of case control studies

A

Looks backwards (vs. cohort studies look forwards)

Begins with identifying cases (vs. cohort study identifies exposure groups)

More difficult to identify causes compared to cohort study but better at identifying causes than cross-sectional studies (next) because you can still assess the temporal sequence of risk vs. disease.

Are cheap and quick to do

They rely heavily on recall or past records, which may be inaccurate or bias.

Rely on selection of cases

17
Q

define a cross sectional study

A

Predictor and response variables are measured at one point in time.

Example - Questionnaire designed to evaluate the factors associated with alcoholism that also asks about lifestyle and feelings.

Example – Randomly sampled African buffalo populations designed to evaluate if coinfection influenced nematode burdens.

18
Q

big problem with cross-sectional studies

A
  • They demonstrate association but cannot attribute cause.
  • Did alcoholism lead to lifestyle changes of vice versa?
  • Did the coccidia influence susceptibility to nematodes or vice versa? Did a confounding factor influence them both?
19
Q

Properties of cross sectional study

A
  1. Poor at identifying causes (vs. case-control and cohort studies that consider timing)
  2. Good at generating hypotheses
    good to do when there is little known about a subject
  3. Quick
  4. Relatively cheap

Consequently, the literature and media abound with ad hoc cross-sectional surveys

20
Q

time component in studies

A

Cause has to involve time: cause then effect, so need to include
time dimension to understand the relationships

Case control study - looks backwards
Cohort study - looks forward
Cross sectional study - one point in time

21
Q

Descriptive studies

A

Describes features our outcome variable with no comparison.

It may be a new disease that provides our case definition that is used in all further studies

Example – quantify infection

  • Proportion of African buffalo with TB
  • Proportion of undergraduates with chlamydia

2. EPIDEMIOLOGY (2 decks)

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