Observational Studies (Sept 13) Flashcards

1
Q

Observational study design

A
  • natural experiments
  • investigator does not manipulate treatment or exposure to disease, but rather observes natural variation
  • observe what exposures they choose and whether these exposures lead to disease
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2
Q

Why use observational study design?

A
  • some things are not ethical to tell people to do (can’t randomize someone to an experimental drug that is known to be harmful)
  • can observe people who choose to smoke, etc. and study their disease outcomes
  • usually applicable to the world
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3
Q

Problems with observational studies

A
  • prone to bias
  • something about study design or population makes it difficult to be certain that what we saw was the truth
  • eg: if you are doing a study on drinkers and lung cancer, you must know whether or not the participants are smokers (confounding)
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4
Q

Case Report

A
  • 1 patient
  • unusual symptoms/syndrome
  • don’t know cause
  • first, describe and speculate about what might be causing the disease to occur
  • can do lab tests, imaging, histology and describe what is happening
  • describing how a person presents, what you did to treat, and what the outcomes are
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5
Q

Why are case reports important?

A
  • highlight unusual/novel findings
  • bring new diseases to the attention of the medical community
  • new side effects of drugs can be discovered
  • identifying new genetic diseases that are very rare
  • birth defects
  • treatment failures
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6
Q

Limitations of case reports

A
  • case may not be generalizable (if it’s something that only strikes health sci students but then it strikes an eng student, we don’t necessarily know if this will apply)
  • not systematic (if you have a unique case others might present differently and require different treatment)
  • causes or associations may have different explanations (eg. someone may be stressed from an underlying heart condition and not because they don’t cry and process their feelings)
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7
Q

Case series

A
  • group or series of case reports

- involves patients with a specific presentation who were given similar treatment

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8
Q

What is contained in a case series?

A
  • detailed information about the patients (exposure pattern)
  • demographic information
  • diagnosis, treatment, response to treatment, and follow up after treatment
  • defined protocol and inclusion/exclusion criteria (what type of people will be included in the study)
  • try to pick up on typical cases (set definition and choose cases that fit that criteria)
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9
Q

SARS case series example

A
  • people who presented with SARS and another comorbid disease did worse than those without a comorbid disease
  • this case study was important as when people first started coming in, it was unknown who would have a better outcome
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10
Q

Why are case series important?

A
  • same reasons as case reports but with more people

- can help identify or characterize rare conditions or treatment courses

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11
Q

Why are case series limited?

A
  • if the series is retrospective it will depend on the availability and accuracy of the data records (no control over how the data was collected)
  • subject to selection bias because the clinician or researcher self selects the cases
  • findings reported may not be generalizable
  • it is often impossible to know what would have happened to the cases if they had not been treated
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12
Q

Counterfactual

A
  • if we could go back in time with people that we treated and not treat them, what do we think would have happened to them?
  • take a group of people similar to them who got a disease but we didn’t treat them (control group)
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13
Q

Case control studies

A
  • control group gives context
  • two groups of people and we compare what happens to them
  • control group allows you to estimate what would have happened to the treated group had they not been treated
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14
Q

Method for case control study

A
  • define cases and recruit them into study
  • every time a case joins the study, find someone who does not have the disease and recruit them into the study
  • ask both participants the same questions about their exposure history
  • compare exposure histories
  • classify people as cases or controls and as exposed or not exposed
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15
Q

How to select a case for a case control study

A
  • if the interest is looking at the average patient, make sure you are not selecting the sickest patient so they are representative
  • specify clear inclusion criteria of cases (DSM criteria, test score, etc.)
  • incident cases preferable to prevalent (prevalent have often had disease for a long period of time and have survived- survivorship bias- tend to be not typical cases of that disease. Also can be hard to separate exposure from disease as if they’ve lived with it for a long time, they mgiht not remember if the disease came first or other unhealthy exposures were first)
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16
Q

Measures of Association

A

-want to know if our exposure is associated with the disease

17
Q

Concept of Odds

A

-probability that an event will occur/probability that an event will not occur
-eg: attending counselling regularly leads to 25% probability of being stressed
odds of being stressed: 0.25/(1-0.25)= 0.33

18
Q

Odds Ratio

A

OR= odds of a case being exposed/odds of a control being exposed (can do this calculation by cross multiplying the 2x2 table)
OR=1 : no association between exposure and outcome
OR>1 : exposure is more “harmful”
OR<1 : exposure is “protective”

19
Q

Selecting controls

A
  • controls must come from same source population as cases

- do not have disease under investigation but would be included in the study if they got the disease

20
Q

Individual matching

A
  • for every male case, select a male control

- for every one male case, select 4 female controls

21
Q

Group matching

A

-select based on proportion of a characteristic in the cases

22
Q

What are advantages of matching?

A

-remove known risk factors that may not be distributed evenly across groups (counfounding things)

23
Q

What are disadvantages of matching?

A
  • can be inefficient if you have a man but can’t find a man to be a control (increased time and cost)
  • hard to find controls if you match on many variables
  • can overmatch; inadvertently matching on variables that are not of interest
  • can not study the effect of matched variables