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Epidemiology and Biostatistics > Case Control Studies > Flashcards

Case Control Studies Flashcards

1
Q

Definition of case control studies

A

People with disease (cases) are compared to people without the disease (controls) and past exposures are measured

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2
Q

Definition of odds ratio

A

Diseased and exposed : disease and unexposed

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3
Q

Definition of power

A

Probability of detecting true effect and not finding a FN/Type II error

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4
Q

Definition of non differential information bias

A

Errors are distributed evenly between cases and controls

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5
Q

Definition of differential information bias

A

Difference in follow up completeness between groups

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6
Q

Definition of selection bias

A

Population used as control must be representative pf the general population

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7
Q

Definition of admission bias

A

Exposed cases have a different chance of admission than controls. Exposed cases in the study are not representative of all exposed cases

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8
Q

Definition of diagnostic bias

A

Diagnostic approach related to knowing exposure status

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9
Q

Definition of survival bias

A

Only survivors of a study are analysed

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10
Q

Definition of non response bias

A

Controls don’t respond => large difference between those who responded and those who didn’t

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11
Q

Definition of recall bias

A

Cases remember exposure differently to controls

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12
Q

Definition of interviewer bias

A

Different questions/questioning styles used by interviewers

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13
Q

Definition of confounding

A

Alternative explanations for observed exposure outcome association due to another exposure

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14
Q

Definition of population stratification

A

Presence of systematic differences in allele frequencies between subpopulations in a population

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15
Q

Definition of statistical interaction/effect modification

A

Association between exposures and outcomes differ according to a 3rd factor

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16
Q

When are case control studies most often used

A

GWAS

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17
Q

Name the 8 Bradford Hill criteria for causation

What are they?

A

Strength of association
-Stronger the relationship between IV and DV => increased credibility and less likely to be due to confounding

Consistency (reproducibility)
-Consistency of results in different studies

Specificity
-Causation likely if there is no other explanation

Temporality
-Does cause always precede consequence?

Dose response
-Does increased IV => increased DV

Biological plausibility
-Does it make sense with existing biological knowledge

Coherence
-Compatibility with existing knowledge

Experimental evidence
-If IV altered => does it lead to the corresponding disease outcome

Analogy
-Results due to chance/bias/confounders

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18
Q

Why are reports of associations between genotype and outcome so often inconsistent
5 reasons

A

Variation of underlying association between genotype and outcome between populations

Heterogenous phenotypes

Confounding by population stratification

Failure to exclude chance as an explanation

Publication bias

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19
Q

What are case control studies

A

People with disease (cases)
People without disease (controls)
Measure past exposure for both via genes and compare prevalence of exposure in both groups

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20
Q

What are the 3 advantages of case control studies

A

Inexpensive and quick
Good for rare outcomes and multiple risk factors
Can look at risk factors in detail

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21
Q

What are the 4 disadvantages of case control studies

A

Not good for rare exposures
Selection bias
Recall bias
No estimate for diseases incidence

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22
Q

In what way must the cases and controls be similar

Describe the ratios between controls and cases

A

The sample population of controls must be similar to the cases

By increasing the ratio of controls

  • increased power
  • decreased p
  • increased 95% CI
  • no chance in OR

By doing so, can compare if controls and cases cary on different risk factors

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23
Q

What are the 6 key features of a case control study

A

Start with disease/outcome
Retrospective, info obtained from past/is lifelong (genotype)
Can be prospective but takes longer to complete
Observational
No follow ups needed
Suitable for rare diseases, all accessible cases can be located, controls can be found afterwards

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24
Q

How are cases selected

What are the 4 possible types of cases

A

Strict diagnostic criteria

  • specificity of disease
  • consider diagnostic bias and validity of diagnosis

Population based cases
-Include all patients/random sample of all subjects with disease at 1 point/during timeframe

Hospital based cases
-All patients in hospital dept at 1 point in time

Incident cases

Prevalent cases

25
Q

Describe the importance of controls

2 factors

A

Study base
-characterise distribution of exposure that is representative and random

Comparable accuracy
-equal reliability in all info obtained => no systemic misclassification

26
Q

What are the 6 sources of control

Which sources of control should you be careful with

A

Hospital patients
Population of defined geographical area
Probability sample of total population

Neighbors
Friends (watch out for similar exposure characteristics to cases)
Relatives (watch out for similar genetics to cases)
27
Q

How would you calculate the odds ratio

How would you interpret the odds ratio

A

AD / BC = disease and exposed:disease and unexposed

OR = not 1, p<0.05

  • greater than 1 => increased risk
  • less than 1 => protective factor

95% CI contains 1 => can’t reject null
No difference between exposed and non exposed population

28
Q

What is the power

A

Probability of detecting true effect and not finding a FN/Type II error

29
Q

Describe the use of p values in GWAS

A

Includes 1000s of comparisons

Generally p = 5x10-8

30
Q

Descibe analysis of a rare disease

-what would you calculate

A

Risk ratio, rate ratio, odds ratio are numerically similar

Can be used interchangeably

31
Q

Describe 2 methods of data collection for the event and exposure

A 
Event
External data sources
-Disease registries
-Death certificates
-Hospital records

Internal data sources

  • Questionnaires
  • Physical exams
  • Blood and diagnostic tests

Exposure
External data sources
-Hospital records
-Employers

Internal data sources

  • Questionnaires
  • Physical exams
  • Blood and diagnostic tests
32
Q

What are the 3 main types of bias

A

Selection bias
Information bias
Confounders

33
Q

What are 3 sources of misclassfication bias

What are the 2 types of misclassification bias

A

Sources

  • disease status
  • determining exposure status
  • confounders

Types

  • Non differential
  • Differential
34
Q

What is selection bias and the effect on the odds ratio

A

The population used as the control must be representative of the general population
If not => underestimation of OR

35
Q

What is admission bias and the effect on the odds ratio

A

Exposed cases have a different chance of admission than controls
Not representative of all cases => overestimation of OR

36
Q

What is diagnostic bias and the effect on the odds ratio

A

Diagnostic approach related to knowing exposure status

More likely to be diagnosed => not representative of all cases => overestimation of OR

37
Q

What is survival bias and the effects on the odds ratio

A

Only survivors of a study are analysed
Contact with risk factor => rapid death
Leads to underestimation of OR

38
Q

What is non response bias and the effects on the odds ratio

A

Controls don’t respond => large difference between those who responded and those who didn’t
Leads to underestimation of OR

39
Q

What is recall bias and the effects on the odds ratio

A

Cases remember exposures differently to controls

Leads to overestimation of OR

40
Q

What is interviewer bias and the effects on the odds ratio

A

Different questions and questioning styles used by interviewers
May ask more leading questions to cases
Leads to overestimation of OR

41
Q

What are the 4 characteristics of both non differential and differential misclassification

What are examples of both types of misclassification

A

Non differential

  • Random error
  • Unrelated to exposure or outcome
  • Not a bias
  • Weakens measure of association

Use of technology (calibration)
Poor quality controls in DNA processing

Differential

  • Systematic error
  • Related to exposure/outcome
  • Results in bias
  • Measure of association distorted in any direction

Collecting diff types of DNA between cases and controls
Diff technologies used to sequence case and control DNA

42
Q

How would increasing the study size affect the size of random and systematic error

A

Random
-As study size increases => decrease in error

Systematic
-As study size increases => no change in error

43
Q

What are 4 ways to reduce bias present in a case control study

A

Carefully consider your

  • choice of study population
  • methods of data
  • sources of exposure and disease info
  • assess extent and direction of bias
44
Q

What are confounders

What is the effect of confounding

A

Alternative explanations for observed exposure outcome association due to another exposure
Causes bias in estimate

45
Q

What are the 2 methods of addressing confounders

A

Design
Collect sufficient data and either
-restrict study to specific populations
-matching controls and cases on confounders

However, its not always possible to match/restrict, there will always be some residual confounding

Analysis
Population stratification could be present in genetic studies
-adjust for confounders with modeling of logistic regression

46
Q

What are the 3 criteria for confounding

A

Must be causally/non causally associated with exposure in source population in study

Must be a causal risk facto for disease in unexposed

Must not be on causal pathway between exposure and pathway

47
Q

What are the 3 common confounders

A

Age
Sex
Socioeconomic status

48
Q

What is population stratification

A

Presence of systematic differences in allele frequencies between subpopulations in a population
Is not always obvious, but can lead to FP and false associations
Dealt with by analytics programs

49
Q

What is statistical interaction/effect modification

A

Association between exposures and outcomes differ according to a third factor
Variation in groups/strata not due to chance
Normally need to report stratum specific rate ratios

50
Q

How would you interpret statistical interaction

Is this common in statistical studies

A

Rate ratio cary per stratum
If rate ratio varies according to a factor, there is an interaction
Can test for this

True interaction rare in genetic studies

51
Q

How can you deal with bias in a study that focuses on genetic risk factors

A

Bias in exposure (genotype) eliminated in correctly designed studies

Selection bias not likely to be an issue unless population stratification present

Confounders

  • population stratification
  • linkage disequilibrium
52
Q

How can you measure risk factors in a study that focuses on genetic risk factors

A

Can measure all risk factors by comparing all loci in a genome

53
Q

How can you use data gained from studies that focus on genetic risk factors

A

Data collected can be banked and shared indefinitely

Records must be anonymized so consent only needs to be gained once

54
Q

How do you measure exposure in studies that focus on genetic risk factors

A

Genotype can be measured retrospectively via case control

55
Q

How can you deal with bias in a study that focuses in environmental risk factors

A

Bias in different exposures can cause problems

Selection bias is an issue mainly in case controls

Confounders can’t be adequately controlled

56
Q

How can you measure risk factors in a study that focuses on environmental risk factors

A

Unlimited risk factors

57
Q

How can you use data gained from studies that focus on environmental risk factors

A

Studies limited to baseline exposures, sharing data => active collab

Not always necessary to break link between records and ID after data collected

58
Q

How do you measure exposure in studies that focus on environmental risk factors

A

Exposure can be affected by disease onset so prospective studies needed

Epidemiology and Biostatistics (16 decks)

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