Causal Inference Flashcards

1
Q

What was the debate regarding red meat consumption

A
  • WHO and other organizations did a series of reviews on red meat/processed meat as probably carcinogenic
  • this study done by Russ and Dena suggested that individuals do not change their red meat consumption
  • controversial conclusion
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2
Q

What is the optimal study design for making causal inferences?

A
  • RCT
  • assign participants at random to interventions
  • ensures balance in known and unknown prognostic factors
  • any differences in the groups can then be attributed to the intervention
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3
Q

What is the revised hierarchy of evidence?

A
  • recognizes that some study designs lower on the hierarchy can sometimes be more useful if they are rigoursly conducted (rigorous case control may be better than poorly conducted RCT)
  • also removes systematic review/meta analysis from the top because it recognizes that the quality of these is highly dependent on the quality of the primary studies
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4
Q

What is the first step to investigate a causal relationship?

A
  • look at evidence from randomized control trials
  • in red meat example, did systematic review of RCTs randomizing participants to lower and higher amounts of red meat
  • found that evidence from the RCTs does not support a causal relationship between red meat intake and adverse health outcomes
  • there were problems with these RCTs (design limitations) so moved onto cohort studies
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5
Q

How are cohort studies normally conducted in nutrition?

A
  • recruit participants and measure intake of various nutritional exposures through questionnaires or biomarkers and follow up over years
  • correlate exposures with health outcomes
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6
Q

What did the review of cohort studies suggest with red meat consumption?

A

-suggested positive association between consumption of red meat and cardiovascular mortality, MI, cancer mortality, etc.

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7
Q

Why might we question the results found in the cohort studies?

A
  • confounding bias (most important)
  • selection bias
  • bias in classification of the exposure
  • bias due to missing data
  • bias in measurement of the outcome
  • bias in selection of the reported results
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8
Q

What biases can also affect RCTs?

A
  • selection bias
  • bias in classification of the exposure
  • bias due to missing data
  • bias in measurement of the outcome
  • bias in selection of the reported results
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9
Q

What is confounding bias?

A
  • distortion of the association between an exposure and outcome due to the association of the exposure with other prognostic factors that also influence the outcome
  • confounding bias is not a concern with RCTs because in an RCT you randomize people to conditions so you get a balance of the confounders
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10
Q

What is selection bias?

A
  • bias in the estimated effect of the exposure on an outcome that arises from the procedures used to select individuals into the study or analysis
  • RCTs and observational studies
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11
Q

Can misclassification of exposure happen in RCT?

A
  • no, RCTs people are assigned an exposure
  • no bias related to measuring the exposure
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12
Q

When does bias from missing data occur?

A

-participants lost to follow up, study participants experiencing deteriorating help so they can’t make study visits, exposure associated with deteriorating health (could make exposure seem less harmful than it is because the people who are getting sick from it are dropping out of study)

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13
Q

Can bias in the measurement of the outcome affect RCTs?

A
  • yes, can affect RCTs and cohort studies
  • differential and non-differential
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14
Q

What criteria are in place that help determine if a relationship is causal?

A

-temporal relationship

-strength of the association

-dose-response relationship

-replication of the findings

-cessation of exposure

  • biologic plausability
  • consistency with other knowledge
  • specificity of the association
  • consideration of alternate explanations

*not all of these have to be met for a relationship to be causal

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15
Q

Describe temporal relationship

A
  • if a factor causes a health outcome, the exposure to the factor should precede the health outcome
  • why case control is not ideal to establish causal relationship
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16
Q

Describe strength of the association

A
  • the greater the magnitude of the association between exposure and outcome, the higher the certainty of evidence supporting a causal relationship
  • RR greater than 2 or less than 0.5 is considered to be large
  • compelled to believe stronger associations because it is unlikely that the entire association could be explained away by other factors or biases
17
Q

Describe dose-response association

A
  • a relationship in which increasing levels of exposure, either in the frequency, magnitude, or duration, is associated with either increasing or decreasing levels of the outcome of interest
  • more confident because the biases are unlikely to produce a dose response association (may produce a one off effect but unlikely to see a pattern if it is due to biases)
18
Q

Describe replication of findings

A
  • the effect is consistently observed across different studies and populations
  • effect could be attributed to a bias particular to one study design or a confounder that acts only in one population or due to chance
19
Q

Describe cessation of exposure

A
  • the effects of an exposure should decline or be eliminated completely once the exposure is removed
  • a potential problem: only select situations where it can be applied- pathogenic pathway for the disease may have already been initiated so stopping the exposure may not reduce your risk of the outcome
20
Q

Describe biologic plausability

A
  • the consistency of the observed association with biological knowledge
  • provides weak evidence for causal relationship because it is subjective
21
Q

Describe consistency with other knowledge

A
  • the consistency of the observed association with forms of evidence
  • weak
  • evidence coming from study designs lower on the hierarchy have higher risk of bias so if there are inconsistencies, they could just be due to other biases
22
Q

Describe specificity

A
  • an association is specific when the exposure of interest is associated with only one disease and when that disease is only caused by the exposure of interest
  • many exposures associated with adverse health outcomes so in real life this doesn’t really play out
23
Q

Describe consideration of alternate explanations

A
  • an association is more likely to be causal when there are no alternate explanations for the observed association
  • not very useful
24
Q

Which criteria were fulfilled for the association between red meat and adverse health outcomes?

A
  • temporality because most of evidence came from prospective cohort studies which assign exposure which precedes outcome
  • strength of association NOT met (small RR)
  • dose response relationship observed (nutritional exposures are hard to study- food exposures are very densely correlated with each other so dose response association makes us less confident because it may be that other exposures correlated with the exposure of interest are confounding the association)
  • consistent effect across different studies (minority reported negative (in asian pop) or no associations- suggests that some positive associations observed in other studies may be due to confounding factors not present in Asian populations)
  • cessation of exposure; don’t know yet
25
Q

What methods are used to facilitate causal inference?

A
  • covariate adjustment: analytic method to adjust for the effects of confounding factors (including confounding variables as covariates which removes their confounding effects- can only do this with confounders we know about and have measured in the study)
  • matching: matches participants according to confounding factors and eliminates the effects of confounders
26
Q

What is the GRADE system? When is data rated highly versus poorly? **on exam

A
  • can be used to evaluate the certainty of evidence supporting causal relationships across different studies (looking at TOTALITY of evidence not a specific study)
  • RCTs start at high quality/certainty evidence
  • observational studies start at low quality/certainty evidence
  • certainty may be downgraded for risk of bias, inconsistency (different studies produce different results), indirectness (question addressed by studies is different from the question of interest), imprecision (studies are too small to draw a reliable conclusion), publication bias
  • certainty may be rated up if there is a large effect, dose-response, and suspected biases act against observed direction of effect