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Causation
Jay M. Fleisher
Causation
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Two types of medical research
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Bench work
Epidemiology
Bench work usually describes the underlying
biology of disease
Epidemiology either tests the results of bench
work on human populations or provides input
to the biomedical scientist on what we still do
not know
What does the term “ Causal” really
mean?
Example #1 - HIV and AIDS
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Epidemiology identifies new disease
caused by defect in immune system
Bench science identifies the infectious
agent
Epidemiological studies confirm that
agent causes disease in humans
Causation is proven
Example #2 - What Causes an MI

Epidemiological studies combined with
laboratory study identify risk factors
Cigarette smoking
 Cholesterol
 Elevated blood pressure
 Stress
 Family history
 Obesity
 Etc
Which of the above contribute the most risk
What are the relationships between risk factors
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Therefore:
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The issue of causation is not as simple
as it first appears
Thus, the need for a unifying concept of
causation
A Unifying Model of Causal
Relationships
The 2 Components:

Sufficient Cause
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precedes the disease
if the cause is present, the disease always occurs
Necessary Cause
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precedes the disease
if the cause is absent, the disease cannot occur
The 4 Models of Causal
Relationships
1. Necessary and Sufficient*
Only Factor A
Genetic factors
* RARELY OCCUR
Disease
Sickle Cell Anemia
2. Necessary but Not
Sufficient
Factor A
+
Factor B
+
Factor C
Disease
2. Necessary but Not Sufficient Example
Initiation
+
Latent Period
+
Promoter
Cancer
3. Sufficient but Not
Necessary
Factor A
Factor B
Factor C
Disease
3. Sufficient but Not Necessary Example
Ionizing Radiation
or
Benzene
or
Electromagnetic
Fields?
Leukemia
4. Neither Sufficient Nor Necessary
Factor A
+
Factor B
and/or
Factor C
+
Factor D
and/or
Factor E
+
Factor F
Disease
4. Neither Sufficient Nor Necessary Example
Smoking
+ Cholesterol
and/or
HBP
+ Fam. History
and/or
Stress
+
Obesity
MI
Therefore:
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Concept of Necessary vs. Sufficient
Causes provides a theoretical
framework for causation of all disease
How do we actually assess whether a
Risk Factor is indeed Causal
Criteria for Assessing
Causation
Temporal relationship
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Exposure precedes the disease
Strength of the Association
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Measured by the Relative Risk ( either the Rate Ratio or
the Odds Ratio)
Dose-response Relationship
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As the dose of exposure increases the risk of disease also
increases
Example: Cigarette Smoking and Lung Ca
Replication of the Findings
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Results replicated in other studies
Criteria for Assessing
Causation
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Biologic plausibility
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Does the association fit with what we know about the underlying biology
Sometimes we know little or nothing about the underlying biology (
“Black Box” epidemiology)
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Consideration of Alternate Explanations
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If knowledge exists, rule out or make sure studies took into account
Cessation of Exposure
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Example – Asbestosis and Lung Ca.. Only have theory of mechanism
If exposure is reduced or eliminated Risk will decline
 Example Ex-Smokers
Specificity of the Association

A specific agent is associated with only 1 disease
 OK for infectious agents but falls apart with many Risk Factors for
Chronic Illness
 Example: Cigarette Smoking associated with several diseases
Criteria for Assessing
Causation
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Consistency with other knowledge
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If we have other knowledge regarding a Risk factor then this
comes into play
Often we do not
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Example:
Exposure to Electromagnetic fields is a POSSIBLE risk factor for
Leukemia
This finding is new and the only other knowledge we have is from
studies in changes in cells ( in vitro)
Again “ Black Box” epidemiology
Criteria for Causation:
Smoking and Lung Cancer

Temporal relationship
Biologic plausibility
Consistency
Alternatives
Cessation effects
Specificity of
association
Strength of Association
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Dose-response
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Smoking before Ca
Yes
> 36 studies
?
Yes
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Point of attack
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25 x > 25+ cigarettes
/day*
Yes
*.Estimated that 80% of all Lung cancer due to Cigarette smoking
The usual bit of humor