-: Hello, in this presentation I'll introduce you
to Hill's Causal Criteria
before walking through a case study.
Hopefully the case study will help you
to think about your causality assignment for this week.
I strongly recommend that you watch the lecture
on the different types of epidemiological studies
before going through this lecture because an understanding
of study types will help you to follow along.
In epidemiology, we are often interested
in whether a given exposure causes a specific disease.
If it does, then prevention is possible.
We may also be interested in
whether a given exposure protects against disease.
If yes, then health promotion is possible.
But how do we determine whether an association
between an exposure and a health outcome is causal?
First, it's important to note
that correlation does not equal causation.
In this graph here, it looks like
per capita cheese consumption is correlated with
the number of people who die tangled in their bedsheets.
However, that doesn't mean
that eating more cheese causes death by bedsheet tangle.
Here's another example, just by looking at the graph,
you can see the ice cream sales
and shark attacks both go up in the summer
but that doesn't mean that one causes the other.
These may seem like silly examples
but it can be an easy mistake
to make an epidemiology so you really need to be aware.
So how do we determine if an association is causal?
A common way to assess causality
is through the use of Hill's Causal Criteria.
However, Hill's Causal Criteria should be thought
of as guidelines because they're not foolproof.
So first is strength of association.
Strength of association between the exposure of interest
and the outcome is often measured via risk ratios
rate ratios, or odds ratios.
Hill thought that causal relationships were more
likely to show strong associations than non causal agents.
However, a weak association doesn't necessarily
indicate non causality, and this is particularly
true when the outcome of interest is relatively common.
Additionally, a strong association alone doesn't indicate
causality and could be influenced by confounding.
Consistency refers to the reproducibility of results.
Do you see the same results
across various populations and situations?
Consistency can be used to rule out other explanations
for the outcome of interest.
Generally, the greater
the consistency the more likely the causal association
Specificity a tricky criterion
and can be invalid in a number of instances.
The idea was that a specific exposure leads solely
to one specific outcome.
However, in the case of smoking, we know
that smoking can lead to lung cancer as well as a number
of other clinical disorders, although it should be noted
that cigarettes do contain a large mix
of different substances.
However, a one-to-one relationship does exist in some cases.
Take for example, specific pathogens
which are necessary to produce a specific disease.
So the virus SARS-COV-2 is necessary to produce COVID-19.
Temporality is an essential criteria though.
For an exposure to be causal, its presence must precede
the development of the outcome.
The presence of a dose response relationship
between an exposure and outcome can provide good evidence
for a causal relationship.
But lack of a dose response relationship doesn't rule out
a causal relationship because some health
outcomes don't display a typical dose response relationship
with an exposure.
For example, there may be a threshold association instead
and this is something we'll get into
in the next module when we start talking
about toxicology.
Information of biological plausibility is often garnered
through laboratory data
and can further support a causal relationship.
Coherence represents the idea that for a causal association
to be supported, any new data shouldn't provide
evidence against causality.
However, you have to be cautious about making conclusions
about causality based on lack of coherence
because information can be biased or incorrect.
Experiment evidence can come
from laboratory studies, epidemiological studies
clinical trials, or other research.
Ideally, the research would involve a well controlled study
with randomized control trials being a gold standard.
These types of studies can support causality
by showing that altering the cause alters the effect.
And then finally, analogy is one of the weaker criterion
because it is speculative and depends on subjective opinion.
But taken together, you would look at all of these criteria
and then determine, make a determination of causality.
So now let's walk through a case study.
Repetitive head impacts defined as the cumulative exposure
to recurrent concussive and sub-concussive events have long
been associated with the neurodegenerative disease
chronic traumatic encephalopathy, or CTE.
However, in recent years, some people have questioned
whether the relationship between the repetitive head impacts
and CTE is causal.
This article shown on the slide applies Hill's
Causal Criteria to this question.
Really quickly, you might be wondering what exactly is CTE?
So the graphic on this page shows
the four stages of CTE starting with no symptoms and with
symptoms progressively worsening until reaching stage four,
advanced dementia.
Strength of association is the first criterion.
An analysis of strength
of association starts from the premise
that for an association to be statistically significant,
the lower confidence limit
on the odds ratio or relative risk must be greater than one,
that is very unlikely
to be caused by random chance.
Other things being equal, the larger the central estimate
of the odds ratio or relative risk,
the less likely that the significant association
is an artifact of confounding bias or misclassification.
An odds ratio or relative risk that is equal
to 2.0 or greater is generally regarded as strong.
This numerical choice is subjective, but
the appeal of using 2.0 as a benchmark
is that above this ratio is more likely
than not that any individual person with the exposure
and the disease will have contracted the disease
because of the exposure than for any other reason.
So cohort studies are a common method
by which to identify odds ratios, but
in this case there were no cohort studies available
that followed both symptomatic and asymptomatic individuals
through to autopsy to confirm the presence or absence
of CTE because it has to be confirmed during an autopsy.
So in this case
the authors identified six case control studies
where the researchers made a reasonable attempt
to identify RHI history
and had more than 50 subjects to be sufficiently powered
for statistical significance.
So all six studies reported large
and significant odds ratios of CTE cases in subjects
with substantial exposure to RHI compared to the controls.
So the clear finding was
that the associations between RHI and CTE cases are strong
and they're consistently above the 2.0 benchmark.
The next criterion is consistency.
So is the association
between repetitive head injuries or impacts
and CTE demonstrated across multiple studies conducted
by independent groups investigating different
patient populations and using different approaches?
The short answer is yes.
Investigations around the world have described CTE pathology
in former athletes and
in military veterans, all individuals who are subject
to repetitive head impact exposure.
Overall the current literature
from independent researchers and from brain banks,
brain banks being research institutes that accept donations
of brains so that they can examine them postmortem,
all of these provide strong support
for the consistency criterion.
Specificity is the next criterion
and I've included a brief quote from the paper.
Specificity can be observed in a number of ways
but perhaps most significantly by the fact
that prior exposure to RHI is the only known unifying factor
among CTE cases reported in the literature to date.
So it clearly meets this criterion.
The next criterion is temporality.
RHI exposure clearly proceeds CTE pathology,
typically years or decades earlier.
So often we don't know that someone had CTE
until the autopsy occurs,
and the head injury or head impact exposure often happened
many years beforehand.
So that clearly fulfills this criterion.
However, because we can only
confirm CTE pathology postmortem
it's unknown when the pathological process actually
manifests for this disease.
So it's important to ask could the pathology develop
before the RHI exposure actually happened?
There are several factors that make this unlikely.
I won't go into it now, but if you're interested
you can read through the entire article.
There's additional temporal evidence
that comes from the clinical manifestation
of CTE which is traumatic encephalopathy syndrome or TES.
So all criteria for TES require a history
of exposure to head injuries
and the symptoms closely associated
with TES appear to manifest
in the years following the exposure.
So that helps to confirm this criterion.
The next criterion is dose response.
CTE has been recognized by multiple studies over the course
of a century as having a strong dose response relationship
with RHI in several different sports.
Examples include boxing and American football.
So ringside observations
of boxers as far back as 1928 included
the recognition of a dose response relationship
between RHI and possible CTE symptoms.
And the paper states that boxers who had the greatest number
of fights, who had a long duration
of fighting, who were sluggers, meaning they took a lot
of blows, or who sparred extensively were most likely
to show a clinical triad of mental confusion
and recent memory impairment, emotional liability
with mood swings and diminished ability to control temper,
and Parkinsonian signs including tremor,
rigidity and bradykinesia.
With regards to American football,
the Boston University CTE Center researchers showed
that each additional year of football play was associated
with an increased odds ratio
of 1.3 with a 95% confidence interval of 1.19 to 1.41
effectively doubling the odds of disease
every 2.6 years played.
The study also found that each additional year
of football play was associated with an increased odds ratio
of 1.14 with a 95% confidence interval
of 1.07 to 1.22 for having more severe CTE
so effectively doubling the odds of having severe
versus mild CTE every additional 5.3 years of play.
Next, what about biological plausibility?
There's still a lot that we don't know about CTE
but the current literature supports
the plausibility of RHI causing CTE.
The evidence comes from mouse models, computational models,
and studies of wildlife.
So interestingly, researchers have found CTE lesions
in the brains of musk oxen and bighorn sheep,
animals that share certain brain similarities
with humans that are exposed
to RHI through combative headbutting in the wild.
So coherence requires
that the interpretation of the data not seriously conflict
with what is already known
about the disease or the exposure.
There are a couple of areas
of coherence in the literature related to CTE.
So for example, CTE has yet
to be diagnosed in a female athlete worldwide
and this may reflect differences in sports RHI exposure.
So some sex specific rules are
in place for sports like ice hockey
and lacrosse where body checking is illegal for females.
Also, historical discrimination in sports participation
mean that there are fewer female former contact sports
participants in the US over the age of 60.
Bear in mind that Title IX was enacted
in 1972 and provided females
with equal opportunity to participate in school sports.
Another way to look at coherence
is to explore alternative hypotheses.
So many variables have been highlighted
as potential confounders for CTE including substance abuse,
mental health disorders, genetics,
lifestyle factors like diet and exercise.
however, so far, none
of these appear to explain the association
between RHI and CTE and RHI remains the only candidate
risk factor for CTE causation.
Experimental evidence can be difficult
to obtain in the context of environmental exposures.
However, researchers can ask themselves
if a preventive action is taken
due to an observed association
between an exposure and a disease,
does that action in fact prevent the disease outcome?
They can also ask themselves
do other experimental studies suggest a causal relationship?
In this case, CTE has only been widely recognized outside
of the sport of boxing
for about 20 years which isn't enough time for there
to have been meaningful studies of CTE prevention efforts.
It would also be difficult to control all variables
of interest in such a study to draw any firm conclusions.
However, findings
from preclinical RHI studies that replicate elements
of observed human pathophysiological imaging and
epidemiological studies do suggest the causal relationship.
Final criterion is analogy
and the authors described two analogies in this study.
The first is
that the evidence supporting traumatic brain injury
as a causal risk factor for dementia is analogous
to the relationship between RHI and CTE.
The second is that the discovery
of a link between smoking and lung cancer is analogous
to the evidence linking RHI to CTE.
To elaborate on this second point,
the authors wrote, while the link
between smoking and lung cancer is widely accepted
key questions remain unanswered or in completely answered
including what precisely constitutes a smoked cigarette,
the dose, why some smokers develop cancer and others do not,
how many cigarettes are too many or which specific cigarette
or carcinogen sparked the lung cancer?
The fact that these questions also remain
for RHI and sub-concussive impacts is often raised
in a as a reason that conclusions
on RHI CTE causation cannot be drawn.
These knowledge gaps have not limited the ability
to assert a causal link between smoking and lung cancer
and similarly should not limit the ability to determine
the likelihood of a causal link between RHI and CTE.
So to conclude, in the case
of repetitive head impacts and CTE
the researchers established the strength of the association
confirmed consistency, specificity, temporality
a dose response relationship,
biological possibility, and coherence.
They also provided the experimental evidence
that was available and described analogies
to other established causal relationships.
They concluded their article by stating that
the evidence on the link between RHI and CTE is imperfect
and like all similar research,
it will remain imperfect in perpetuity.
After reviewing the medical literature
on RHI and CTE through the Bradford Hill criteria
we have the highest confidence
in the conclusion that RHI causes CTE.
We encourage the medical, scientific
and public health communities
to now act under the premise of a causal relationship
and take immediate action to prevent CTE, minimize risk
and develop therapeutics
to slow or stop disease progression.
If you have any additional questions
about this study and Hill's Causal Criteria
I would encourage you
to read the full article at the link provided on slide six
but hopefully this has helped to give you a good idea
of how Hill's Causal Criteria can be applied in real life.