00:00
Now we don't know that smoking
causes cancer, at least not until
we've explored it more fully. The reason we
can't be reliably certain experimentally that
smoking causes cancer is because no one's
ever applied a randomized controlled trial
to the relationship between smoking and cancer.
That would look like this, we'd have a study
population that we randomize into two groups,
one group would have to smoke and the other
group would have to not smoke and we'd follow
them for many years and we'd see which group
develops more cancer. That's not ethically
feasible or permissible, so it's never been
done. As a result another set of criteria
or perspectives need to be applied to that
scenario to establish whether or not it's
likely that smoking causes cancer. And today
we're pretty confident that in fact smoking
does cause lung cancer.
00:48
Now the set of criteria I'm talking about
are called the Bradford Hill criteria named
after Sir Austin Bradford Hill. There are
other criteria as well but his are the most
famous and the most widely applied. They're
the foundation for causal proof in epidemiology
in the last few decades, they've also bled
into other disciplines like anthropology and
social science. What Bradford Hill did was
he set out a series of conditions, wherein
a relationship must satisfy them to be considered
likely causal. Not all relationships satisfy
all of his criteria, but we like to say that if
they satisfy most of them or a lot of them
or the important ones, that relationship is
likely a causal relationship, so let's go
through them. The first one is strength and
by the way I want to say that even though
I'm using these words in descriptions of
Bradford Hill's criteria, other people may
describe them differently, but we're talking
about the same thing. By strength I mean effect
size, how big is the relationship statistically.
Now we've covered in another lecture relative
risk and odd ratios, that's what we're talking
about here, how big are the relative risks
or odds ratios for the association between
our potentially causal factor and the outcome,
that's strength. Consistency, do I see the
relationship regularly. And specificity, is
it likely that this one exposure only causes
this outcome, or this one outcome is only
viewed in the presence of this exposure. This
one's a hard one to observe and it isn't a
hard and fast rule, but we'd like to see it
if we can. Temporality, this one is critical,
so it tells us, does the cause proceed the
effect, does the smoking come before the cancer,
if the cancer came before the smoking, it's
pretty much impossible that the smoking caused
the cancer. Biological gradient, this is also
called a dose-response relationship. That's
when the more of one causes more of the other,
meaning, the more I smoke, the more likely
it is I'm going to get lung cancer. Plausibility,
doesn't make sense, doesn't make sense biologically,
does what we understand about the biological
sciences and medicine and physiology, does
that play into and satisfy the relationship
that I'm watching or observing. Coherence
is the relationship that I think I'm watching,
does it fit into what I know about science
as a whole, is it coherent, was what I know
about this particular disease or outcome or
phenomenon. An experiment is it possible to
conduct an experiment. Now if I could conduct
an RCT, that would pretty much satisfy whether
or not my risk factor is causal for my outcome,
but sometimes we can't do it on people, but
we can do it animals, so do we have the experimental
animal data for example. And analogy, one is
difficult to describe, but, can we devise
an analogy or analogous relationship between
my outcome and perhaps another exposure, if
so, then it's possible that my exposure is
not unique and possibly unlikely. In other
words, have I explored other theoretical possibilities
for the relationship that I'm observing.
04:04
Okay now let's use all of Bradford Hill's
criteria to explore the relationship between
smoking and lung cancer. First strength, as
we've had explored in another lecture, there
is a strong relative risk association measured
through cohort studies between smoking and
lung cancer, a very high relative risk, so
strength is satisfied. Consistency, do we
see this relationship a lot, we see it all
the time, pretty much every study of smoking
and lung cancer shows a strong relationship.
Specificity, well this is where this particular
example sort of falls apart, many things can
cause lung cancer and smoking can lead to
many different outcomes. So the Bradford Hill
criteria don't satisfy that one checkmark,
specificity, when it comes to smoking and
lung cancer. Temporality, yeah smoking definitely
precedes lung cancer, we can definitely show
that in a cohort design where we know the
exposure came before the outcome. Gradient,
absolutely, so the more you smoke the more
likely or the more probable you are to have
lung cancer. Plausibility, does it make sense?
Yeah, we can show in the laboratory setting
that lung tissue exposed to the carcinogens
of tobacco smoke does tend to become more
cancerous. Coherence, is this coherent with
other things we've observed? Absolutely, by
understanding of this particular branch of
science shows that it is coherent. Experimental
evidence, yes we've exposed laboratory animals
to smoke and they have developed cancer. And
lastly analogy, we have explored some other
things that perhaps could be causing lung
cancer, so this one is a bit more vague and
I would say that the Bradford Hill last criterion
is not satisfied in this example. But that's
okay, the majority have been. And using this
framework, we can be reliably certain that
there is likely a causal relationship between
cigarette smoking and lung cancer.