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Science.

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The very word for many of you conjures
unhappy memories of boredom

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in high school biology or physics class.

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But let me assure that what you did there

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had very little to do with science.

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That was really the "what" of science.

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It was the history
of what other people had discovered.

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What I'm most interested in as a scientist

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is the "how" of science.

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Because science is knowledge in process.

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We make an observation,
guess an explanation for that observation,

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and then make a prediction
that we can test

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with an experiment or other observation.

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A couple of examples.

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First of all, people noticed
that the Earth was below, the sky above,

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and both the Sun and the Moon
seemed to go around them.

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Their guessed explanation

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was that the Earth must be
the center of the universe.

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The prediction: everything
should circle around the Earth.

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This was first really tested

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when Galileo got his hands
on one of the first telescopes,

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and as he gazed into the night sky,

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what he found there was a planet, Jupiter,

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with four moons circling around it.

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He then used those moons
to follow the path of Jupiter

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and found that Jupiter
also was not going around the Earth

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but around the Sun.

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So the prediction test failed.

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And this led to
the discarding of the theory

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that the Earth was the center
of the universe.

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Another example: Sir Isaac Newton
noticed that things fall to the Earth.

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The guessed explanation was gravity,

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the prediction that everything
should fall to the Earth.

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But of course, not everything
does fall to the Earth.

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So did we discard gravity?

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No. We revised the theory and said,
gravity pulls things to the Earth

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unless there is an equal
and opposite force in the other direction.

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This led us to learn something new.

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We began to pay more attention
to the bird and the bird's wings,

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and just think of all the discoveries

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that have flown
from that line of thinking.

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So the test failures,
the exceptions, the outliers

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teach us what we don't know
and lead us to something new.

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This is how science moves forward.
This is how science learns.

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Sometimes in the media,
and even more rarely,

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but sometimes even scientists will say

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that something or other
has been scientifically proven.

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But I hope that you understand
that science never proves anything

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definitively forever.

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Hopefully science remains curious enough

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to look for

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and humble enough to recognize

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when we have found

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the next outlier,

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the next exception,

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which, like Jupiter's moons,

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teaches us what we don't actually know.

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We're going to change gears
here for a second.

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The caduceus, or the symbol of medicine,

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means a lot of different things
to different people,

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but most of our
public discourse on medicine

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really turns it into
an engineering problem.

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We have the hallways of Congress,

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and the boardrooms of insurance companies
that try to figure out how to pay for it.

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The ethicists and epidemiologists

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try to figure out
how best to distribute medicine,

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and the hospitals and physicians
are absolutely obsessed

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with their protocols and checklists,

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trying to figure out
how best to safely apply medicine.

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These are all good things.

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However, they also all assume

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at some level

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that the textbook of medicine is closed.

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We start to measure
the quality of our health care

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by how quickly we can access it.

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It doesn't surprise me
that in this climate,

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many of our institutions
for the provision of health care

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start to look a heck of a lot
like Jiffy Lube.

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(Laughter)

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The only problem is that
when I graduated from medical school,

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I didn't get one of those
little doohickeys

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that your mechanic
has to plug into your car

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and find out exactly what's wrong with it,

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because the textbook of medicine

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is not closed.

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Medicine is science.

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Medicine is knowledge in process.

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We make an observation,

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we guess an explanation
of that observation,

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and then we make a prediction
that we can test.

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Now, the testing ground
of most predictions in medicine

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is populations.

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And you may remember
from those boring days in biology class

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that populations tend to distribute

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around a mean

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as a Gaussian or a normal curve.

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Therefore, in medicine,

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after we make a prediction
from a guessed explanation,

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we test it in a population.

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That means that what we know in medicine,

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our knowledge and our know-how,

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comes from populations

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but extends only as far

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as the next outlier,

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the next exception,

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which, like Jupiter's moons,

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will teach us what we don't actually know.

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Now, I am a surgeon

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who looks after patients with sarcoma.

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Sarcoma is a very rare form of cancer.

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It's the cancer of flesh and bones.

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And I would tell you that every one
of my patients is an outlier,

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is an exception.

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There is no surgery I have ever performed
for a sarcoma patient

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that has ever been guided
by a randomized controlled clinical trial,

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what we consider the best kind
of population-based evidence in medicine.

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People talk about thinking
outside the box,

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but we don't even have a box in sarcoma.

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What we do have as we take
a bath in the uncertainty

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and unknowns and exceptions
and outliers that surround us in sarcoma

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is easy access to what I think
are those two most important values

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for any science:

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humility and curiosity.

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Because if I am humble and curious,

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when a patient asks me a question,

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and I don't know the answer,

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I'll ask a colleague

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who may have a similar
albeit distinct patient with sarcoma.

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We'll even establish
international collaborations.

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Those patients will start
to talk to each other through chat rooms

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and support groups.

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It's through this kind
of humbly curious communication

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that we begin to try and learn new things.

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As an example, this is a patient of mine

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who had a cancer near his knee.

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Because of humbly curious communication

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in international collaborations,

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we have learned that we can repurpose
the ankle to serve as the knee

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when we have to remove the knee
with the cancer.

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He can then wear a prosthetic
and run and jump and play.

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This opportunity was available to him

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because of international collaborations.

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It was desirable to him

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because he had contacted other patients
who had experienced it.

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And so exceptions and outliers in medicine

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teach us what we don't know,
but also lead us to new thinking.

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Now, very importantly,

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all the new thinking that outliers
and exceptions lead us to in medicine

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does not only apply
to the outliers and exceptions.

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It is not that we only learn
from sarcoma patients

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ways to manage sarcoma patients.

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Sometimes, the outliers

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and the exceptions

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teach us things that matter quite a lot
to the general population.

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Like a tree standing outside a forest,

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the outliers and the exceptions
draw our attention

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and lead us into a much greater sense
of perhaps what a tree is.

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We often talk about
losing the forests for the trees,

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but one also loses a tree

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within a forest.

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But the tree that stands out by itself

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makes those relationships
that define a tree,

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the relationships between trunk
and roots and branches,

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much more apparent.

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Even if that tree is crooked

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or even if that tree
has very unusual relationships

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between trunk and roots and branches,

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it nonetheless draws our attention

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and allows us to make observations

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that we can then test
in the general population.

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I told you that sarcomas are rare.

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They make up about one percent
of all cancers.

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You also probably know that cancer
is considered a genetic disease.

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By genetic disease we mean
that cancer is caused by oncogenes

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that are turned on in cancer

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and tumor suppressor genes
that are turned off to cause cancer.

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You might think
that we learned about oncogenes

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and tumor suppressor genes
from common cancers

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like breast cancer and prostate cancer

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and lung cancer,

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but you'd be wrong.

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We learned about oncogenes
and tumor suppressor genes

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for the first time

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in that itty-bitty little one percent
of cancers called sarcoma.

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In 1966, Peyton Rous got the Nobel Prize

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for realizing that chickens

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had a transmissible form of sarcoma.

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Thirty years later, Harold Varmus
and Mike Bishop discovered

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what that transmissible element was.

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It was a virus

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carrying a gene,

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the src oncogene.

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Now, I will not tell you
that src is the most important oncogene.

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I will not tell you

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that src is the most frequently
turned on oncogene in all of cancer.

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But it was the first oncogene.

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The exception, the outlier

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drew our attention and led us to something

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that taught us very important things
about the rest of biology.

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Now, TP53 is the most important
tumor suppressor gene.

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It is the most frequently turned off
tumor suppressor gene

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in almost every kind of cancer.

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But we didn't learn about it
from common cancers.

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We learned about it
when doctors Li and Fraumeni

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were looking at families,

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and they realized that these families

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had way too many sarcomas.

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I told you that sarcoma is rare.

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Remember that a one
in a million diagnosis,

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if it happens twice in one family,

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is way too common in that family.

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The very fact that these are rare

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draws our attention

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and leads us to new kinds of thinking.

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Now, many of you may say,

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and may rightly say,

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that yeah, Kevin, that's great,

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but you're not talking
about a bird's wing.

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You're not talking about moons
floating around some planet Jupiter.

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This is a person.

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This outlier, this exception,
may lead to the advancement of science,

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but this is a person.

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And all I can say

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is that I know that all too well.

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I have conversations with these patients
with rare and deadly diseases.

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I write about these conversations.

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These conversations are terribly fraught.

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They're fraught with horrible phrases

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like "I have bad news"
or "There's nothing more we can do."

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Sometimes these conversations
turn on a single word:

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"terminal."

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Silence can also be rather uncomfortable.

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Where the blanks are in medicine

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can be just as important

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as the words that we use
in these conversations.

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What are the unknowns?

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What are the experiments
that are being done?

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Do this little exercise with me.

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Up there on the screen,
you see this phrase, "no where."

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Notice where the blank is.

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If we move that blank one space over

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"no where"

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becomes "now here,"

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the exact opposite meaning,

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just by shifting the blank one space over.

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I'll never forget the night

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that I walked into
one of my patients' rooms.

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I had been operating long that day

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but I still wanted to come and see him.

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He was a boy I had diagnosed
with a bone cancer a few days before.

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He and his mother had been meeting
with the chemotherapy doctors

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earlier that day,

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and he had been admitted
to the hospital to begin chemotherapy.

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It was almost midnight
when I got to his room.

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He was asleep, but I found his mother

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reading by flashlight

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next to his bed.

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She came out in the hall
to chat with me for a few minutes.

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It turned out that
what she had been reading

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was the protocol
that the chemotherapy doctors

261
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had given her that day.

262
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She had memorized it.

263
00:12:35,900 --> 00:12:39,436
She said, "Dr. Jones, you told me

264
00:12:39,460 --> 00:12:41,636
that we don't always win

265
00:12:41,660 --> 00:12:42,940
with this type of cancer,

266
00:12:44,380 --> 00:12:47,860
but I've been studying this protocol,
and I think I can do it.

267
00:12:48,660 --> 00:12:52,236
I think I can comply
with these very difficult treatments.

268
00:12:52,260 --> 00:12:55,236
I'm going to quit my job.
I'm going to move in with my parents.

269
00:12:55,260 --> 00:12:57,220
I'm going to keep my baby safe."

270
00:13:00,020 --> 00:13:01,220
I didn't tell her.

271
00:13:02,540 --> 00:13:05,460
I didn't stop to correct her thinking.

272
00:13:05,864 --> 00:13:08,451
To shift that blank to where it should be.

273
00:13:09,133 --> 00:13:11,863
The experiment wasn't whether or not
she could comply

274
00:13:11,888 --> 00:13:13,648
with this very difficult protocol.

275
00:13:15,380 --> 00:13:17,636
She was trusting in a protocol

276
00:13:17,660 --> 00:13:20,876
that even if complied with,

277
00:13:20,900 --> 00:13:23,300
wouldn't necessarily save her son.

278
00:13:25,660 --> 00:13:26,860
I didn't tell her.

279
00:13:28,060 --> 00:13:29,460
I didn't fill in that blank.

280
00:13:30,780 --> 00:13:32,756
But a year and a half later

281
00:13:32,780 --> 00:13:35,500
her boy nonetheless died of his cancer.

282
00:13:37,100 --> 00:13:38,420
Should I have told her?

283
00:13:41,160 --> 00:13:43,416
Now, many of you may say, "So what?

284
00:13:43,440 --> 00:13:44,696
I don't have sarcoma.

285
00:13:44,720 --> 00:13:46,616
No one in my family has sarcoma.

286
00:13:46,640 --> 00:13:48,096
And this is all fine and well,

287
00:13:48,120 --> 00:13:50,816
but it probably doesn't
matter in my life."

288
00:13:50,840 --> 00:13:52,096
And you're probably right.

289
00:13:52,120 --> 00:13:54,800
Sarcoma may not matter
a whole lot in your life.

290
00:13:56,840 --> 00:13:59,176
But where the blanks are in medicine

291
00:13:59,200 --> 00:14:00,520
does matter in your life.

292
00:14:02,320 --> 00:14:04,616
I didn't tell you one dirty little secret.

293
00:14:04,640 --> 00:14:09,016
I told you that in medicine,
we test predictions in populations,

294
00:14:09,040 --> 00:14:10,296
but I didn't tell you,

295
00:14:10,320 --> 00:14:12,536
and so often medicine never tells you

296
00:14:12,560 --> 00:14:15,416
that every time an individual

297
00:14:15,440 --> 00:14:17,536
encounters medicine,

298
00:14:17,560 --> 00:14:21,600
even if that individual is firmly
embedded in the general population,

299
00:14:24,160 --> 00:14:26,536
neither the individual
nor the physician knows

300
00:14:26,560 --> 00:14:29,240
where in that population
the individual will land.

301
00:14:29,840 --> 00:14:32,536
Therefore, every encounter with medicine

302
00:14:32,560 --> 00:14:34,000
is an experiment.

303
00:14:34,720 --> 00:14:36,736
You will be a subject

304
00:14:36,760 --> 00:14:38,440
in an experiment.

305
00:14:39,470 --> 00:14:44,310
And the outcome will be either
a better or a worse result for you.

306
00:14:45,720 --> 00:14:47,736
As long as medicine works well,

307
00:14:47,760 --> 00:14:50,776
we're fine with fast service,

308
00:14:50,800 --> 00:14:54,240
bravado, brimmingly
confident conversations.

309
00:14:55,120 --> 00:14:56,776
But when things don't work well,

310
00:14:56,800 --> 00:14:58,640
sometimes we want something different.

311
00:14:59,920 --> 00:15:03,200
A colleague of mine
removed a tumor from a patient's limb.

312
00:15:04,320 --> 00:15:06,136
He was concerned about this tumor.

313
00:15:06,160 --> 00:15:09,176
In our physician conferences,
he talked about his concern

314
00:15:09,200 --> 00:15:10,616
that this was a type of tumor

315
00:15:10,640 --> 00:15:13,200
that had a high risk
for coming back in the same limb.

316
00:15:14,080 --> 00:15:16,056
But his conversations with the patient

317
00:15:16,080 --> 00:15:18,176
were exactly what a patient might want:

318
00:15:18,200 --> 00:15:19,456
brimming with confidence.

319
00:15:19,480 --> 00:15:22,496
He said, "I got it all
and you're good to go."

320
00:15:22,520 --> 00:15:24,256
She and her husband were thrilled.

321
00:15:24,280 --> 00:15:28,360
They went out, celebrated, fancy dinner,
opened a bottle of champagne.

322
00:15:29,440 --> 00:15:31,736
The only problem was a few weeks later,

323
00:15:31,760 --> 00:15:34,856
she started to notice
another nodule in the same area.

324
00:15:34,880 --> 00:15:39,016
It turned out he hadn't gotten it all,
and she wasn't good to go.

325
00:15:40,340 --> 00:15:43,180
But what happened at this juncture
absolutely fascinates me.

326
00:15:43,900 --> 00:15:45,516
My colleague came to me and said,

327
00:15:45,540 --> 00:15:48,260
"Kevin, would you mind
looking after this patient for me?"

328
00:15:48,940 --> 00:15:52,156
I said, "Why, you know the right thing
to do as well as I do.

329
00:15:52,180 --> 00:15:53,796
You haven't done anything wrong."

330
00:15:53,820 --> 00:15:58,300
He said, "Please, just look
after this patient for me."

331
00:15:59,900 --> 00:16:01,436
He was embarrassed...

332
00:16:01,460 --> 00:16:02,860
Not by what he had done,

333
00:16:03,854 --> 00:16:05,780
but by the conversation that he had had,

334
00:16:06,460 --> 00:16:07,900
by the overconfidence.

335
00:16:09,300 --> 00:16:11,916
So I performed
a much more invasive surgery

336
00:16:11,940 --> 00:16:15,076
and had a very different conversation
with the patient afterwards.

337
00:16:15,100 --> 00:16:17,436
I said, "Most likely I've gotten it all

338
00:16:17,460 --> 00:16:19,876
and you're most likely good to go,

339
00:16:19,900 --> 00:16:23,060
but this is the experiment
that we're doing.

340
00:16:23,740 --> 00:16:25,756
This is what you're going to watch for.

341
00:16:25,780 --> 00:16:27,676
This is what I'm going to watch for.

342
00:16:27,700 --> 00:16:31,636
And we're going to work together
to find out if this surgery will work

343
00:16:31,660 --> 00:16:32,980
to get rid of your cancer."

344
00:16:33,620 --> 00:16:35,556
I can guarantee you, she and her husband

345
00:16:35,580 --> 00:16:38,500
did not crack another bottle of champagne
after talking to me.

346
00:16:40,300 --> 00:16:43,156
But she was now a scientist,

347
00:16:43,180 --> 00:16:46,540
not only a subject in her experiment.

348
00:16:48,660 --> 00:16:50,276
And so I encourage you

349
00:16:50,300 --> 00:16:53,756
to seek humility and curiosity

350
00:16:53,780 --> 00:16:54,980
in your physicians.

351
00:16:56,860 --> 00:16:59,836
Almost 20 billion times each year,

352
00:16:59,860 --> 00:17:03,796
a person walks into a doctor's office,

353
00:17:03,820 --> 00:17:06,099
and that person becomes a patient.

354
00:17:07,420 --> 00:17:10,940
You or someone you love
will be that patient sometime very soon.

355
00:17:11,940 --> 00:17:13,579
How will you talk to your doctors?

356
00:17:14,740 --> 00:17:15,940
What will you tell them?

357
00:17:16,859 --> 00:17:18,380
What will they tell you?

358
00:17:20,700 --> 00:17:22,915
They cannot tell you

359
00:17:22,940 --> 00:17:24,460
what they do not know,

360
00:17:25,660 --> 00:17:29,220
but they can tell you when they don't know

361
00:17:30,380 --> 00:17:31,740
if only you'll ask.

362
00:17:32,260 --> 00:17:35,100
So please, join the conversation.

363
00:17:36,300 --> 00:17:37,516
Thank you.

364
00:17:37,540 --> 00:17:40,408
(Applause)