0:00:09.840,0:00:11.040
Science.

0:00:11.760,0:00:15.176
The very word for many of you conjures[br]unhappy memories of boredom

0:00:15.200,0:00:18.096
in high school biology or physics class.

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But let me assure that what you did there

0:00:21.240,0:00:23.416
had very little to do with science.

0:00:23.440,0:00:25.736
That was really the "what" of science.

0:00:25.760,0:00:28.480
It was the history[br]of what other people had discovered.

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What I'm most interested in as a scientist

0:00:32.080,0:00:34.216
is the "how" of science.

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Because science is knowledge in process.

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We make an observation,[br]guess an explanation for that observation,

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and then make a prediction[br]that we can test

0:00:43.640,0:00:45.560
with an experiment or other observation.

0:00:46.080,0:00:47.416
A couple of examples.

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

0:00:51.040,0:00:54.920
and both the Sun and the Moon[br]seemed to go around them.

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Their guessed explanation

0:00:57.280,0:01:00.360
was that the Earth must be[br]the center of the universe.

0:01:01.240,0:01:04.440
The prediction: everything[br]should circle around the Earth.

0:01:05.319,0:01:06.976
This was first really tested

0:01:07.000,0:01:09.816
when Galileo got his hands[br]on one of the first telescopes,

0:01:09.840,0:01:12.216
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[br]to follow the path of Jupiter

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and found that Jupiter[br]also was not going around the Earth

0:01:31.320,0:01:33.280
but around the Sun.

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So the prediction test failed.

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And this led to[br]the discarding of the theory

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that the Earth was the center[br]of the universe.

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

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The guessed explanation was gravity,

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the prediction that everything[br]should fall to the Earth.

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But of course, not everything[br]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,[br]gravity pulls things to the Earth

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unless there is an equal[br]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[br]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[br]from that line of thinking.

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So the test failures,[br]the exceptions, the outliers

0:02:29.100,0:02:34.481
teach us what we don't know[br]and lead us to something new.

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This is how science moves forward.[br]This is how science learns.

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Sometimes in the media,[br]and even more rarely,

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but sometimes even scientists will say

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that something or other[br]has been scientifically proven.

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But I hope that you understand[br]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[br]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[br]to different people,

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but most of our[br]public discourse on medicine

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really turns it into[br]an engineering problem.

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We have the hallways of Congress,

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and the boardrooms of insurance companies[br]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[br]how best to distribute medicine,

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and the hospitals and physicians[br]are absolutely obsessed

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with their protocols and checklists,

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trying to figure out[br]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[br]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[br]that in this climate,

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many of our institutions[br]for the provision of health care

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start to look a heck of a lot[br]like Jiffy Lube.

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(Laughter)

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

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I didn't get one of those[br]little doohickeys

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that your mechanic[br]has to plug into your car

0:04:18.760,0:04:21.136
and find out exactly what's wrong with it,

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because the textbook of medicine

0:04:23.280,0:04:24.800
is not closed.

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Medicine is science.

0:04:27.560,0:04:30.240
Medicine is knowledge in process.

0:04:31.280,0:04:32.656
We make an observation,

0:04:32.680,0:04:34.815
we guess an explanation[br]of that observation,

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and then we make a prediction[br]that we can test.

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Now, the testing ground[br]of most predictions in medicine

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is populations.

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And you may remember[br]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[br]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,

0:05:03.880,0:05:06.136
our knowledge and our know-how,

0:05:06.160,0:05:08.416
comes from populations

0:05:08.440,0:05:11.216
but extends only as far

0:05:11.240,0:05:12.976
as the next outlier,

0:05:13.000,0:05:14.216
the next exception,

0:05:14.240,0:05:15.976
which, like Jupiter's moons,

0:05:16.000,0:05:18.400
will teach us what we don't actually know.

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Now, I am a surgeon

0:05:20.940,0:05:23.356
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[br]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[br]for a sarcoma patient

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

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

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People talk about thinking[br]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[br]a bath in the uncertainty

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and unknowns and exceptions[br]and outliers that surround us in sarcoma

0:06:01.100,0:06:05.636
is easy access to what I think[br]are those two most important values

0:06:05.660,0:06:07.196
for any science:

0:06:07.220,0:06:09.420
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[br]albeit distinct patient with sarcoma.

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We'll even establish[br]international collaborations.

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Those patients will start[br]to talk to each other through chat rooms

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and support groups.

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It's through this kind[br]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

0:06:39.920,0:06:41.600
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[br]the ankle to serve as the knee

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when we have to remove the knee[br]with the cancer.

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He can then wear a prosthetic[br]and run and jump and play.

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This opportunity was available to him

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because of international collaborations.

0:07:02.800,0:07:04.496
It was desirable to him

0:07:04.520,0:07:07.480
because he had contacted other patients[br]who had experienced it.

0:07:08.520,0:07:12.576
And so exceptions and outliers in medicine

0:07:12.600,0:07:16.560
teach us what we don't know,[br]but also lead us to new thinking.

0:07:17.680,0:07:19.536
Now, very importantly,

0:07:19.560,0:07:23.416
all the new thinking that outliers[br]and exceptions lead us to in medicine

0:07:23.440,0:07:26.800
does not only apply[br]to the outliers and exceptions.

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It is not that we only learn[br]from sarcoma patients

0:07:30.720,0:07:32.680
ways to manage sarcoma patients.

0:07:33.520,0:07:35.576
Sometimes, the outliers

0:07:35.600,0:07:37.296
and the exceptions

0:07:37.320,0:07:40.560
teach us things that matter quite a lot[br]to the general population.

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Like a tree standing outside a forest,

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the outliers and the exceptions[br]draw our attention

0:07:48.680,0:07:53.532
and lead us into a much greater sense[br]of perhaps what a tree is.

0:07:54.340,0:07:56.836
We often talk about[br]losing the forests for the trees,

0:07:56.860,0:07:58.676
but one also loses a tree

0:07:58.700,0:08:00.220
within a forest.

0:08:01.700,0:08:03.556
But the tree that stands out by itself

0:08:03.580,0:08:06.476
makes those relationships[br]that define a tree,

0:08:06.500,0:08:10.316
the relationships between trunk[br]and roots and branches,

0:08:10.340,0:08:11.580
much more apparent.

0:08:12.060,0:08:13.756
Even if that tree is crooked

0:08:13.780,0:08:16.756
or even if that tree[br]has very unusual relationships

0:08:16.780,0:08:19.076
between trunk and roots and branches,

0:08:19.100,0:08:21.796
it nonetheless draws our attention

0:08:21.820,0:08:23.716
and allows us to make observations

0:08:23.740,0:08:25.980
that we can then test[br]in the general population.

0:08:26.700,0:08:28.676
I told you that sarcomas are rare.

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They make up about one percent[br]of all cancers.

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

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By genetic disease we mean[br]that cancer is caused by oncogenes

0:08:39.900,0:08:41.275
that are turned on in cancer

0:08:41.299,0:08:44.340
and tumor suppressor genes[br]that are turned off to cause cancer.

0:08:44.860,0:08:47.276
You might think[br]that we learned about oncogenes

0:08:47.300,0:08:49.516
and tumor suppressor genes[br]from common cancers

0:08:49.540,0:08:51.516
like breast cancer and prostate cancer

0:08:51.540,0:08:53.036
and lung cancer,

0:08:53.060,0:08:54.259
but you'd be wrong.

0:08:54.700,0:08:57.595
We learned about oncogenes[br]and tumor suppressor genes

0:08:57.619,0:08:58.835
for the first time

0:08:58.859,0:09:02.300
in that itty-bitty little one percent[br]of cancers called sarcoma.

0:09:03.460,0:09:06.036
In 1966, Peyton Rous got the Nobel Prize

0:09:06.060,0:09:08.076
for realizing that chickens

0:09:08.100,0:09:11.220
had a transmissible form of sarcoma.

0:09:11.960,0:09:14.796
Thirty years later, Harold Varmus[br]and Mike Bishop discovered

0:09:14.820,0:09:17.356
what that transmissible element was.

0:09:17.380,0:09:18.956
It was a virus

0:09:18.980,0:09:20.396
carrying a gene,

0:09:20.420,0:09:21.860
the src oncogene.

0:09:22.580,0:09:26.236
Now, I will not tell you[br]that src is the most important oncogene.

0:09:26.260,0:09:27.476
I will not tell you

0:09:27.500,0:09:30.996
that src is the most frequently[br]turned on oncogene in all of cancer.

0:09:31.020,0:09:33.460
But it was the first oncogene.

0:09:34.660,0:09:36.996
The exception, the outlier

0:09:37.020,0:09:39.540
drew our attention and led us to something

0:09:40.220,0:09:44.260
that taught us very important things[br]about the rest of biology.

0:09:45.580,0:09:49.676
Now, TP53 is the most important[br]tumor suppressor gene.

0:09:49.700,0:09:52.436
It is the most frequently turned off[br]tumor suppressor gene

0:09:52.460,0:09:54.260
in almost every kind of cancer.

0:09:55.060,0:09:57.356
But we didn't learn about it[br]from common cancers.

0:09:57.380,0:09:59.796
We learned about it[br]when doctors Li and Fraumeni

0:09:59.820,0:10:01.396
were looking at families,

0:10:01.420,0:10:03.436
and they realized that these families

0:10:03.460,0:10:05.980
had way too many sarcomas.

0:10:06.620,0:10:08.396
I told you that sarcoma is rare.

0:10:08.420,0:10:11.596
Remember that a one[br]in a million diagnosis,

0:10:11.620,0:10:13.756
if it happens twice in one family,

0:10:13.780,0:10:16.180
is way too common in that family.

0:10:17.340,0:10:20.036
The very fact that these are rare

0:10:20.060,0:10:21.500
draws our attention

0:10:22.460,0:10:24.700
and leads us to new kinds of thinking.

0:10:26.180,0:10:27.636
Now, many of you may say,

0:10:27.660,0:10:29.196
and may rightly say,

0:10:29.220,0:10:31.116
that yeah, Kevin, that's great,

0:10:31.140,0:10:33.196
but you're not talking[br]about a bird's wing.

0:10:33.220,0:10:36.700
You're not talking about moons[br]floating around some planet Jupiter.

0:10:37.220,0:10:38.756
This is a person.

0:10:38.780,0:10:42.036
This outlier, this exception,[br]may lead to the advancement of science,

0:10:42.060,0:10:43.260
but this is a person.

0:10:44.980,0:10:46.596
And all I can say

0:10:46.620,0:10:48.980
is that I know that all too well.

0:10:50.460,0:10:53.860
I have conversations with these patients[br]with rare and deadly diseases.

0:10:54.500,0:10:56.436
I write about these conversations.

0:10:56.460,0:10:58.756
These conversations are terribly fraught.

0:10:58.780,0:11:00.596
They're fraught with horrible phrases

0:11:00.620,0:11:03.860
like "I have bad news"[br]or "There's nothing more we can do."

0:11:04.460,0:11:07.660
Sometimes these conversations[br]turn on a single word:

0:11:08.460,0:11:09.660
"terminal."

0:11:17.620,0:11:20.540
Silence can also be rather uncomfortable.

0:11:22.060,0:11:24.636
Where the blanks are in medicine

0:11:24.660,0:11:26.516
can be just as important

0:11:26.540,0:11:28.780
as the words that we use[br]in these conversations.

0:11:29.780,0:11:31.316
What are the unknowns?

0:11:31.340,0:11:33.540
What are the experiments[br]that are being done?

0:11:34.380,0:11:36.076
Do this little exercise with me.

0:11:36.100,0:11:39.316
Up there on the screen,[br]you see this phrase, "no where."

0:11:39.340,0:11:40.620
Notice where the blank is.

0:11:41.380,0:11:44.580
If we move that blank one space over

0:11:45.340,0:11:46.916
"no where"

0:11:46.940,0:11:49.636
becomes "now here,"

0:11:49.660,0:11:51.556
the exact opposite meaning,

0:11:51.580,0:11:53.780
just by shifting the blank one space over.

0:11:56.380,0:11:57.956
I'll never forget the night

0:11:57.980,0:12:00.220
that I walked into[br]one of my patients' rooms.

0:12:00.980,0:12:02.636
I had been operating long that day

0:12:02.660,0:12:04.676
but I still wanted to come and see him.

0:12:04.700,0:12:07.900
He was a boy I had diagnosed[br]with a bone cancer a few days before.

0:12:08.540,0:12:11.596
He and his mother had been meeting[br]with the chemotherapy doctors

0:12:11.620,0:12:12.836
earlier that day,

0:12:12.860,0:12:15.836
and he had been admitted[br]to the hospital to begin chemotherapy.

0:12:15.860,0:12:18.036
It was almost midnight[br]when I got to his room.

0:12:18.060,0:12:20.236
He was asleep, but I found his mother

0:12:20.260,0:12:21.836
reading by flashlight

0:12:21.860,0:12:23.316
next to his bed.

0:12:23.340,0:12:26.140
She came out in the hall[br]to chat with me for a few minutes.

0:12:26.980,0:12:29.076
It turned out that[br]what she had been reading

0:12:29.100,0:12:31.276
was the protocol[br]that the chemotherapy doctors

0:12:31.300,0:12:32.540
had given her that day.

0:12:32.900,0:12:34.140
She had memorized it.

0:12:35.900,0:12:39.436
She said, "Dr. Jones, you told me

0:12:39.460,0:12:41.636
that we don't always win

0:12:41.660,0:12:42.940
with this type of cancer,

0:12:44.380,0:12:47.860
but I've been studying this protocol,[br]and I think I can do it.

0:12:48.660,0:12:52.236
I think I can comply[br]with these very difficult treatments.

0:12:52.260,0:12:55.236
I'm going to quit my job.[br]I'm going to move in with my parents.

0:12:55.260,0:12:57.220
I'm going to keep my baby safe."

0:13:00.020,0:13:01.220
I didn't tell her.

0:13:02.540,0:13:05.460
I didn't stop to correct her thinking.

0:13:05.864,0:13:08.451
To shift that blank to where it should be.

0:13:09.133,0:13:11.863
The experiment wasn't whether or not[br]she could comply

0:13:11.888,0:13:13.648
with this very difficult protocol.

0:13:15.380,0:13:17.636
She was trusting in a protocol

0:13:17.660,0:13:20.876
that even if complied with,

0:13:20.900,0:13:23.300
wouldn't necessarily save her son.

0:13:25.660,0:13:26.860
I didn't tell her.

0:13:28.060,0:13:29.460
I didn't fill in that blank.

0:13:30.780,0:13:32.756
But a year and a half later

0:13:32.780,0:13:35.500
her boy nonetheless died of his cancer.

0:13:37.100,0:13:38.420
Should I have told her?

0:13:41.160,0:13:43.416
Now, many of you may say, "So what?

0:13:43.440,0:13:44.696
I don't have sarcoma.

0:13:44.720,0:13:46.616
No one in my family has sarcoma.

0:13:46.640,0:13:48.096
And this is all fine and well,

0:13:48.120,0:13:50.816
but it probably doesn't[br]matter in my life."

0:13:50.840,0:13:52.096
And you're probably right.

0:13:52.120,0:13:54.800
Sarcoma may not matter[br]a whole lot in your life.

0:13:56.840,0:13:59.176
But where the blanks are in medicine

0:13:59.200,0:14:00.520
does matter in your life.

0:14:02.320,0:14:04.616
I didn't tell you one dirty little secret.

0:14:04.640,0:14:09.016
I told you that in medicine,[br]we test predictions in populations,

0:14:09.040,0:14:10.296
but I didn't tell you,

0:14:10.320,0:14:12.536
and so often medicine never tells you

0:14:12.560,0:14:15.416
that every time an individual

0:14:15.440,0:14:17.536
encounters medicine,

0:14:17.560,0:14:21.600
even if that individual is firmly[br]embedded in the general population,

0:14:24.160,0:14:26.536
neither the individual[br]nor the physician knows

0:14:26.560,0:14:29.240
where in that population[br]the individual will land.

0:14:29.840,0:14:32.536
Therefore, every encounter with medicine

0:14:32.560,0:14:34.000
is an experiment.

0:14:34.720,0:14:36.736
You will be a subject

0:14:36.760,0:14:38.440
in an experiment.

0:14:39.470,0:14:44.310
And the outcome will be either[br]a better or a worse result for you.

0:14:45.720,0:14:47.736
As long as medicine works well,

0:14:47.760,0:14:50.776
we're fine with fast service,

0:14:50.800,0:14:54.240
bravado, brimmingly[br]confident conversations.

0:14:55.120,0:14:56.776
But when things don't work well,

0:14:56.800,0:14:58.640
sometimes we want something different.

0:14:59.920,0:15:03.200
A colleague of mine[br]removed a tumor from a patient's limb.

0:15:04.320,0:15:06.136
He was concerned about this tumor.

0:15:06.160,0:15:09.176
In our physician conferences,[br]he talked about his concern

0:15:09.200,0:15:10.616
that this was a type of tumor

0:15:10.640,0:15:13.200
that had a high risk[br]for coming back in the same limb.

0:15:14.080,0:15:16.056
But his conversations with the patient

0:15:16.080,0:15:18.176
were exactly what a patient might want:

0:15:18.200,0:15:19.456
brimming with confidence.

0:15:19.480,0:15:22.496
He said, "I got it all[br]and you're good to go."

0:15:22.520,0:15:24.256
She and her husband were thrilled.

0:15:24.280,0:15:28.360
They went out, celebrated, fancy dinner,[br]opened a bottle of champagne.

0:15:29.440,0:15:31.736
The only problem was a few weeks later,

0:15:31.760,0:15:34.856
she started to notice[br]another nodule in the same area.

0:15:34.880,0:15:39.016
It turned out he hadn't gotten it all,[br]and she wasn't good to go.

0:15:40.340,0:15:43.180
But what happened at this juncture[br]absolutely fascinates me.

0:15:43.900,0:15:45.516
My colleague came to me and said,

0:15:45.540,0:15:48.260
"Kevin, would you mind[br]looking after this patient for me?"

0:15:48.940,0:15:52.156
I said, "Why, you know the right thing[br]to do as well as I do.

0:15:52.180,0:15:53.796
You haven't done anything wrong."

0:15:53.820,0:15:58.300
He said, "Please, just look[br]after this patient for me."

0:15:59.900,0:16:01.436
He was embarrassed...

0:16:01.460,0:16:02.860
Not by what he had done,

0:16:03.854,0:16:05.780
but by the conversation that he had had,

0:16:06.460,0:16:07.900
by the overconfidence.

0:16:09.300,0:16:11.916
So I performed[br]a much more invasive surgery

0:16:11.940,0:16:15.076
and had a very different conversation[br]with the patient afterwards.

0:16:15.100,0:16:17.436
I said, "Most likely I've gotten it all

0:16:17.460,0:16:19.876
and you're most likely good to go,

0:16:19.900,0:16:23.060
but this is the experiment[br]that we're doing.

0:16:23.740,0:16:25.756
This is what you're going to watch for.

0:16:25.780,0:16:27.676
This is what I'm going to watch for.

0:16:27.700,0:16:31.636
And we're going to work together[br]to find out if this surgery will work

0:16:31.660,0:16:32.980
to get rid of your cancer."

0:16:33.620,0:16:35.556
I can guarantee you, she and her husband

0:16:35.580,0:16:38.500
did not crack another bottle of champagne[br]after talking to me.

0:16:40.300,0:16:43.156
But she was now a scientist,

0:16:43.180,0:16:46.540
not only a subject in her experiment.

0:16:48.660,0:16:50.276
And so I encourage you

0:16:50.300,0:16:53.756
to seek humility and curiosity

0:16:53.780,0:16:54.980
in your physicians.

0:16:56.860,0:16:59.836
Almost 20 billion times each year,

0:16:59.860,0:17:03.796
a person walks into a doctor's office,

0:17:03.820,0:17:06.099
and that person becomes a patient.

0:17:07.420,0:17:10.940
You or someone you love[br]will be that patient sometime very soon.

0:17:11.940,0:17:13.579
How will you talk to your doctors?

0:17:14.740,0:17:15.940
What will you tell them?

0:17:16.859,0:17:18.380
What will they tell you?

0:17:20.700,0:17:22.915
They cannot tell you

0:17:22.940,0:17:24.460
what they do not know,

0:17:25.660,0:17:29.220
but they can tell you when they don't know

0:17:30.380,0:17:31.740
if only you'll ask.

0:17:32.260,0:17:35.100
So please, join the conversation.

0:17:36.300,0:17:37.516
Thank you.

0:17:37.540,0:17:40.408
(Applause)