summarize this "During my stint away from medicine, I realized that my colleagues and I had
been trained to solve the problems of an earlier era: the acute illnesses and
injuries that Medicine 2.0 had evolved to treat. Those problems had a much
shorter event horizon; for our cancer patients, time itself was the enemy. And
we were always coming in too late.
This actually wasn’t so obvious until I’d spent my little sabbatical
immersed in the worlds of mathematics and finance, thinking every day about
the nature of risk. The banks’ problem was not all that different from the
situation faced by some of my patients: their seemingly minor risk factors
had, over time, compounded into an unstoppable, asymmetric catastrophe.
Chronic diseases work in a similar fashion, building over years and decades—
and once they become entrenched, it’s hard to make them go away.
Atherosclerosis, for example, begins many decades before the person has a
coronary “event” that could result in their death. But that event, often a heart
attack, too often marks the point where treatment begins.
This is why I believe we need a new way of thinking about chronic
diseases, their treatment, and how to maintain long-term health. The goal of
this new medicine—which I call Medicine 3.0—is not to patch people up and
get them out the door, removing their tumors and hoping for the best, but
rather to prevent the tumors from appearing and spreading in the first place.
Or to avoid that first heart attack. Or to divert someone from the path to
Alzheimer’s disease. Our treatments, and our prevention and detection
strategies, need to change to fit the nature of these diseases, with their long,
slow prologues.
It is already obvious that medicine is changing rapidly in our era. Many
pundits have been predicting a glorious new era of “personalized” or
“precision” medicine, where our care will be tailored to our exact needs,
down to our very genes. This is, obviously, a worthy goal; it is clear that no
two patients are exactly alike, even when they are presenting with what
appears to be an identical upper-respiratory illness. A treatment that works
for one patient may prove useless in the other, either because her immune
system is reacting differently or because her infection is viral rather than
bacterial. Even now, it remains extremely difficult to tell the difference,
resulting in millions of useless antibiotic prescriptions.
Many thinkers in this space believe that this new era will be driven by
advances in technology, and they are likely right; at the same time, however,
technology has (so far) been largely a limiting factor. Let me explain. On the
one hand, improved technology enables us to collect much more data on
patients than ever before, and patients themselves are better able to monitor
their own biomarkers. This is good. Even better, artificial intelligence and
machine learning are being harnessed to try to digest this massive profusion
of data and come up with more definitive assessments of our risk of, say,
heart disease than the rather simple risk factor–based calculators we have
now. Others point to the possibilities of nanotechnology, which could enable
doctors to diagnose and treat disease by means of microscopic bioactive
particles injected into the bloodstream. But the nanobots aren’t here yet, and
barring a major public or private research push, it could be a while before
they become reality.
The problem is that our idea of personalized or precision medicine
remains some distance ahead of the technology necessary to realize its full
promise. It’s a bit like the concept of the self-driving car, which has been
talked about for almost as long as automobiles have been crashing into each
other and killing and injuring people. Clearly, removing human error from
the equation as much as possible would be a good thing. But our technology
is only today catching up to a vision we’ve held for decades.
If you had wanted to create a “self-driving” car in the 1950s, your best
option might have been to strap a brick to the accelerator. Yes, the vehicle
would have been able to move forward on its own, but it could not slow down,
stop, or turn to avoid obstacles. Obviously not ideal. But does that mean the
entire concept of the self-driving car is not worth pursuing? No, it only means
that at the time we did not yet have the tools we now possess to help enable
vehicles to operate both autonomously and safely: computers, sensors,
artificial intelligence, machine learning, and so on. This once-distant dream
now seems within our reach.
It is much the same story in medicine. Two decades ago, we were still
taping bricks to gas pedals, metaphorically speaking. Today, we are
approaching the point where we can begin to bring some appropriate
technology to bear in ways that advance our understanding of patients as
unique individuals. For example, doctors have traditionally relied on two tests
to gauge their patients’ metabolic health: a fasting glucose test, typically given
once a year; or the HbA1c test we mentioned earlier, which gives us an
estimate of their average blood glucose over the last 90 days. But those tests
are of limited use because they are static and backward-looking. So instead,
many of my patients have worn a device that monitors their blood glucose
levels in real time,  which allows me to talk to them about nutrition in a
specific, nuanced, feedback-driven way that was not even possible a decade
ago. This technology, known as continuous glucose monitoring (CGM), lets
me observe how their individual metabolism responds to a certain eating
pattern and make changes to their diet quickly. In time, we will have many
more sensors like this that will allow us to tailor our therapies and
interventions far more quickly and precisely. The self-driving car will do a
better job of following the twists and turns of the road, staying out of the
ditch.
But Medicine 3.0, in my opinion, is not really about technology; rather, it
requires an evolution in our mindset, a shift in the way in which we approach
medicine. I’ve broken it down into four main points.
First, Medicine 3.0 places a far greater emphasis on prevention than
treatment. When did Noah build the ark? Long before it began to rain.
Medicine 2.0 tries to figure out how to get dry after it starts raining. Medicine
3.0 studies meteorology and tries to determine whether we need to build a
better roof, or a boat.
Second, Medicine 3.0 considers the patient as a unique individual.
Medicine 2.0 treats everyone as basically the same, obeying the findings of
the clinical trials that underlie evidence-based medicine. These trials take
heterogeneous inputs (the people in the study or studies) and come up with
homogeneous results (the average result across all those people). Evidencebased medicine then insists that we apply those average findings back to
individuals. The problem is that no patient is strictly average. Medicine 3.0
takes the findings of evidence-based medicine and goes one step further,
looking more deeply into the data to determine how our patient is similar or
different from the “average” subject in the study, and how its findings might
or might not be applicable to them. Think of it as “evidence-informed”
medicine.
The third philosophical shift has to do with our attitude toward risk. In
Medicine 3.0, our starting point is the honest assessment, and acceptance, of
risk—including the risk of doing nothing.
There are many examples of how Medicine 2.0 gets risk wrong, but one
of the most egregious has to do with hormone replacement therapy (HRT) for
postmenopausal women, long entrenched as standard practice before the
results of the Women’s Health Initiative Study (WHI) were published in
2002. This large clinical trial, involving thousands of older women, compared
a multitude of health outcomes in women taking HRT versus those who did
not take it. The study reported a 24 percent relative increase in the risk of
breast cancer among a subset of women taking HRT, and headlines all over
the world condemned HRT as a dangerous, cancer-causing therapy. All of a
sudden, on the basis of this one study, hormone replacement treatment
became virtually taboo.
This reported 24 percent risk increase sounded scary indeed. But nobody
seemed to care that the absolute risk increase of breast cancer for women
in the study remained minuscule. Roughly five out of every one thousand
women in the HRT group developed breast cancer, versus four out of every
one thousand in the control group, who received no hormones. The absolute
risk increase was just 0.1 percentage point. HRT was linked to, potentially,
one additional case of breast cancer in every thousand patients. Yet this tiny
increase in absolute risk was deemed to outweigh any benefits, meaning
menopausal women would potentially be subject to hot flashes and night
sweats, as well as loss of bone density and muscle mass, and other unpleasant
symptoms of menopause—not to mention a potentially increased risk of
Alzheimer’s disease, as we’ll see in chapter 9.
Medicine 2.0 would rather throw out this therapy entirely, on the basis of
one clinical trial, than try to understand and address the nuances involved.
Medicine 3.0 would take this study into account, while recognizing its
inevitable limitations and built-in biases. The key question that Medicine 3.0
asks is whether this intervention, hormone replacement therapy, with its
relatively small increase in average risk in a large group of women older than
sixty-five, might still be net beneficial for our individual patient, with her own
unique mix of symptoms and risk factors. How is she similar to or different
from the population in the study? One huge difference: none of the women
selected for the study were actually symptomatic, and most were many years
out of menopause. So how applicable are the findings of this study to women
who are in or just entering menopause (and are presumably younger)?
Finally, is there some other possible explanation for the slight observed
increase in risk with this specific HRT protocol?[*3]
My broader point is that at the level of the individual patient, we should
be willing to ask deeper questions of risk versus reward versus cost for this
therapy—and for almost anything else we might do.
The fourth and perhaps largest shift is that where Medicine 2.0 focuses
largely on lifespan, and is almost entirely geared toward staving off death,
Medicine 3.0 pays far more attention to maintaining healthspan, the quality of
life.
Healthspan was a concept that barely even existed when I went to medical
school. My professors said little to nothing about how to help our patients
maintain their physical and cognitive capacity as they aged. The word exercise
was almost never uttered. Sleep was totally ignored, both in class and in
residency, as we routinely worked twenty-four hours at a stretch. Our
instruction in nutrition was also minimal to nonexistent.
Today, Medicine 2.0 at least acknowledges the importance of healthspan,
but the standard definition—the period of life free of disease or disability—is
totally insufficient, in my view. We want more out of life than simply the
absence of sickness or disability. We want to be thriving, in every way,
throughout the latter half of our lives.
Another, related issue is that longevity itself, and healthspan in particular,
doesn’t really fit into the business model of our current healthcare system.
There are few insurance reimbursement codes for most of the largely
preventive interventions that I believe are necessary to extend lifespan and
healthspan. Health insurance companies won’t pay a doctor very much to tell
a patient to change the way he eats, or to monitor his blood glucose levels in
order to help prevent him from developing type 2 diabetes. Yet insurance will
pay for this same patient’s (very expensive) insulin after he has been
diagnosed. Similarly, there’s no billing code for putting a patient on a
comprehensive exercise program designed to maintain her muscle mass and
sense of balance while building her resistance to injury. But if she falls and
breaks her hip, then her surgery and physical therapy will be covered. Nearly
all the money flows to treatment rather than prevention—and when I say
“prevention,” I mean prevention of human suffering. Continuing to ignore
healthspan, as we’ve been doing, not only condemns people to a sick and
miserable older age but is guaranteed to bankrupt us eventually.
—
When I introduce my patients to this approach, I often talk about icebergs—
specifically, the ones that ended the first and final voyage of the Titanic. At
9:30 p.m. on the fatal night, the massive steamship received an urgent
message from another vessel that it was headed into an icefield. The message
was ignored. More than an hour later, another ship telegraphed a warning of
icebergs in the ship’s path. The Titanic’s wireless operator, busy trying to
communicate with Newfoundland over crowded airwaves, replied (via Morse
code): “Keep out; shut up.”
There were other problems. The ship was traveling at too fast a speed for
a foggy night with poor visibility. The water was unusually calm, giving the
crew a false sense of security. And although there was a set of binoculars on
board, they were locked away and no one had a key, meaning the ship’s
lookout was relying on his naked eyes alone. Forty-five minutes after that last
radio call, the lookout spotted the fatal iceberg just five hundred yards ahead.
Everyone knows how that ended.
But what if the Titanic had had radar and sonar (which were not
developed until World War II, more than fifteen years later)? Or better yet,
GPS and satellite imaging? Rather than trying to dodge through the maze of
deadly icebergs, hoping for the best, the captain could have made a slight
course correction a day or two before and steered clear of the entire mess.
This is exactly what ship captains do now, thanks to improved technology that
has made Titanic-style sinkings largely a thing of the past, relegated to sappy,
nostalgic movies with overwrought soundtracks.
The problem is that in medicine our tools do not allow us to see very far
over the horizon. Our “radar,” if you will, is not powerful enough. The longest
randomized clinical trials of statin drugs for primary prevention of heart
disease, for example, might last five to seven years. Our longest risk
prediction time frame is ten years. But cardiovascular disease can take
decades to develop.
Medicine 3.0 looks at the situation through a longer lens. A forty-year-old
should be concerned with her thirty- or forty-year cardiovascular risk profile,
not merely her ten-year risk. We therefore need tools with a much longer
reach than relatively brief clinical trials. We need long-range radar and GPS,
and satellite imaging, and all the rest. Not just a snapshot.
As I tell my patients, I’d like to be the navigator of your ship. My job, as I
see it, is to steer you through the icefield. I’m on iceberg duty, 24-7. How
many icebergs are out there? Which ones are closest? If we steer away from
those, will that bring us into the path of other hazards? Are there bigger,
more dangerous icebergs lurking over the horizon, out of sight?
Which brings us to perhaps the most important difference between
Medicine 2.0 and Medicine 3.0. In Medicine 2.0, you are a passenger on the
ship, being carried along somewhat passively. Medicine 3.0 demands much
more from you, the patient: You must be well informed, medically literate to
a reasonable degree, clear-eyed about your goals, and cognizant of the true
nature of risk. You must be willing to change ingrained habits, accept new
challenges, and venture outside of your comfort zone if necessary. You are
always participating, never passive. You confront problems, even
uncomfortable or scary ones, rather than ignoring them until it’s too late. You
have skin in the game, in a very literal sense. And you make important
decisions.
Because in this scenario, you are no longer a passenger on the ship; you
are its captain."