AMAKA ENEANYA: So a little
bit more of her background
as I looked in her
chart was that she
had been lost to follow up.
So she didn't have a
primary care clinician.
And she had a hematologist,
but she was bouncing around
between Philadelphia, Johnstown,
and Pittsburgh, Pennsylvania.
She essentially did not
have a place to live.
She was living with family
members, various family members
and friends, as well
as halfway homes.
And she was a single mother.
She had two young daughters.
Their father was
currently in prison,
and so she was very forthright
with how difficult it
was for her in this situation.
And again, since she did
not have a place to live,
it was hard for her to
obtain a regular dialysis
unit for treatments.
So I looked in the chart,
and over a two year period,
she had been admitted 18
times, all for sickle cell pain
crises.
And as I read the progress
notes, and admission notes,
and the discharge notes, I
saw words that kept coming up
in her medical
chart consistently,
and I'll share them with you:
"poor insight," "non-adherent,"
"unlikely to be sickle cell
pain," "missed dialysis,"
"poor compliance,"
"over-medicated with pain
meds."
And lastly, the discharge
disposition, "the patient
was discharged to home
in good condition," which
seemed to counter all of
the frequent admissions
that she had, and
clearly, why she
kept being admitted
for sickle cell pain.
So questions to
consider as I move on
for the goals of this talk
is, what is the best treatment
plan for this patient?
And most importantly,
does one already
know this patient by reading
about her previous admissions?
And what kind of
biases are you bringing
into the clinical
encounter by reading
all about the pejorative words
that you see consistently, time
and time again in her chart?
So let's define
structural racism.
Structural racism as defined
by Nancy Krieger at Harvard is,
"it refers to the totality of
ways in which societies foster
racial discrimination
via mutually-reinforcing
inequitable systems, such as
housing, education, employment,
et cetera, that
in turn reinforce
discriminatory beliefs, values,
and distribution of resources
that are reflected
in history, culture,
and interconnected
institutions."
So just a reminder that racism
is a hierarchical opportunity
system that unfairly
disadvantages and advantages
others based on
phenotypical appearances,
classically Blacks, Hispanics,
and Native Americans
in this country having
the disadvantage.
And so let's shift into
the economic disparities
that we see for, in
particular, Black individuals
in this country.
So this on the left is a graph
from the US Census Bureau
that looked at trends over
time in median household income
by race and Hispanic origin.
And you can see as of 2018,
that the median household
income for Asians was
87,000, for whites, 70,000,
and for Blacks, $41,000.
And similarly on the right, you
see racial and ethnic wealth
gaps.
And we define wealth
as the total market
value of intangible and
tangible assets minus debts.
And you can see as
of 2013, that whites
had a median net
wealth of 141,000
versus 11,004 for Blacks.
And you see a similar
pattern for median net wealth
for whites versus Hispanics.
And so clearly, we have huge
and parallel disparities
that have occurred over time.
And I'd like to point
out these horizontal bars
that you see in right here,
which represents recessions.
And you can see clearly
that after recessions,
that Hispanic and Black
individuals in the United
States don't rebound to
their either pre-recession
median household
income or wealth
compared to whites and
Asians in this country.
So very important to
note given the COVID-19
pandemic and the
recession that we're in.
So similarly, let's look
at education disparities.
This is from Pew
Research Center who
also produced the net wealth
graph that I showed before,
but this is looking at the
proportion of US adults
age 25 and older who have at
least a bachelor's degree.
And over time, you can again
see distinct and parallel trends
between the different racial and
ethnic groups in this country.
So Asians as of
2015, 53% of Asians
have attained a college
degree versus 36%
for white individuals, versus
23% for Blacks, and so forth.
So what I'm getting at here?
So essentially,
structural racism
has caused inequitable
distributions
of resources in this
country that map
along racial and ethnic lines.
And so these basically
result in social determinants
of health, which the World
Health Organization has defined
as "conditions in which people
are born, grow, live, work,
and age."
So looking at income, education,
food insecurity, crime rates,
et cetera, these are
the circumstances,
the social circumstances
that drive health inequities
among patients of different
race and ethnicity
in the United States.
So let's switch gears to
racial bias in clinical care.
I'd like to define
first implicit bias
and contrast that
with explicit bias.
So implicit bias refers to
the unconscious attitude
and stereotypes that
we carry with us
that impacts how we act, make
decisions, and view the world.
The literature has shown
that there is associations
with implicit bias
in clinical medicine
with physician-patient
communication,
adherence to recommendations,
and follow up care.
I'd like to contrast that
with explicit bias, which
is conscious and controlled acts
based on usually phenotypical
appearances and stereotypes.
And then on this graph
here on the right,
this is a graph that was
produced by the researchers who
came up with the Implicit
Association Test, which
seeks to identify implicit
biases against individuals
of different racial groups,
gender, and religion,
et cetera.
I'm going to keep going.
As you can see here,
they looked at 3 million
implicit association test
scores between 2002 and 2015.
And you can see
here that there's
a strong and moderate
automatic preference
for European
Americans as opposed
to a significantly lower
moderate and strong
automatic preference
for Black individuals.
So again, this is looking at
3 million implicit association
tests that were developed--
that were accumulated
from the researchers with
the implicit association test
group.
So I'll move on to describe how
bias can affect clinical care.
And I want to review this study
that was published in PNAS
in 2016, so not very long ago.
And it basically was conducted
at the University of Virginia
Medical School among all
of the medical students,
but they decided to
focus their analysis
on the white medical students.
So 200 or so white
medical students
were essentially polled
about biological differences
between Blacks and whites.
So they received surveys that
had 15 items, four of which
had true differences
between Blacks and whites,
mostly epidemiological outcomes.
So for instance, whites are
admitted with stroke less often
than Blacks.
But they also had items that
assess biological differences
that were false.
So for instance, Blacks had
less sensitive nerve endings
or thicker skin compared
to white patients.
And what they found was that
approximately 50% of students
held one false belief about
biological differences.
And they were asked to
then read two mock cases
about a Black and white
patient, and estimate
the pain of each patient,
and make a recommendation.
So you can see on these
graphs here on the right,
on the x-axis you have
beliefs, on the y-axis
you have average pain rating.
And for those who
held high beliefs
about biological differences
between Blacks and whites,
they were more likely
to rate a Black patient
as having less pain
than a white patient.
So you can imagine, again,
what bringing implicit bias
into the encounter does
for subsequent management
of clinical management
and decision making.
So what does this
mean for nephrology?
So the core of this panel is
to talk about race and EGFR
equations.
And you'll hear more
about these equations
from the experts on the panel,
but some studies in the United
States have shown that Black
individuals have on average
higher serum creatinine
levels compared
to non-Black individuals at the
same level of measured kidney
function.
And this has been historically
attributed to Black individuals
having more muscle mass
than white individuals.
But this is where the scientific
base is extremely poor.
And really as we think about
this more and more people are
writing about this
and studying it,
is are the differences that
we're seeing historically
with kidney function
and creatinine really
actually due to ancestry,
diet, or environmental factors?
These things have not been
assessed very robustly.
And so we're left with
clinicians judging a patient's
physical characteristics
to determine
which EGFR calculation
or number to use
in the clinical encounter.
Typically, you see
Black versus non-Black
in most health care systems.
And if you remember my
definition of explicit bias,
that would fall right
into that definition
because we are judging
phenotypical characteristics
that are then driving
our decisions.
And race correction in EGFR
equation, which puts Black
as having a higher
kidney function
can result in late referrals
to general nephrology
and transplant nephrology, which
only widens disparities that we
know exist in nephrology.
And so it's actually
really unclear
how false beliefs that--
so us being taught about
biological differences
that Blacks have more
muscle mass than whites,
it's really actually
unclear what else that
does in the encounter.
So we know what the
explicit bias does,
we have no idea what
this implicit bias is.
So let me end on eliminating
some structural racism
and bias in nephrology
and strategies for that.
So for eliminating
structural racism,
this is not an easy feat.
But people, very,
very brilliant people
wrote about this in the
Institute of Medicine's Unequal
Treatment Report
over 20 years ago.
And essentially,
they have strategies,
and I would encourage
everyone to look at this.
It is a free
publication about how
we can compensate or start
to break down the barriers
that structural
racism has caused.
So strengthening the stability
of the physician-patient
relationship, implementing
multidisciplinary treatment
and preventative care
teams, using strategies
to facilitate
patient empowerment,
and being intentional
about ethnic and racial
diversification
of clinical teams.
All of these things were very,
very helpful for that patient
that I presented in the
beginning of my talk,
and really helped her
to focus on taking
control of her health.
So introducing more
social services, housing,
having the psychological
service come in
to help with her coping.
Teaching her about
transplant actually made
a significant
difference in a patient
who had been classically
labeled as a difficult patient
and a frequent flyer.
And so what is the
approach to eliminating
racial bias in clinical care?
And so I published a perspective
about race and EGFR last year
with co-authors and faculty at
the University of Pennsylvania,
and we basically postulated
that race should only be used
to guide clinical care
if it's justified,
if it meets four criteria:
the use confers substantial
benefit, the benefit cannot be
achieved through other feasible
approaches, patients who
reject race categorization are
accommodated fairly, and the
use of race is transparent.
And so essentially, this
leaves us with two options.
We should use current EGFR
equations without race, namely,
we should be looking at
biomarkers like Cyctatin C that
unlike creatinine, do
not perform differently
across races.
But we can also
consider reflex testing
with the current equations
that we use without race.
And then for patients who are
around a clinically-relevant
decision, i.e.
Dosing of medications or
referral to specialty care,
we can then confirm what
their kidney function
is using other methods
such, as a Cyctatin
C or urinary
creatinine clearance.
And we should also be very
transparent with our patients,
which we have not been doing
in terms of how we're judging
their phenotype characteristics,
which is determining what type
of care they'll
get based on that.
So I'll end here with
one of my favorite quotes
from John Lewis, a US State
Representative, the late John
Lewis, I should say,
and a civil rights
icon: "if you see something
that is not right, not fair, not
just, you have a
moral obligation
to do something about it."
So I charge the
medical community
and scientific
community to start
to do something
about the injustices
that we've seen when
it comes to bias
in clinical care in nephrology.
Thank you.
MILDA SAUNDERS: Thank
you, Dr. Eneanya.
Next, Dr. Inker.
LESLEY INKER: Well
thank you very much.
It's really an honor to
be here with all of you.
I wish I could see you
all right in front of me,
but I'm glad that
we at least have
the videos by participants, so
I can see some of your faces.
And so my role in
this panel is to talk
about a brief history of
GFR estimate equations
and using the
coefficient for race,
and moving towards
race-free estimates.
So here is my disclosures,
although none are
relevant for this presentation.
And I'll be talking in this
talk about the importance of GFR
for care of patients
very briefly.
But the bulk of
the talk, we'll be
talking about the physiology
or the basis of GFR estimate
equations and the empirical
evidence surrounding
use of the race coefficient.
Sorry, I'm just going to try
and put my Zoom on properly.
And then, finally, a path
towards race-free GFR
estimates.
So why are we talking about GFR?
Well, GFR is the best
overall assessment
of the health of the kidney.
And for this reason,
the work group
that developed the National
Kidney Foundation's Kidney
Disease Outcome
Quality Initiative
Guideline for Chronic
Kidney Disease,
you'd use GFR to define
and stage the disease.
This guideline,
published in 2002,
really set the stage for the
study and care of patients
of who have kidney disease,
and transformed our ability
to understand the disease.
In addition to
defining and staging
the disease, the stage that's
associated with the management
plan, GFR is also important
for assessment, progression,
determination, and
prognosis, drug-dosing,
interpretation of signs,
symptoms, signs, and laboratory
abnormalities.
In other words, it's
really fundamental
for all patient care.
The work group use GFR as a
concept, not a specific way
to assess kidney function.
But as we all know, we mostly
used endogenous filtration
markers in the blood
to estimate the GFR,
and serum creatinine is
the most common method
to estimate GFR as
the first-line test.
It's measured more
than 80 million times
per year in the United States.
It's estimated, GFR
based in creatinine
is reported on more than 95%
of clinical laboratories,
and it has a substantial impact
in clinical practice, research,
and public health.
In other words to use Dr--
the title from Dr. Powe's
recent article in JAMA,
kidney function matters.
And it matters that we
get it actually right
so we make the right decision
for individual patients.
So first, a little physiology.
Here, we have in the
center our orange ellipsis,
is the serum level of
creatinine that's in the blood.
It comes with the blood
from muscle and from diet.
It's eliminated from
the blood to some extent
through extra-renal elimination.
So with creatinine, we're
really talking about the gut.
But of course, the
creatinine mostly
leaves their body
from the kidney,
represented here by
the urinary excretion,
the urinary concentration
times the volume.
It gets into the
urine, primarily
from filtration for GFR, and to
some extent from the secretion.
And we could represent
these, this physiological
relationships and these
mathematical equations
for the urinary excretion
is equal to the generation
minus any external
renal elimination
in the steady state.
And then, we can rearrange
and solve for GFR.
GFR is equal to the G minus
E minus any secretion divided
by the serum level.
And these three
parameters represent
the non-GFR determinants.
So estimate equations
relate measured GFR
to the serum level
using surrogates
for the unmeasured
physiological parameters.
And we're not actually
able to tease out
whether it's generation,
extra-renal elimination
or tubular secretion.
And so it could be
not just muscle,
but any abnormalities
in the way creatinine
is handled by the
kidney, or the way
their gut handles creatinine,
our gut handles creatinine.
And we think that's important
so that we separate out
some of the key issues that
we're talking about here.
These are the three most
commonly used estimating
equations for GFR.
We have the Cockcroft-Gault
formula, the MDRD study
equation, and the
CKD-EPI equation.
There's differences
amongst these equations
as you can see by some
of the more complex
of the mathematical formulas.
And we'll be talking on
the next slide about some
of these differences.
But I just want to
point out that they all
have the same fundamental
relationship with creatinine.
They all have an inverse
relationship with creatinine.
And so all of the
limitations of creatinine
are going to be in, really,
amongst all of these equations.
The Cockcroft-Gault formula
was developed in 249 white men.
And I have heard some say
that if we're going to--
we should potentially move to a
race-free way to estimate GFR,
but I think that
lack of inclusion
of a diverse
population, including
women in this equation
really limits its variation.
Even more importantly
in the current era
with the creatinine
assays, there's
large inaccuracies in
the Cockcroft-Gault,
especially in the elderly
and extremes of weight.
So I think the
two equations that
are there are more
reasonable to use
are the MDRD study equation
and the CKD-EPI equation.
The MDRD study equation
was developed in patients
with kidney disease.
And because of that, it
has a reasonable accuracy
in kidney disease
populations, but
a systematic underestimation of
measured GFR at higher levels.
And its surrogates for
the non-GFR determinants
of creatinine are
age, sex, and race.
The CKD-EPI equation,
we developed
and try to address some
of the major limitations
to the MDRD study equation.
And that is only accurate
people with kidney disease.
And when the
guidelines came out,
the goal was to identify
who had kidney disease
and who didn't have
kidney disease.
So we need an
equation that really
could expand that spectrum.
And we were able to do that so
it is unbiased across the GFR
range, however, it has the same
three surrogates of age, sex,
and race.
And they will say, we tried hard
to replace these demographics.
So if you're understanding
some of their limitations
with variables such
as height of weight,
and we were able
to come to nearly
the same amount of accuracy.
Just what is the
empirical evidence
for this race coefficient?
Well, I think the first evidence
and the first observation
came from the development
of the MDRD study equation
which that in both men and
women, Black participants
in the MDRD study had
higher levels of creatinine
compared to white participants
for the same level of GFR.
And for this reason,
they included it
in the MDRD study equation.
This was probably, in fact,
the first time that Black
participants had measured GFR.
This was done in
the late 80s, and I
think including them in the
trial of chronic kidney disease
was extremely important.
However, this was
the first instance.
And so shortly after the
publication of the MDRD study
equation, there was
a validation of it,
and in particular, the way
that the coefficient for Black.
And in the African-Americans
study for kidney disease,
or AASK, which is a trial
to look at hypertension,
hypertensive kidney disease but
have really excellent measures
of GFR, they were
able to confirm
that the results in AASK
were consistent with the MDRD
despite differences
in characteristics
such as mean level GFR,
BMI, albumin, and urea.
And importantly, the
recruitment for AASK
was across the
entire range of GFR
of people with kidney disease.
And these results were
from the screening cohort
which had a very large range
of GFR, not necessarily people
with kidney disease.
So the third piece
of evidence comes
from a slightly
different population,
which is the observation that
in prevalent dialysis patients,
higher creatinine
were associated
with increased survival.
And so these
investigators say, well,
why is it that our Black
patients tend to have higher
creatinine and do better?
Is this related to muscle?
And what they observed is that
creatinine was significantly
higher in Black versus
non-black patients,
even after adjustment for
nutrition and body composition,
suggesting that it's not
diet and muscle, as I think
what many people had assumed.
And the final piece of data
is from a more recent study
looking at genetic ancestry,
and that African ancestry
was positively associated
with serum creatinine,
and the authors concluded
that this supports
the physiological association
of creatinine when
it comes to race.
So you know I think
there are some data
to support that it's a
consistent finding, not
just in particular populations,
and not just related
to muscle mass or
diet, but seems
to be across these populations.
But there are
clearly limitations.
First of all, the cause of
the empirical observation
is not well understood.
And I think that is
important to understand
what we're talking about.
Secondly, there is
extreme practical problems
in implication, and that's
increasingly so in our society.
And finally, and this is
what was raised more recently
in the past year or so is
the concern that it uses,
propagates, race-based
medicine and implicit bias.
And of course, that is
not anybody's goal here.
So what do we do?
So in response to the
JAMA article, we actually,
as the CKD-EPI investigator
said, OK, let's look at it.
Can we actually take
away race and replace it
for height and weight,
or take away race
and have a bias
that's appropriate,
that would be reasonable
to still provide
highly-accurate estimates
to all of the patients.
And so this, we published this
in JAMA Internal Medicine.
And here, we have the original
CKD-EPI equation which includes
age, sex, and race--
creatinine, age, sex,
and race, then we
have a revised version with
creatinine, age, and sex.
And then we have an alternative
version of creatinine,
age, sex, height, and weight.
And in orange is the
Black participants,
and the gray was the
other participants.
Now I'm not showing
you an orange line
here because the CKD-EPI
equation is completely
unbiased in Black participants.
When we take away race, we
get a large underestimate
of the measure of GFR
in Black participants,
and a smaller overestimate
of measured GFR
in the other participants.
And if we add height and weight,
we don't get any benefit.
And so our concern
and the conclusion
here is that although
we have an advance,
it's that if we remove
the race coefficient,
we really sacrifice for
the sake of the large bias.
So how do we move forward?
And I think the issue
of race-free estimates,
and actually I would
say more generally,
demographic-free estimates
is actually our goal.
And this has been our
goal since we actually
started the development of
the CKD-EPI equation way
back in 2003.
And we were barely hopeful then
that alternative filtration
markers could replace
creatinine and replace
the need for any
demographics, and so we
started studying Cyctatin.
Here you have the same
figure that I showed you
earlier with creatinine.
And like I said, we
were really hopeful
that Cyctatin would have a much
simpler physiological profile.
It wouldn't have any
non-GFR determinants.
And in fact, they are lower.
There coefficients for
age and sex are lower,
and there's no
association with race.
But the problem is
that there is variation
amongst people and within a
person over time, particularly
related, we think, to
inflammation and obesity,
but it's actually really
hard to understand
the non-GFR determinants
of Cyctatin.
And so because of that,
when we develop equations
using creatinine
or Cyctatin alone
along with these other
variables, their performance
or the comparative measured
GFR are about the same.
We don't really get any
benefit from Cyctatin.
It was only when we
combined the two together
that we have improved precision
and improved accuracy.
But in order to do
so, we needed race.
So in here what I have in
this portion of the slide
is the coefficients for
all of the variables.
And in particular, I
wanted to highlight
the coefficient for race
in each of the equations.
This is in the creatinine
alone equation,
and this is in the
combined equation.
And the coefficient for
race was 8%, half of what
it was in the
creatinine-only equation.
And so actually at
the time we said,
wouldn't it have been
great if we didn't
need this race coefficient?
Any simplification related
to any demographics
allows us to have
less assumptions,
less across individuals.
And unfortunately at the
time in our validation data
set, which is the different
data sets from which we
develop the equation which is
a true test of the performance.
We only had 30 black people.
And so at the time,
we rote in the paper,
we think this is
for future studies
to evaluate and determine the
importance of this coefficient.
And so what we've done
actually over the past decade
is try and get our
own funding to measure
GFR in a more multi-ethnic
multi-race cohorts
and develop partnerships with
other investigators who have
access to data and samples.
And actually, we are
now about to embark
on evaluating what is the
impact of removing the race
coefficient in the combined
creatinine-Cyctatin equation.
So finally, ultimately,
we're really
hoping for a demographic-free
GFR estimate.
And the way we think
we possibly can do this
is to have a panel
of panel EGFR that
has multiple different
endogenous filtration markers,
our thought is we probably
need about six to eight.
And that will minimize
the impact of all
of these non-GFR determinants.
And this will allow us to have
accuracy and precision that
approaches that of measured GFR.
So where are we along this path?
Well, we have two evidence
of proof of this concept,
not ready for prime time.
The first is using low
molecular-weight proteins,
and particularly, beta
trace protein and beta 2
micro globulin.
And then those two combined
with creatinine and Cyctatin
is as accurate as a
creatinine-Cyctatin
without the use of race.
And then we have another
panel of metabolites
we're identifying using
discovery methods.
And this four-marker
panel was as
accurate as EGFR,
creatinine, Cyctatin,
but without these creatinine,
age, sex, and race.
So I think we're on our path.
We're not there
yet, but I really
hope that we are able to
provide GFR estimates that
don't have any of the
assumptions that are required
with any of the surrogates for
these non-GFR determinants.
So in conclusion, the
estimating equations
are based on physiological
principles, empirical evidence.
The creatinine-based
estimates include the race
to provide the most precise
and accurate estimates
for all people.
Race-free methods to estimate
GFR, such as Cyctatin--
and I didn't actually
measure this,
but I needed to add it in,
that it is appropriate to ask
for measured GFR urinary
clearances or endogenous
filtration markers
are available,
and can be used
routinely, especially
for clinical decisions
impacted by the level of GFR.
And future panels of GFR will
provide improved precision
with age, sex, and
race-free estimates.
Thank you.
MILDA SAUNDERS:
Thank you, Dr. Inker.
I think that's Dr. Powe.
NEIL POWE: It's a pleasure
to be back with colleagues
at the University of Chicago
talking about race and kidney
disease again.
I actually came as a
Bowman lecturer in 2008,
and I have tremendous
respect for James Bowman.
In fact, I have
this effigy of him
in my office that's a keepsake.
So he made important
contributions
to science and to medicine.
I'm going to share my screen,
and then we will have the--
more.
And we're going to disable
the attendee annotation.
And then, I will put
this on my screen share.
OK, are we good?
OK, so I'm going to talk about
the consequences and approaches
to use of race in
estimating EGFR.
These are my disclosures.
I have a lot of associations
and professional associations,
but no corporate or for
profit associations.
So what I'm going
to do is describe
the potential clinical
consequences of removing race
from EGFR equations, I'm
going to examine with you
some data on whether
incorporation
of race into equations
generates disparities,
and I'm going to describe
approaches mostly,
and challenges to
mitigate the use of race
in estimating or reporting.
Much of what I'm going
to say is in this article
that was published last week.
So as Dr. Inker said, there are
about 280 million creatinine
are performed each
year in the US.
And one of the crowning
achievements I think,
in nephrology, has been the
standardized measurement
of kidney function.
And as Dr. Inker said,
over GFR of laboratories
in the United States
are now reporting EGFR.
And over 90% report with
either the MDRD equation
or the CKD-EPI equation that
contains race estimates.
So black kidney
function matters.
Why does it matter?
Because kidney failure
is up to 3 times greater
in racial and ethnic minorities.
You can see here, three times
greater in African-Americans,
and also greater in
other ethnic minorities,
and it occurs up to five
years earlier in in game.
So we've heard about
what the differences
between African-Americans
and whites
and in other groups
in creatinine levels.
So what does removing race
do from these Equations
It increases the persons with
CKD or with more severe stages.
But what that implies
when we remove it,
either the past was
under-diagnosis,
or with change, we might
have over-diagnosis.
So what you really want to do
is look at the balance sheet.
So here's the balance sheet.
The benefits might be increased
referrals to specialists,
increased access to the
transplant waitlist,
access to
Medicare-funded services,
and more aggressive
CKD management.
But the harms might be
that African-Americans
would be less able
to donate kidneys
to their loved ones, that
actually drug use or dosing
might be diminished,
things like metformin,
or even pain medicines
that Dr. Eneanya talked
about, under treatment,
possible under-treatment of pain
in African-Americans,
which has already
been described as a disparity.
And the use of
chemotherapy, for example,
carboplatin therapy
in ovarian cancer.
It could also lead to
decreased imaging procedures,
decrease access for
African-Americans
to clinical trials,
and actually to anxiety
or labeling if it
was over-diagnosis.
So I want to raise the
question, did disparities
for Blacks in the waiting
list in nephrology referral,
where they present before
the use of these equations?
The MDRD results were
published in 1999,
and the CKD-EPI in 2009.
This panel shows
weight-listing a study done
by Paul Eggers looking at
different ethnic groups
waitlisting, And you can
see that African-Americans
where the lowest
over several years
in being listed on the waitlist.
This is a study that Dr.
Saunders talked about,
My Choice study, which
in 1995 and 1996,
we demonstrated that Black
females and Black males
were more likely to have a late
evaluation to a nephrologist.
But these equations could
not have affected these,
because the equations with race
we're not actually in place.
So you might say, well,
what's happened since then?
So here is actually
waitlisting or a receipt
of a deceased donor since
the introduction of the MDRD
equation.
And if anything, it hasn't.
It certainly hasn't gone down.
In fact, probably
has gone up a little.
And then what about
the CKD-EPI equation?
This is some other
data on waitlisting,
and you can see that when the
CKD-EPI equation was introduced
in 2009, the rate of
waitlisting has not
changed for African-Americans,
and for a number
of the other ethnic groups.
Could it be keeping it there?
Yeah, that's a possibility.
So what about trends
in nephrology care,
pre-dialysis nephrology care?
This is some recent data
done by Tanjala Purnell
at Hopkins, which looked
over time at the odds
ratio of early referral of
Blacks compared to whites.
And you can see it's reduced.
And what's distressing
is that actually, it's
been that way over time.
But here's where the
CKD-EPI equation came in.
So it was already reduced, and
what's interesting about this
if you look at Hispanics,
it also was reduced
and the pattern looks the same.
So I would say that the
similar trend in race
and the non-race
coefficient minorities
suggests that disparities are
driven mostly by other factors.
And I am concerned
that we're not
concentrating on those
other factors, which
may be institutionalized
racism or biased.
It could certainly
be that, and we
need to find out what
these factors are.
Now on the other
side, a recent study
looked at metformin prescribing
before an FDA label change.
And what it showed when
the use of serum creatinine
dictated use of metformin,
that in individuals whose EGFR
was less than 45, Blacks were
less likely to use metformin.
But then after the label change
was changed to EGFR with race
because that was
the equations that I
showed you were used
in the US, in fact
that disparity diminished.
In fact among persons
who are EGFR 30 to 40,
it actually was eliminated.
Interesting.
So there are other
consequences of race removal.
Regulatory approval
drugs by the FDA,
tracking of kidney
disease in the population.
What about life
insurance or disability
access if in fact, individuals
are overdiagnosed and labeled?
And then exclusion from
research study participation
by African-Americans
could be a problem.
So what I mostly want
to concentrate on
is the approaches to
mitigate use of race that
are being used or proposed to
be used in clinical practice
and pointing out some
of the challenges.
I'm sure as Dr.
Inker showed you,
we don't want to
return to the past
and use just serum creatinine
or the Cockcroft-Gault
because that is
highly inaccurate.
And measuring GFR takes a lot
of time, effort, and cost.
So what we really--
here are a list of
options that I think--
and some that are being used.
So I'm going to take
you through them,
and it might be interesting
in our discussion session
to learn about what
your approach might be.
So this is what I call the
dominant race scrap standard,
and this is probably
what's being used most
throughout the country today.
They did discard the race
coefficient from the equation
and report only the
non-Black estimate.
Well, this removes
the race in reporting,
and I believe it's
discriminatory
because it ignores the data on
Blacks from studies included
in equation derivation.
So it institutionalizes
exclusions of Blacks
from research for
clinical decision making.
Let me show you what I mean.
Here's the equation, the math
that Dr. Inker showed you.
Essentially what's
happening, we're
throwing a coefficient
in the trashcan.
But along that, we're
removing the data
on 31% of Blacks in
the pooled study that
included a gold standard
of measured GFR,
and the large number of them
were from the African-American
studying kidney disease.
I can bring home
that point by this;
if you looked at
over five decades
in the Framingham
Study, we criticized
that that study was
developing risk equations
and are being applied
to African-Americans off
of just European Americans.
And so the NHLVI started
the Jackson Heart Study
in Jackson, Tennessee
to look at heart
disease in African-Americans.
So essentially when you remove
the race coefficient, what
you're doing is saying, I
don't care about the data
on African-Americans.
Now this is a
problem, because we
have fought to have
diversity in our research
and our clinical trials in
order to drive clinical decision
making for diverse populations.
So the second thing that people
have used, and I have to say,
some petitioners
at my institution
suggested substituting low
muscle mass and high muscle
mass for non-Black and Black.
And as Dr. Inker showed
you, while this recognizes
participation of
Blacks, it assumes
race is a proxy for
muscle mass, and I
believe this
stereotypes all Blacks
as having high muscle mass.
So in fact, it
institutionalizes stereotyping.
And I can drive this
home by saying this;
these are the stereotypes that
I think are in people's brains.
But we know that there
are all possibilities, OK?
So this is really problematic.
Now another approach that
people have said, well,
could we develop an equation--
and I believe actually Dr.
Inker could do this--
she could develop a new equation
from the CKD-EPI data that's
a weighted average of the
ethnicity coefficients.
But the issue is would you
use 30% of the Black CKD-EPI
participants, or would you use
13% of the Blacks in the US?
Or you might care, well,
I have this many Blacks
at my institution, so I
want to see it for that.
So it requires agreement
on the appropriate weight.
And then, it raises questions
whether it should be done
for all race and ethnic groups.
And I just show
you the math here
to illustrate how it's
done with the weights
with the African-American
coefficient and not.
And it's important to note that
these blended equations would
need testing as well.
So a fourth way is to report
two values currently generated
by the equation, but not openly
tag them with race descriptors.
So that would remove
race in reporting,
but the underlying
race distinction
remains below the surface.
Now that's not unlike many
tests we have in medicine,
because it leaves
clinical correlation,
nephrology consultation,
and shared decision making
to the ordering
physicians, who also could
get nephrology consultation and
have greater input about what
a person's true GFR might be.
And finally Dr. Inker
said, this is really
where we want to be, is
to have race-less markers.
So using non-creatinine
filtration markers
for which race does not
add greater precision.
The problem, as Dr. Inker
says, that the higher
cost of Cyctatin C, which
is up to 10 times higher,
and in many institutions,
it's a send-out test that
may require waiting a little.
And standardization
is improving.
And as Dr. Inker said, because
it's an acute-phase reactant,
it's uncertain how it will
perform in very ill patients.
But we might use this
when decision making could
affect patient health, and those
decisions are really critical.
So in summary, I'd like to
say that elimination of race
is a worthy aspiration, but the
consequences are far reaching.
And making changes is
not a trivial task.
What we're trying to seek
is the correct diagnosis,
not under or over-diagnosis.
But we want to avoid
doing more harm than good
as we go on this
journey together.
So EGFR equations are unlikely
as a major cause of disparities
in waitlists and
specialists referral,
as the data I showed you.
And there's indirect
evidence that they
helped eliminate metformin
prescribing disparity.
So some approaches
promulgated to remove
race institutionalized
discrimination
or may be racist,
in the new race-less
markers may offer
a path forward,
but they need to be scaled,
widely adopted, and monitored.
So our solutions to this should
be consistent, not different
across separate institutions.
We spent decades trying to
standardize EGFR measurement,
because patients go
across institutions,
and our trainees go
across institutions,
and doctors sometimes
go across institutions.
We need something
that's durable.
It needs to be evidence-based,
not just plucked out
of the sky.
And it's devised with input
from a variety of stakeholders.
And what I believe
is, the patient
has been left out of a
lot of the decisions that
are happening now, and we
need to bring the patient
into those.
So thank you very
much for listening,
and I look forward
to the questions.
MILDA SAUNDERS: Great.
Thank you, Dr. Powe.
So now, I'm going to
open for questions.
I think that if you
have a question,
you can put it in the Comments.
But I think people are
also texting back and forth
because comments had
been blocked out.
So I will be looking
at all sources.
And then, I will read
questions from the Chat.
If I call on you, if you
want to unmute and read
your question out loud,
if you are currently
unable to do that, then
I'll read it out loud.
But in the meantime, I'm
going to open with a question
an introduction from
Professor Dorothy Roberts.
Professor Roberts is
an acclaimed scholar
of race and gender and law,
and joined the University
of Pennsylvania as the 14th Penn
Integrated Knowledge Professor
with joint appointments in the
departments of africana studies
and sociology in the
law school, where
she holds the inaugural Raymond
Pace and Sadie Tanner Moselle
Alexander chair.
She is also the
founding director
of the Penn Program on
Race, Science, and Society
in the Center for
Africana Studies,
and her path-breaking work
in law and public policy
focuses on urgent
contemporary issues
in health, social
justice, and bioethics,
especially as they impact
the lives of women, children,
and African-Americans.
One of her major
books, Fatal Invention:
How Science, Politics, and
Big Business Recreate Race
In the 21st Century
examines how the myth
of the biological
concept of race
continues to undermine
a just society
and promote inequality in the
supposedly post-racial era.
And some of the
Pritzker students
are actually reading
this text now.
And so Dr. Roberts, if you want
to unmute and ask a question
or make a comment,
we'd appreciate it.
DOROTHY ROBERTS: OK, great.
Thanks so much for
inviting me to have
a little participation in this
really interesting discussion.
Let me give a little bit
of commentary to preface
my question, and it's
commentary coming from someone
who isn't a physician.
I am a sociologist
and a legal scholar,
but I've spent my entire career,
which is over 30 years now,
studying race.
And I have to say,
I first became
familiar with race
correction in the EGFR
when my daughter sent
me her lab test results
and pointed out this remarkable
thing that there were
two different numbers for EGFR:
one for African-Americans,
and one for
non-African-Americans.
She was astounded.
I was astounded, I really
couldn't believe my eyes
because I couldn't see
how it could possibly
be that doctors could assume
that just because a patient was
African-American, the patient
should be treated differently
from any other human being.
How could it be that
African-Americans
are so different from other
human beings as a group
that you could make an
automatic conclusion to adjust
the amount of creatinine
in their blood for whatever
reason, whether it's muscle
mass or whatever it is.
It seems like doctors
don't even know
what it is that's the
reason you would do this.
But it was just
astounding to me,
and it remains astounding to me.
So I guess my question
is, how can there
be this disconnect between
what my astonishment, my--
even though-- and
my astonishment
doesn't come from my lack
of medical knowledge,
that comes from my
understanding of race.
I know that race is
a human invention.
It's not a natural creation.
The definition of it differs.
So when we talk
about standardizing,
you can't standardize using race
because race means something
different in different
societies and even
at different points of time.
So to me, the worst thing to
use as a standardized measure,
that would be race because
if you took my blood
test in England or
in Brazil, it might
want to use a completely
different category.
And just saying I'm
black or African-American
wouldn't necessarily tell you.
You're not even sure where
that category comes from.
Who determines
what your race is?
And if it's
self-identified, it could
be lots of different
things, and it
could be different from how
the doctor identifies you.
I'm not even getting
to the question of,
what if you identify
as mixed race
or you don't identify
racially at all,
what do you do in those cases?
So it just seems like
such a crude and amorphous
and variable category to base
such an automatic adjustment on
seems so strange.
And then also, the
harms that we know
can occur, just the basic
harm that if you were white,
you might be waitlisted in cases
where you wouldn't if you're
identified as Black.
So I understand
Dr. Powe's research
looking at whether there
really was an impact or not.
Of course, we would have to look
at all the other factors that
happened around the
same time to determine
whether the change in
adding race to the GFR
was the cause of
any of those things.
We don't know for
sure, but we do
know that that number makes a
difference for some decisions,
and race makes a
difference to that number.
And I just wonder if
the harms of taking
it out-- and I understand those
harms couldn't be addressed
in better ways than keeping
race in the EGFR, including
addressed in consultation
with a nephrologist.
Or, other ways of making
sure that Black patients are
treated accurately for
other kinds of medication.
Why should it depend
on race and the EGFR
to make sure they're
getting accurate diagnoses
and prescriptions
for other things?
So I guess overall, my
other concern about it
is that the biological
concept of race
has caused so much
damage historically.
We know it comes out
of slavery, the idea
that Black people's bodies
function differently,
that black people have
different diseases, experience
common diseases differently
than other human beings.
We can trace that
directly to what
doctors said during slavery to
support slavery as beneficial
to Black people's health.
And it supports his general
view that races are biological,
which we know produces
and reinforces biases
and stereotypes, like the ones
that Dr. Eneanya described,
like the mistreatment of
Black patients for pain.
All of that stems
from stereotypes
about the biological
differences between races
that are reinforced in medical
school when students are taught
things like correcting,
automatically
correcting for race.
And it also seems
as if there are
ways that we could have a more
accurate measure of kidney
function.
The kinds of things that
Dr. Inker was talking about.
But relying on race
has been a barrier,
why is it that just now a Dr.
Inker is doing this research,
right?
Why hasn't it been done sooner?
I think it's because we've
been relying on race,
so we don't have to look
for something more accurate.
So I guess my
challenge to all of you
is, again, I do not profess
to be an expert in kidney
function, at all.
I do profess to be an expert on
racism and the meaning of race.
And I guess my overall
question, how do you
reconcile the fact that race
is not a biological category,
and that that idea has been
so harmful to Black people
globally for centuries with
the continued use of race
correction in the EGFR?
So that's my question.
I know that's a big question.
But it's just an honest
question coming from someone
where in my field, it seems
totally absurd to do it.
And how can we reconcile
these difference those
between a sociological approach
and an historical approach,
and the medical
approach of continuing
to adjust categorically
and automatically because
of a patient's race, especially
the idea of Black race
or African-American race?
AMAKA ENEANYA: Can I comment
first, and then maybe we can--
do you mind?
So I echo clearly
everything that you said.
Thank you so much, Dr.
Roberts, for attending.
I truly and wholeheartedly
agree that we do not practice
medicine based on one number.
And so, holding on tightly
to an equation or a number
to dictate dosing,
we don't do that now.
We don't do that now
for our patients.
If a patient has side effects
and their GFR is a number,
we don't give them that
medication based on their GFR
because that's what
they're GFR says.
And so I think the way
around this in addition
to thinking about Cyctatin
C and better biomarkers,
is to basically change,
a systemic change
in which nephrology leads the
way because we do that anyway.
When patients come in that are
very muscular or very frail
and the creatinine is not
reliable in those patients,
or if they're
amputees, what we do
are other things to confirm
their kidney function.
And we can confirm
their diagnosis,
we can refute their diagnosis.
And so I think really
the way around this
is better communication
and collaboration
with nephrologists.
I think that we
created this, and it's
our job to take care of this.
And not only is it something
that I think is going to be,
over time, is we're going
to have better studies
and actually realize
these differences that
have been shown, but it causes
moral distress among students
and trainees who I speak
to who are now receiving
this education to do this.
We don't really understand
why, as you said,
and we're perpetuating
these racist notions.
So I do think that
there's ways around having
less accurate kidney
function measures than we're
seeing in the chart, we
do that all the time.
creatinine is not a
perfect biomarker,
it's very problematic.
And so just to follow
up on what you said,
I'd love to hear comments
from Dr. Powe and Dr. Inker.
LESLEY INKER: So I can
take the next stab.
And first of all
in a personal way,
I've been trying to
do this work for--
I think we got our first
grant to try and get more GFR
measurements and to
study this issue in 2008,
and science is slow.
And I apologize for maybe
not writing more grants,
but this is not new.
We have been trying really hard.
And I have to just say,
I take that really--
tales of woe in
grant applications.
First, let's say that.
And where I think I--
DOROTHY ROBERTS: If I just--
that was not a criticism
of you, whatsoever.
It was praise for you doing
these research projects,
so I just want to
make that clear.
LESLEY INKER: Yeah, but I
think that where I do regret
is that we've been
hearing rumors about--
not rumors, but
hints of discussions
of creatinine concerns
for a few years now.
And where I think we
didn't listen well enough
is that we said, listen, we're
writing all these grants,
and we're going
to have this work,
we have this new
biomarker, Cyctatin C.
And we didn't say,
you know what?
We need an answer here and now.
So I actually really take
that on, that responsibility.
And I apologize.
I think this came through
almost a crisis moment.
And I don't think it should
not come to a crisis,
we should always
anticipate them.
But one of the
first things I did
was reach out to the National
Kidney Foundation and say,
we need a national
conversation about this.
And I did make a statement.
I do like the creatinine
equation as it is,
but I'm not going to
defend it for all of those.
I'm going to have a conversation
with the National Cancer
foundation and the
American Society
of Nephrology, which is
actually wonderful in itself,
that our two big organizations
in the United States
say, this is a really
serious problem, how
do we deal with this so we
can have the consistency Dr.
Powe talked about, which I
think is really important
to decrease confusion.
So I think-- so I'm--
sorry, I just made some notes
and I just had to reach down.
So I think that that is--
they have said they're going to
have a recommendation by 2020,
the end of 2020.
So I'm just saying that I know
the community is listening.
I do think there was a comment
about Zoom for nephrologists
and non-nephrologists, and I
don't think we can assume that
everybody in practice
can easily have a--
I'm on the consult service now.
Our medical students, are
fellows will come, and I we
have multiple, deep
conversations about GFR.
I do not think that this
happens in most nephrology
consult services or
in most primary care.
And so I think like in all
medicine, we have a first line
and we have a
second line, and how
do we better relationship that.
But there's some
advantage of that.
And finally, I just want to
comment on the sociology.
So this has been--
since these conversations
have come on,
I've actually taken on to
talk to my patients about it
and be transparent about it.
And I have had the most
wonderful conversations
with my patients.
They open up areas that I
would never have gone to.
And what I'm a little worried
about is that if we take--
I mean, I really hope that we
do better with these equations.
But in general, we
say, we just can't
talk about ancestry or race,
and how we call ourselves,
then we're going
to make people not
comfortable with talking
about people's history
and who they are.
And I think that they're-- and
I try to be thoughtful on both
sides, and the balance
of Dr. Powe's side,
and I just wanted
to acknowledge that.
Because it's just been one of
the most wonderful experience
is in actually being
transparent about it,
and having deep conversations
with my patients.
NEIL POWE: Well, I'll take my--
Dr. Roberts, I'm glad
you're able to join us
from the great city
of Philadelphia,
where I was born and raised, but
also terrorized on the streets
by Frank Rizzo's police.
And I'm so glad that his
statue was taken down
a couple of months ago.
And also from one
of my alma maters,
the University of Pennsylvania.
And I really appreciate the
scholarship and the attention
you have brought to racism.
And that it has no
part in our society.
Whether it's institutionalized
or personalized.
It has no part in our society.
And I do believe that
the concept of race
is a fuzzy concept, but
it is not unimportant.
I believe that
some patients, it's
a big part of their identity.
In fact, one of the studies
that I referenced in my piece
in JAMA is a study of
100,000 people in Kaiser.
And they asked people, what
their self-identified ancestry
was, and then they went and
did their genetic ancestry.
And there is a strong,
strong correlation
between their self-identified
race and the race
as determined by
genetic ancestry.
I'm not saying that the e.g.
that actually the
creatinine observations
are necessarily
biological, but that
is in fact, evidence,
very strong evidence
from the literature, in the
area of the country where
we probably have more mixed-race
individuals than anywhere else
in the country, in California.
So my colleagues here, I
can't say we're all unified,
I have colleagues
who are looking--
who have published on the
genetics of creatinine
and ancestry, those are
African-American and Latinx
faculty.
We published some of that data
Dr. Inker didn't show you,
but it was another
study that actually
showed the relationship between
the percent of African ancestry
and serum creatinine levels.
And those are people
who are trying
to understand the
interrelationships
between social factors
and biologic factors
for the purpose of
improving human health.
And what I don't like
about these discussions
is we have one group
of people lined up:
race has no biologic
signal; and then we
have another group,
my geneticists,
who are doing work
on ancestry, not
only African-American ancestry
but other types of ancestry
and showing and studying
how actually people respond
to drugs in different ways.
Now it's very crude research,
just like the crude research
that started out on
this journey way back.
And I think anyone
doing it today
would have done it
differently, OK?
Because we didn't even
have the human genome
sequence 'till 2003.
And even though we
still have it sequenced,
we're still understanding
how that is expressed
and what it means.
What does it mean?
Are there ancestral
genes that travel
with important biological
functions for which
clinical decisions are made?
We do not know that.
But to trash the
whole thing, I think
it's wrong rather than to
listen, learn, and understand
it.
And I have to say
that I beg to differ
that the terms that the
use of race is misused.
Some people prefer the term
race-conscious medicine
versus racially-biased
medicine, OK?
I'll say it again,
race-conscious medicine
as opposed to
race-biased medicine.
It's not simply that using
race may be bad medicine.
And you have to ask,
if not race then what?
If individuals want as
a planet, if not race,
what do you have that
will be equally accurate
and that is evidence-based,
and that will not do any harm?
And my big concern is people
are moving in a direction,
as I've showed you, that could
lead to more harm than good.
The patient is being left
out of this conversation.
Not only their opinions
about this, but also
not looking at what the
impact is, not considering
all the consequences,
not measuring
all those consequences
before movement is made.
And I think, physicians
we want to practice
evidence-based
medicine, we also don't
want to practice
race-biased medicine.
I don't think any of
us want to do that.
So that's what I would say.
MILDA SAUNDERS: Thank you.
So I want to bring some--
we have a bunch of questions
on the side.
And so one question is, what
are the current recommendations
for GFR reporting for health
systems at the present time?
Are there national
recommendations?
LESLEY INKER: Yes.
So the national
recommendation comes
from the KDIGO, which is the
International [AUDIO OUT]
regarded as the
CKD-EPI equation,
as they are where
they were developed.
The National Kidney Foundation
has a laboratory engagement
group, which is a way in
which they communicate
with clinical
chemists recognizing
all of these questions and
really appreciating it,
and suggested that no changes
are made right now, pending
this task force.
AMAKA ENEANYA: So
I'll jump in there
and say I think all
three of us on the panel
are on the task force, and that
will be announced publicly,
soon.
I think it will be really
important for everyone
to align, as Dr.
Powe said, there
are opinions that are
not aligned right now
and that's causing
a lot of confusion.
More importantly for
practitioners in the community
who are not so proximal to
all of the academic research
that we are.
And so those changes
are forthcoming,
but I also know that
a lot of institutions
are moving forward with
making their changes.
And I don't think that anyone
can actually stop them.
I feel like there's
people who feel very, very
wrong about this,
and there's not much
that we can do in the
meantime, especially
for medical students,
who again, have really
put the fuel to the fire
for these discussions, who
are learning how to be doctors.
This is the next
generation of doctors,
and they don't feel right.
And we don't have--
I totally agree that there
are differences that are there
that we do not
understand, but we
don't have a good way to teach
them about those differences.
And then, we're asking them to
do something that is literally
causing moral distress.
And so this is a
critical time in history,
I think, to really
be able to change
the narrative on how we train
the next generation of doctors.
I think somebody
commented in the--
and I didn't mean
to, Dr. Saunders,
to take this question
now, but a lot of people
have asked me about the patient
selection of Black participants
in CKD-EPI trials.
So 70% of those participants
came from the AASK trial.
And they AASK trial again
was a longitudinal cohort
study looking at
African-Americans
and their disease for CKD
or chronic kidney disease
progression when on
certain medications,
ACEs and ARBs were introduced.
And amongst that cohort,
the AASK cohort, almost half
of those participants had
an income less than $15,000,
and of upwards of 62% did not
have a high school education.
And so if 70% of
those participants who
were in the CKD
formulated or comprised
the Black participants
in CKD-EPI,
we're using a group of
individuals you may say
is representative United States.
But if we're thinking about diet
and environmental effects that
could affect creatinine
generation or secretion,
we have to be really, really
critical about the participants
that have generated
this data, especially
in the CKD-EPI equation that
we've been using so widely.
And so the question
I pose is, what do we
tell the medical students?
What do we tell the trainees
when we're talking about this?
And I think we've
all raised this,
but what do we
tell our patients?
Somebody rejects
the use of race,
and they want to move forward--
I have personal
family members that
have lost years,
years on the waitlist
because their
nephrologist did not
allow them to accumulate
waitlisting time because they
sat on that border.
So what do we tell patients that
say, I don't want to use this.
This is hurting me.
And so, what do I tell my--
I stepped in.
Thankfully, I'm an advocate
for my family member
and was able to get
that person listed.
But there's countless
other people
in this situation that don't
have the same type of advocacy.
So what do we tell
those patients?
And what do we tell medical
students and trainees that
are learning about this now?
MILDA SAUNDERS: I guess that's
a great question, because I
think we need to close.
So I will open it to the panel.
As we leave and go
out to our trainees,
what do we tell the trainees?
And what do we tell
our colleagues?
Not necessarily in nephrology,
but also within primary care,
and within and within the
others have specialties
that need to use this number.
What should we go
out and tell them?
LESLEY INKER: Well I think
that kidney function matters.
Accurate kidney
function matters,
and that if you need help
determining the accurate
level of kidney function, it's
a very appropriate referral
for a nephrologist.
A nephrologist should actually
know that the kidney function
matters.
And if they're questioning
about the level of GFR
for a transplant
referral, there's
absolutely no excuse for
a transplant physician
or a nephrologist to not use a
more accurate, a confirmatory
test.
We talked about the guidelines,
and the more recent guidelines
said, creatinine is
a first-line test
because it's really inexpensive,
it's readily available,
it's on the all the analyzers,
there's a lot of data on it.
So you can run it on
a lot of parameters,
but it's not where you end.
And as a nephrologist,
there's absolutely no excuse
for nephrologists to end there.
How I think it's harder to
educate the other physicians
to ask nephrologists for help.
But I can speak for myself, but
I think I speak for those of us
here to say, please send us--
I would very much like to have
a really careful assessment
of the kidney function.
That's a very appropriate
reason for a referral.
NEIL POWE: SO I will
say, change is hard.
Change is messy.
Change takes time.
But I like to think that
when we make change,
we're making it
for our patients.
And I am not certain whether
the changes that are being made
are being done for our patients,
with our patients best interest
in mind.
And so I think we need to pause.
And this community is galvanized
and capable of finding
the answer to this.
And I say that from both
biologic scientists,
clinical scientists,
social scientists,
we can find the path forward.
But it will be chaos
if we're doing it
the way it's going on now.
And so I would say for
people to be patient.
Remember, these equations
have been here for 20 years.
And the balance sheet is what's
important for the patient.
And I don't know anyone who can
tell us today, definitively,
what that balance sheet looks
like to have a path forward.
MILDA SAUNDERS: OK, so
I think we'll close now.
Thank you so much for
everyone's comments.
There are many questions
left, but that just
means they'll have to
be another, part two,
as more data and
thoughts come forward.
And we welcome you
back for a round two.
And then Dr. Vela, I think,
if you'll close for us.
MONICA VELA: Sure.
I just want to make sure
we thank Dr. Eneanya, Dr
Inker, Dr. Powe, Dr.
Roberts, and Dr. Saunders
for leading us all
in this discussion.
It's very clear to me
that we must not forget
our patients and all of this.
And I'm sure that Dr. Bowman
would be proud to hear us
all putting our patients first.
It's very clear that we
need much more to be done,
and we need to continue
to discuss this.
And we can't be afraid to
have these discussions.
Thank you for the hard
work and the passion.
And thank you most
of all for modeling
thoughtful civil
discourse for all of us.
We are going to move
forward, hopefully
in the path of keeping
our patients first.
First and foremost,
healthy and well.
Again, thank you all very
much for joining us tonight.
Have a good evening.
MILDA SAUNDERS: Thank you.
