Episode Transcript
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Erin Spain, MS (00:10):
This is Breakthroughs,
a podcast from Northwestern University
Feinberg School of Medicine.
I'm Erin Spain, host of the show.
Northwestern University Feinberg Schoolof Medicine is home to a team of premier
faculty and staff biostatisticians,who are the driving force of data
(00:30):
analytic innovation and excellence here.
Today, we are talking with Dr.
Denise Scholtens, a leader inbiostatistics at Northwestern,
about the growing importance of thefield, and how she leverages her
skills to collaborate on severalprojects in Maternal and Fetal Health.
She is the Director of the NorthwesternUniversity Data Analysis and
(00:51):
Coordinating Center, NUDACC, andChief of Biostatistics in the
Department of Preventive Medicine aswell as Professor of Preventive
Medicine and Neurological Surgery.
Welcome to the show.
Denise Scholtens, PhD (01:02):
Thank you so much.
Erin Spain, MS (01:03):
So you have said in
the past that you were drawn to this
field of biostatistics because you'reinterested in both math and medicine, but
not interested in becoming a clinician.
Tell me about your path intothe field and to Northwestern.
Denise Scholtens, PhD (01:17):
You're right.
I have always been interestedin both math and medicine.
I knew I did not want to beinvolved in clinical care.
Originally, fresh out of college, Iwas a math major and I taught high
school math for a couple of years.
I really enjoyed that, loved the kids,loved the teaching parts of things.
Interestingly enough, my departmentchair at the time assigned
me to teach probability andstatistics to high school seniors.
(01:40):
I had never taken a statistics coursebefore, so I was about a week ahead
of them in our classes and found thatI just really enjoyed the discipline.
So as much as I loved teaching, Idid decide to go ahead and invest
in this particular new area thatI had found and I really enjoyed.
So wanted to figure out how I couldengage in the field of statistics.
Decided to see, you know,exactly how studying statistics
(02:05):
could be applied to medicine.
At the time, Google was brand new.
So I literally typed in the two words mathand medicine to see what would come up.
And the discipline of biostatisticsis what Google generated.
And so here I am, I applied to gradschool and it's been a great fit for me.
Erin Spain, MS (02:23):
Oh, that's fantastic.
So you went on to get a PhD, andthen you came to Northwestern in 2004.
And so tell me a little bitabout the field then and how it's
changed so dramatically since.
Denise Scholtens, PhD (02:37):
So yes, I started
here at Northwestern in 2004, just a few
months after I had defended my thesis.
At the time there was really an emergingfield of study called bioinformatics.
So I wrote my thesis in the spaceof genomics data analysis with
what at the time was a brandnew technology, microarrays.
This was the first way we couldmeasure gene transcription
(03:00):
at a high throughput level.
So I did my thesis work in that space.
I studied at an institution with a lot ofstrengths and very classical statistics.
So things that we think of inbiostatistics like clinical
trial design, observationalstudy analysis, things like that.
So I had really classic biostatisticstraining and then complimented that
with sort of these emerging methodswith these high dimensional data types.
(03:23):
So I came to Northwestern here and Isort of felt like I lived in two worlds.
I had sort of classic biostatclinical trials, which were
certainly, you know, happening here.
And, that work was thriving here atNorthwestern, but I had this kind of
new skillset, and I just didn't quiteknow how to bring the two together.
That was obviously a longtime ago, 20 years ago.
Now we think of personalized medicineand genomic indicators for treatment
(03:48):
and, you know, there's a whole varietyof omics data variations on the theme
that are closely integrated with clinicaland population level health research.
So there's no longer any confusion for meabout how those two things come together.
You know, they're two disciplines thatvery nicely complement each other.
But yeah, I think that does speak tohow the field has changed , you know,
(04:10):
these sort of classic biostatisticsmethods are really nicely blended with
a lot of high dimensional data types.
And it's been fun to be a part of that.
Erin Spain, MS (04:17):
There was only
a handful of folks like you
at Northwestern at the time.
Tell me about now and the demandfor folks with your skill set.
Denise Scholtens, PhD (04:26):
When I came
to Northwestern, I was one of a very
small handful of biostatistics faculty.
There were five of us.
We were not even called adivision of biostatistics.
We were just here as theDepartment of Preventive Medicine.
And a lot of the work we did wasreally very tightly integrated with the
epidemiologists here in our departmentand we still do a lot of that for sure.
(04:46):
There was also some work going on withthe Cancer Center here at Northwestern.
But yeah, a pretty smallgroup of us, who has sort of a
selected set of collaborations.
You know, I contrast that now to ourcurrent division of biostatistics where
we are over 20s, pushing 25, dependingon exactly how you want to count.
Hoping to bring a couple of newfaculty on board this calendar year.
(05:08):
We have a staff of about25 statistical analysts.
And database managers and programmers.
So you know, when I came therewere five faculty members and I
think two master's level staff.
We are now pushing, you know, pushing50 people in our division here
so it's a really thriving group.
Erin Spain, MS (05:26):
in your opinion,
what makes a good biostatistician?
Do you have to have a little bit ofa tough skin to be in this field?
Denise Scholtens, PhD (05:34):
I do
think it's a unique person who
wants to be a biostatistician.
There are a variety of traits thatcan lead to success in this space.
First of all, I think it's helpful to bewildly curious about somebody else's work.
To be an excellent collaborativebiostatistician, you have to be able to
learn the language of another discipline.
So some other clinical specialtyor public health application.
(05:57):
Another trait that makes a biostatisticiansuccessful is to be able to ask the
right questions about data that will becollected or already have been collected.
So understanding the subtleties there,the study design components that lead
to why we have the data that we have.
You know, a lot of our data, you couldthink of it in a simple flat file, right?
(06:18):
Like a Microsoft Excelfile with rows and columns.
That certainly happens a lot,but there are a lot of incredibly
innovative data types out there:
wearables technology, imaging data, (06:23):
undefined
all kinds of high dimensional data.
So I think a tenacity to understandall of the subtleties of those data and
to be able to ask the right questions.
And then I think for a biostatisticianat a medical school like ours, being
able to blend those two things, sounderstanding what the data are and
(06:43):
what you have to work with and whatyou're heading toward, but then also
facilitating the translation of thoseanalytic findings for the audience
that really wants to understand them.
So for the clinicians, for the patientsfor participants and the population
that the findings would apply to.
Erin Spain, MS (07:00):
It must feel good,
though, in those situations where you
are able to help uncover somethingto improve a study or a trial.
Denise Scholtens, PhD (07:07):
It really does.
This is a job that's easy to getout of bed for in the morning.
There's a lot of really goodthings that happen here.
It's exciting to know that the workwe do could impact clinical practice,
could impact public health practice.
I think in any job, you know, you cansometimes get bogged down by the amount
of work or the difficulty of the workor the back and forth with team members.
(07:30):
There's just sort of all of theday to day grind, but to be able to
take a step back and remember theactual people who are affected by
our own little niche in this world.
It's an incredibly helpful andmotivating practice that I often keep
to remember exactly why I'm doing whatI'm doing and who I'm doing it for.
Erin Spain, MS (07:50):
Well, and
another important part of your
work is that you are a leader.
You are leading the center, NUDACC, thatyou mentioned, Northwestern University
Data Analysis and Coordinating Center.
Now, this has been openfor about five years.
Tell me about the center and why it'sso crucial to the future of the field.
Denise Scholtens, PhD (08:08):
We
specialize at NUDACC in large scale,
multicenter prospective studies.
So these are the clinical trials orthe observational studies that often,
most conclusively, lead to clinical orpublic health practice decision making.
We focus specifically on multicenter work.
(08:29):
Because it requires a lot of centralcoordination and we've specifically
built up our NUDACC capacity to handlethese multi center investigations
where we have a centralized database,we have centralized and streamlined
data quality assurance pipelines.
We can help with central team leadershipand organization for large scale networks.
So we have specificallyfocused on those areas.
(08:51):
There's a whole lot of projectmanagement and regulatory expertise
that we have to complement ourdata analytics strengths as well.
I think my favorite part ofparticipating in these studies is we
get involved at the very beginning.
We are involved in executivelevel planning of these studies.
We oversee all components of study design.
(09:12):
We are intimately involved in thedevelopment of the data capture systems.
And in the QA of it.
We do all of this work on the front endso that we get all of the fun at the end
with the statistics and can analyze datathat we know are scientifically sound, are
well collected, and can lead to you know,really helpful scientific conclusions.
Erin Spain, MS (09:33):
Tell me about that
synergy between the clinicians and
the other investigators that you'reworking with on these projects.
Denise Scholtens, PhD (09:41):
It is always
exciting, often entertaining.
Huge range of scientific opinion andexpertise and points of view, all of which
are very valid and very well informed.
All of the discussion that could go intodesigning and launching a study, it's
just phenomenally interesting and tryingto navigate all of that and help bring
(10:01):
teams to consensus in terms of what isscientifically most relevant, what's
going to be most impactful, what ispossible given the logistical strengths.
Taking all of these well informed,valid, scientific points of view and
being a part of the team that helpsintegrate them all toward a cohesive
study design and a well executed study.
(10:21):
That's a unique part of the challengethat we face here at NUDACC,
but an incredibly rewarding one.
It's also such an honor and a giftto be able to work with such a
uniformly gifted set of individuals.
Just the clinical researchers who devotethemselves to these kinds of studies
are incredibly generous, incrediblythoughtful and have such care for their
(10:43):
patients and the individuals that theyserve, that to be able to sit with them
and think about the next steps for agreat study is a really unique privilege.
Erin Spain, MS (10:52):
How unique is a
center like this at a medical school?
Denise Scholtens, PhD (10:55):
It's
fairly unique to have a center
like this at a medical school.
Most of the premier medical researchinstitutions do have some level of
data coordinating center capacity.
We're certainly working toward trying tobe one of the nation's best, absolutely,
and build up our capacity for doing so.
I'm actually currently a part of agroup of data coordinating centers
where it's sort of a grassroots effortright now to organize ourselves and
(11:19):
come up with, you know, some unifiedstatements around the gaps that we
see in our work, the challenges thatwe face strategizing together to
improve our own work and to potentiallycontribute to each other's work.
I think maybe the early beginningsof a new professional organization
for data coordinating centers.
We have a meeting coming up of about,I think it's 12 to 15 different
(11:40):
institutions, academic researchinstitutions, specifically medical schools
that have centers like ours to try totalk through our common pain points and
also celebrate our common victories.
Erin Spain, MS (11:51):
I want to shift
gears a little bit to talk about
some of your research collaborations,many of which focus on maternal
and fetal health and pregnancy.
You're now involved with a study withfolks at the Ohio State University
that received a 14 million grantlooking at the effectiveness of
aspirin in the prevention ofhypertensive disorders in pregnancy.
(12:12):
Tell me about this work.
Denise Scholtens, PhD (12:14):
Yes, this
is called the aspirin study.
I suppose not a very creativename, but a very appropriate one.
What we'll be doing in this studyis looking at two different doses
of aspirin for trying to preventmaternal hypertensive disorders of
pregnancy in women who are consideredat high risk for these disorders.
This is a huge study.
(12:35):
Our goal is to enroll 10,742 participants.
This will take place at 11different centers across the nation.
And yes, we at NUDACC will serve asthe data coordinating center here,
and we are partnering with the OhioState University who will house
the clinical coordinating center.
So this study is designed to lookat two different doses to see which
(12:58):
is more effective at preventinghypertensive disorders of pregnancy.
So that would include gestationalhypertension and preeclampsia.
What's really unique about thisstudy and the reason that it is so
large is that it is specificallyfunded to look at what's called a
heterogeneity of treatment effect.
What that is is a difference in theeffectiveness of aspirin in preventing
(13:22):
maternal hypertensive disorders,according to different subgroups of women.
We'll specifically have sufficientstatistical power to test for
differences in treatment effectiveness.
And we have some high prioritysubgroups that we'll be looking at.
One is self-identified race.
There's been a noted disparity inmaternal hypertensive disorders,
(13:42):
for individuals who self identifyaccording to different races.
And so we will be powered to see ifaspirin has comparable effectiveness
and hopefully even better effectivenessfor the groups who really need it,
to bring those rates closer to equitywhich is, you know, certainly something
we would very strongly desire to see.
(14:02):
We'll also be able to look at subgroupsof women according to obesity, according
to maternal age at pregnancy, accordingto the start time of aspirin when
aspirin use is initiated during pregnancy.
So that's why the trial is so huge.
For a statistician the statisticiansout there who might be listening, this
is powered on a statistical interactionterm, which doesn't happen very often.
(14:24):
So it's exciting that thetrial is funded in that way.
Erin Spain, MS (14:27):
Tell me a little bit more
about this and how your specific skills
are going to be utilized in this study.
Denise Scholtens, PhD (14:32):
Well, there
are three biostatistics faculty here
at Northwestern involved in this.
So we're definitelydividing and conquering.
Right now, we're planning thisstudy and starting to stand it up.
So we're developing ourstatistical analysis plans.
We're developing the database.
We are developing ourrandomization modules.
So this is the piece of the study whereparticipants are randomized to which
(14:53):
dose of aspirin they're going to receive.
Because of all of the subgroups thatwe're planning to study, we need to make
especially sure that the assignmentsof which dose of aspirin are balanced
within and across all of those subgroups.
So we're going to be using someadaptive randomization techniques to
ensure that that balance is there.
So there's some fun statistical andcomputer programming innovation that will
(15:17):
be applied to accomplish those things.
So right now, there areusually two phases of a study
that are really busy for us.
That's starting to studyup and that's where we are.
And so yes, it is verybusy for us right now.
And then at the end, you know, infive years or so, once recruitment is
over, then we analyze all the data,
Erin Spain, MS (15:36):
Are there any
guidelines out there right now about
the use of aspirin in pregnancy.
What do you hope thatthis could accomplish?
Denise Scholtens, PhD (15:43):
Prescribing aspirin
use for the prevention of hypertension
during pregnancy is not uncommon at all.
That is actually fairly routinely done,but that it's not outcomes based in
terms of which dosage is most effective.
So 81 milligrams versus 162 milligrams.
That's what we will be evaluating.
(16:04):
And my understanding is that cliniciansprescribe whatever they think is better,
and I'm sure those opinions are very wellinformed but there is very little outcomes
based evidence for this in this particularpopulation that we'll be studying.
So that would be the goal here, wouldbe to hopefully very conclusively
say, depending on the rates ofthe hypertensive disorders that we
(16:24):
see in our study, which of the twodoses of aspirin is more effective.
Importantly, we will also be trackingany side effects of taking aspirin.
And so that's also very much often a partof the evaluation of You know, taking a,
taking a drug, right, is how safe is it?
So we'll be tracking thatvery closely as well.
(16:45):
Another unique part of this study isthat we will be looking at factors
that help explain aspirin adherence.
So we are going to recommendthat participants take
their dose of aspirin daily.
We don't necessarily expect that's alwaysgoing to happen, so we are going to
measure how much of their prescribed dosethey are actually taking and then look at,
(17:06):
you know, factors that contribute to that.
So be they, you know, social determinantsof health or a variety of other
things that we'll investigate to tryto understand aspirin adherence, and
then also model the way in which thatadherence could have affected outcomes.
Erin Spain, MS (17:21):
This is not the
first study that you've worked on
involving maternal and fetal health.
Tell me about your interestin this particular area, this
particular field, and some ofthe other work that you've done.
Denise Scholtens, PhD (17:31):
So I actually
first got my start in data coordinating
work through the HAPO study.
HAPO stands for HyperglycemiaAdverse Pregnancy Outcome.
That study was started here atNorthwestern before I arrived.
Actually recruitment to the studyoccurred between 2000 and 2006.
Northwestern served as the centralcoordinating center for that study.
It was an international study of 25,000 pregnant individuals who were
(17:57):
recruited and then outcomes wereevaluated both in moms and newborns.
When I was about mid career here,all the babies that were born as a
part of HAPO were early teenagers.
And so we conducted a followup study on the HAPO cohort.
So that's really when I got involved.
It was my first introduction to beinga part of a coordinating center.
(18:20):
As I got into it, though, I saw the beautyof digging into all of these details for
a huge study like this and then saw theseincredible resources that were accumulated
through the conduct of such a large study.
So the data from the study itselfis, was of course, a huge resource.
But then also we have all ofthese different samples that
sit in a biorepository, right?
(18:42):
So like usually blood sample collectionis a big part of a study like this.
So all these really fun ancillarystudies could spin off of the HAPO study.
So we did some genomics work.
We did some metabolomics work.
We've integrated the two andwhat's called integrated omics.
So, you know, my work in this spacereally started in the HAPO study.
(19:03):
And I have tremendously enjoyedintegrating these high dimensional
data types that have come from thesereally rich data resources that have
all, you know, resulted because of thishuge multicenter longitudinal study.
So I kind of accidentally fellinto the space of maternal and
fetal health, to be honest.
But I just became phenomenally interestedin it and it's been a great place.
Erin Spain, MS (19:24):
Would you say that this is
also a population that hasn't always been
studied very much in biomedical science?
Denise Scholtens, PhD (19:32):
I think
that that is true, for sure.
There are some unique vulnerabilities,right, for a pregnant individual and for
the fetus, right, and in that situation.
You know, the vast majority of whatwe do is really only pertaining
to the pregnant participant but,you know, there are certainly
fetal outcomes, newborn outcomes.
And so, I think conducting researchin this particular population is
(19:53):
a unique opportunity and there arecomponents of it that need to be treated
with special care given sort of thisunique phase of human development
and this unique phase of of life.
Erin Spain, MS (20:04):
So, as data generation
just really continues to explode,
and technology is advancing so fast,faster than ever, where do you see
this field evolving, the field ofbiostatistics, where do you see it
going in the next five to ten years?
Denise Scholtens, PhD:
That's a great question. (20:19):
undefined
I think all I can really tellyou is that I'm continually
surprised by new data types.
I, think that we will see anemergence of a whole new kind of
technology that we probably can'teven envision five years from now.
And I think that's the fun partabout being a biostatistician is
(20:39):
seeing what's happening and thentrying to wrap your mind around the
possibilities and the actual natureof the data that are collected.
You know, I think back to 2004and this whole high throughput
space just felt so big.
You know, we could look atgene transcription across the
genome using one technology.
And we could only lookat one dimension of it.
(21:00):
Right now it just seems so basic.
When I think about where thefield has come over the past
20 years, it's just phenomenal.
I think we're seeing similar emergenceof the scale and the type of data
in the imaging space and in thewearable space, with EHR data, just.
You know, all these different technologiesfor capturing, capturing things that
we just never even conceived of before.
(21:21):
I do hope that that we continueto emphasize making meaningful and
translatable conclusions from these data.
So actionable conclusions that can impactthe way that we care for others around us.
I do hope that remains a guidingprinciple in all that we do.
Erin Spain, MS (21:40):
Why is Northwestern
Medicine and Northwestern Feinberg
School of Medicine such a supportiveenvironment to pursue this type of work?
Denise Scholtens, PhD (21:47):
That's a
wonderful question and one, honestly,
that faculty candidates often ask me.
When we bring faculty candidatesin to visit here at Northwestern,
they immediately pick up on the factthat we are a collaborative group of
individuals who are for each other.
Who want to see each other succeed,who are happy to share the things
(22:07):
that we know and support each other'swork, and support each other's
research, and help strategize aroundthe things that we want to accomplish.
there is a strong culture here, at leastin my department and in my division
that I've really loved that continuesto persist around really genuinely
collaborating and genuinely sharinglessons learned and genuinely supporting
(22:29):
each other as we move toward common goals.
We've had some really strong, generousleadership who has helped us to get
there and has helped create a culturewhere those are the guiding principles.
In my leadership role is certainlysomething that I strive to maintain.
Really hope that's true.
I'm sure I don't do it perfectlybut that's absolutely something I
want to see accomplished here inthe division and in NUDACC for sure.
Erin Spain, MS (22:50):
Well, thank you so much
for coming on the show and telling us
about your path here to Northwesternand all of the exciting work that we
can look forward to in the coming years.
Denise Scholtens, PhD (22:59):
Thank
you so much for having me.
I've really enjoyed this.
Erin Spain, MS (23:04):
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