Robert Epstein: Good morning.
It's a pleasure to be here today.
I actually thought it was a pleasure to be here until Ken spoke and said he wasn't born
in 1976.
[laughter]
Jesus Christ.
I mean I was in a rock band.
[laughs]
[laughter]
So I feel pretty bummed out frankly.
[laughter]
So it's just a downer from that point onwards.
That's all I can say.
[laughter]
I'm a physician epidemiologist and I work in the crap world, as Howard said, of translation.
So, like Helen, I'm definitely not deep in genomics, but I do know a lot about how we
can twist and turn our database to be useful in the genomic space and that's what I was,
I think, asked to come here and speak about today.
I'm not even going to trust this thing, so let me go to page down, I think.
So what I'd like to do is just two things in the 10 minutes that I'm here for.
Firstly, give you some sense on how you can use payer-type data to either confirm some
hunches that many of you may have by things like phenocopying and I'll show you one quick
example, or investigating potential clinical utility for various tests and then secondly
I would like to pose a point around how the data or the system in which drugs are paid
for in this country is really an interesting and scalable solution to promulgate the use
of these tests where people might believe that the evidence is there.
So, this is a busy slide.
I'm sorry.
It's the only busy slide that I have, but you know, for those of you who are curious
what is payer data?
What are we talking about?
I don't actually use that term.
It was given to me for today's presentation.
But in the United States, typically these are the buckets of data that are available
within different payer environments and I work for Medco.
We cover 65 million Americans for outpatient drugs, so we have all of their outpatient
drug information.
We carry, like Helen was describing, what we call an eligibility file, which is an anonymized,
but linkable individual number for each person, including their aliases as they switch jobs
and things.
With that it gives us age, gender, household relationships, comorbidities in some cases,
and it's updated every month so we know if someone becomes ineligible for some reason
and so therefore we wouldn't find any followup information.
We have all their insurance information, all of their claims data, meaning every outpatient
prescription drug that they've received for many, many years.
So we would know things like compliance, switching, nonpersistence, dosing duration.
Also, information about the prescriber, specialty, year since training, which may have some interest
to you if you're trying to figure out who is it that's ordering these genomic tests
or who isn't.
Medical claims, inpatient or outpatient with ICD-9 codes, so we know, you know, as long
as it's coded what the reason for hospitalization or some event would be and the presence or
absence of a test, as long as it's coded, but not usually the value.
Now, different than others at Medco, we also have some genomic information and I'll give
you a sense for that in a moment.
So, a structured kind of retrospective study in our world, retrospective meaning not going
and approaching patients or doing an IRB-type informed consent.
With our anonymized data you could ask yourself a question for drug X out of 10,000 people
taking drug X, who got a PGX test and who didn't, if you think one of them is ready
for primetime or you think it's being used out there in the real world.
Then you could ask yourself well, on the basis of looking at the physician behavior, did
they do something about it?
And those who did or didn't use the test, did they select a different drug at a different
rate?
Did they dose differently?
Did they perhaps, like in the case of hepatitis C, pay more attention to duration of therapy?
Did the patient's behavior change?
We have a study today underway where we're actually providing the data back to the patient
to see if they're more compliant once they know they are genetically at higher risk for
an adverse problem, actually a clinical problem.
Is the use of a test associated possibly with an increase or decrease of emergency room
visits and why?
You know, there might be some hypothesis you'd have about reducing some side effect or bleeding
or whatever it might be, hospitalizations, maybe the use of other tests, or changes in
therapy and costs.
So those are the kinds of things you can set up.
I'll give you one example, which you may be aware of.
About three or four years ago we had been reading the literature about clopidogrel and
at that time there had been some pharmacokinetic studies that had suggested that 30 percent
of people are either intermediate or poor metabolizers with 2C19.
They were not able to active clopidogrel.
That was all very interesting, but there were really no large scale studies looking at what
does all that mean.
We have about a million clopidogrel users at Medco, so for us, if 300,000 of them are
intermediate or poor metabolizers and not getting the benefit of the drug, we need to
know about that, because there might be something we would recommend to them, maybe one of the
newer therapies that have hit the market, et cetera.
So, we went into our claims data with some researchers from Indiana University in this
case, looked at new starts of people on clopidogrel who had had a recent ACS event, compared people
who were on clopidogrel by itself for a year versus those are taking a concomitant very
potent 2C19 inhibitor for that same time window, and just looked to see the MACE events, the
cardiovascular end points, and found about a 50 percent increase relative risk amongst
those who were taking a potent 2C19 inhibitor.
So, you know, obviously not a randomized trial, but was 17,000 patients and we did adjust
for, you know, everything on earth and subsequent to our presentation, American Heart Association
and publication, there's been about a dozen studies that are similar with different kinds
of payer databases like these that were in JAMA from the VA looking at the same question
and coming out with somewhat similar odds ratios.
Another question that I heard yesterday, which was around laboratory reporting back to physicians
and what do they do with the reports?
We did do a study with the Mayo Clinic Reference Laboratory and one of the questions we asked
ourselves was well, if you know, 500 or 1000 patients -- physicians get back a report on
warfarin genotyping, which says something like you know, patient's got a very high sensitivity,
would they in fact reduce the dose or are they just going to stick it in the chart or
look at it and go I don't know what that means or not do anything?
So here we actually linked up data on close to, I think 600 or 700 patients who were genotyped
with warfarin with their subsequent prescription claims files and what we found was really
nicely kind of a dose-dependent change in the weekly warfarin, just the way the genotypes
would've suggested.
So, they obviously got the report, we know that, within three weeks of these prescriptions.
And if you look at the very bottom, you see the people who had very high sensitivity to
warfarin had about a 17 milligram per week drop in the use of their warfarin and at the
very top the people who needed a higher dose of warfarin, in fact, did get a higher dose
of warfarin.
So, physicians who got the report, which was generated by the Mayo Reference Laboratory,
which provided this extra layer of interpretation, physicians actually did change behavior based
on the report in a way that you would've expected.
So I'd say, you know, some of the buckets of things then that we could look at are does
genomic test information result in differences in compliance like fear factor?
You know, can you scare people based on their use -- or their genomic information to stay
on their therapy?
Because in our world we find with most chronic meds people -- about 50 percent of people
drop off in the first year and that's despite trying to explain to them how important it
is to stay on their therapy.
One little twist in the theme may be that genomic information would be that extra piece
of information that scares them enough to stay on the therapy.
So we're actually looking at that today.
I share with you the example on physician behavior change and also examples on major
clinical events and resource utilization.
Lots of limitations with payer data and we could go on to the conversation for three
hours, but you know, here's just some of them in full disclosure.
I think the biggest one, just in terms of -- from an analytic perspective, in the U.S.
anyway, the medical claims part, the hospitalizations and all of that, those get looked at and kind
of fooled around with and readjudicated for upwards of five months so they're not fresh
the way drug data are, which are instantaneous every day.
Switching gears quickly.
Yep, two minutes.
One of the big problems with promulgating testing beyond figuring out about the evidence
is physician awareness in the field.
We did do a 10,000 physician survey with the American Medical Association a couple of years
ago and these data are in press currently.
Good news on the far left is that 98 percent of American physicians do believe that genes
do relate to drugs, so that's a good thing, because if they didn't believe that we'd really
be in trouble.
But if you look at the arrow and the bar next to the arrow only about 10 percent of physicians
feel they know enough to even order a test.
Ninety percent don't feel comfortable, don't remember having any training or education
in genetics.
So that's a real problem.
And so the one solution I would throw out there that is scalable relates to the only
part of the U.S. health care system that's 100 percent wired today, which is pharmacy.
Since 1990, all 60,000 outpatient pharmacies in America have been electronically wired
with the same data elements being entered no matter where you go.
So for the 90 percent of Americans who carry an insurance card in their wallet, if you
go to Hawaii one day and New York the next we're going to know it and if there's a drug-drug
interaction it pops up right on the screen with decision support rules, you know, right
there to the pharmacist or to the physician if they use an E prescribing device.
What we've been doing at Medco the last few years is using that same system to propagate
a rule that says did you know there is this genomic test for this drug?
You might want to consider it.
The payer is paying for it.
Or if we have the genomic data, did you know there's a gene-drug interaction and here it
is and warning the physician or the pharmacist about it.
So, this is a scalable way in this country to get on board an existing wired system with
gene-drug rule sets that don't exist today for systems like this that are resident in
every single pharmacy in America.
Of course it's all about partnerships and collaborations, public and private.
That was the point for those of you who were not born before 1980 --
[laughter]
This was President Nixon and Elvis Presley.
You laugh, but I was at a meeting about a year ago using the same slide and a young
person came up afterward and said, "Who are those two people?"
[laughter]
So these are some of the folks we've been working with.
I just mostly want to acknowledge the very bottom row, which is the more than 150 payers
and more than 50,000 patients who have participated in one or more studies with us to date.
And these are my conclusions.
I am going to stop there and take any questions.
Thank you.
[applause]
Fire away.
Male Speaker: So, on your warfarin example, what I'm wondering
is how you get the other data besides the drug information?
So, for example, how do you know that the physicians didn't change the dosing because
they were doing clotting times?
Robert Epstein: Oh.
Well, we have the INR tests, whether they do or don't do them.
So we would know if they did or didn't have an INR test between the date of their genomic
test and the date of the drug change.
We wouldn't know the INR time, I mean the actual result, but we would know the presence
or absence of having the test.
Male Speaker: So you know they didn't do --
Robert Epstein: Correct.
Male Speaker: Those tests.
Robert Epstein: That's right.
Male Speaker: Oh.
Well, I'm surprised, actually, that's great.
[laughter]
Robert Epstein: You know, what you find in the real world
of data like this is people don't behave the way you think they do, you know, in academic
settings or other places.
You know, the frequency with which INR testing is actually done is pretty infrequent after
the first week or two of warfarin therapy.
It's kind of sad, but a lot of things are like that.
When we --
Male Speaker: Shouldn't that genetic tests be done for [unintelligible]
therapy the same time they should be --
Robert Epstein: Well, theoretically it would be, yes.
You know, even to -- we went to a panel of oncologists asking them, you know, do you
think for imatinib users, a reminder system on BCR-ABL testing would be a good idea, because
it's in everybody's guidelines to do that a certain frequency.
And they all said no, no.
We don't need to be told, because we know to do it blah, blah, blah.
We looked at the data set and, you know, 40 percent of the time it's not being done, nationally.
So you know, maybe in your practice you do it, but it's not happening.
Yep.
Female Speaker: You said under most circumstances you're not
--
Robert Epstein: Oh, sorry.
Female Speaker: Sorry.
Robert Epstein: Sorry, sorry, sorry.
Male Speaker: Could you comment -- so you manage this, but
you have people you report to, companies and employers of various sorts.
What's their level of interest in genetics?
Robert Epstein: That's a great question.
So, about two years ago we actually surveyed 700 payers who represent about 60 billion
dollars of prescription drug expenditures in this country and we had them force rank
a bunch of different topics and pharmacogenomics was one on the list.
It's the number two topic of interest.
Do you believe?
So, their number one is like benefit designs, co-pays, deductibles, that kind of stuff.
But number two was pharmacogenomics.
That beat out generics, bio-tech drugs, pipeline, you know, all sorts of drug-related questions,
but pharmacogenomics has the payer's interest right now.
They're looking at it as a solution, not so much as an obstacle, but a solution to the
imprecision that happens today.
Male Speaker: Could you comment on --
Male Speaker: [unintelligible]
Male Speaker: Oh, sorry.
Male Speaker: I have a quick question.
I was interested in the low prevalence or the low comfort level of physicians in ordering
tests and you're talking about delegating to pharmacists the advising on the genetic
testing, so for you specifically and maybe more generally for this group is, what's the
role of the medical geneticists and genetic counselors in all of this?
And I think it's a question specifically here it would be real interesting to hear the answer,
but just in general, you know, how's that community which has traditionally been the
experts in counseling going to interact with all this new data?
Robert Epstein: Let me first say that there does not seem
to be a natural home for who owns the communication and understanding around all this new science
and there needs to be.
I mean, there's lots of different players in this space.
We hire in -- we have about 30 genetic counselors on our staff today who talk to physicians
every day, but that's not a scalable solution.
There are only 2000 of them in the country, so you know, who should own this information
and be the person communicating it?
And I don't have a great answer for that one.
I've been to so many meetings where everybody says you know, it's over there, but I'm not
sure about the answer to that question.
But we do need somebody who really owns and keeps people up to date and has a system that
learns and educates people, because the knowledge is moving so quickly it's very hard for people
who are in practice to keep up.
Male Speaker: And by the way, I recognize Nixon, but I was
wondering who that person on the right was.
Robert Epstein: [laughs]
[laughter]
Male Speaker: So, could you comment on Medco's DNA Direct
company and sort of how you think for something that needs a scale at this level, does it
need to be a private entity who can hire 40 people to work on this or can -- should it
be a government entity?
Could you comment along those lines?
Robert Epstein: Sure.
We -- DNA Direct was a company we acquired a couple of years ago.
We started off doing lots of studies and research and helping payers get access to individual
tests that were related to drugs, of which there may be like 40 total.
But what the payers told us was the genetic testing in general was so much bigger.
You know, you know this.
There's 2000 to 3000 genetic tests and they wanted help managing all of that.
So, we identified a company called DNA Direct who had sort of a system and software that
helps physicians do decision support and figure out, you know, are the indications right for
that given test?
An example of where a finding in that product where it's been used, and I won't say the
percent, but a surprising percent of physicians order a BCR-ABL test when what they really
wanted was a BRCA1 test and vice versa and I'm not kidding.
So you're getting a ton of leukemia tests in breast cancer people and vice versa because
they start with B.
[laughter]
Well, it's the way it's working.
I'm serious from real experience.
So, you know, we do need some kind of decision support tools and I don't know if it has to
be the private sector, the public sector, but we definitely need to get ready for the
future.
Male Speaker: [unintelligible]
Male Speaker: I think we stop there and move on.
Robert Epstein: You can ask me questions during the break.
It's fine, if you want.
Thank you very much.
Appreciate it.
[applause]