Designing Clinical Trials Using Adaptive Designs

Designing Clinical Trials Using Adaptive Designs


I’m going to have just about six slides and they’re very brief
and they’re very general. So each one of these addresses a general topic. The first general
topic is adaptive clinical designs considered in toto. That is the great variety of clinical
designs and as pointed out in a recent article by Chow and Chang in the Orphanet Journal
of Rare diseases, there are actually three different types of adaptation. There are prospective
adaptations and that’s really the subject of this particular seminar. Talking about
the prospective or adaptive designs in which we can consider things like adaptive randomization,
early stopping, dropping the losers, sample size re-estimation and various other types
of adaptive designs. But of course we also have current adaptations. These are adaptations
that are made to — generally to randomize clinical trials in which the investigators
decide whoa, we have to go back to the drawing board. And these concurrent adaptations frequently
involve things like conclusionary exclusionary criteria, changing those typically because
oh, subject recruitment is not quite what we thought it would be. Let’s relax our criteria
a little bit or let’s allow this nor that to happen. Evaluability criteria, the data,
those regiment or treatment duration, hypothesis, study endpoints and other. And I’ll jump over
to your right, the retrospective adaptations before I go to the bottom of the slide. The
retrospective adaptations would be primarily things like statistical analysis changes.
These are made before the data base lock or unblinding of the treatment code. So we’re
still in the sense, pretty pure with regard to this whole process. But it’s a reconsideration
of the statistical analysis. Now notice that prospective adaptations, you can see in the
red print below. These are implemented by study protocol. So adaptive designs are all
the planning is done in advance. It is intended that there will be an adaptive component.
In the case of the concurrent adaptations these were not intended but they’re implemented
by protocol amendments. And we can elaborate that a little bit as we will in a moment.
In the case of the retrospective adaptations those are implemented by regulatory reviewer’s
consensus. So in each one of these cases there is a particular type of implementation. Now
moving to the bottom of this slide this is really an elaboration of implementation or
protocol amendments. It is a very interesting report by Getz and colleagues published in
2011 in therapeutic innovation and regulatory science. And what they did was to look at
a large number of drug trials. Asking the question how often are these amended and what
is the nature of the amendment. Well, they noticed that nearly 60 percent of all protocols
used in clinical trials for new drugs were amended, the great majority are amended. 40
percent, this was surprising to me, 40 percent were amended before the first subject or the
first visit. So right away people are saying let’s go back to the drawing board. An average
of 2.3 amendments were made per protocol, and each amendment required an average of
6.9 changes. So there is a lot of going back to the drawing board, a lot of reconsideration,
a lot of time lost and a lot of head scratching. A number of these were found to be avoidable.
That is, if the investigators had spent a little bit more time considering the design
in advance they might have been able to avoid these. But the point of this is simply to
say adaptation is a fairly frequently occurring thing. Whether we intend to do it or whether
we do not. Adaptive clinical designs, as I just mentioned are several types and we could
maybe explore some of these a little bit more in the discussion section. I’m not going to
talk for very long so I hope there will be time for discussion. Whatever we do, whether
it’s any of those bulleted and adaptive randomization, early stopping etc. There are important constraints
on adaptations. And three of those are controlling the type error, type one, error rate. Number
two. Being sure that the trial has a high probability of answering the research question.
We don’t want to sacrifice that. And finally maintaining equipoise which I think is probably
best defined as meaning that in the general scientific community there is uncertainty
regarding the advantages or disadvantages of a particular treatment. So we’ve not prejudged
the matter but we do think it is worthy of exploration. Now another very broad question,
why is it that clinical trials fail? We’ve had enough clinical trials and certainly in
the drug arena but also in behavioral interventions for us to take a step back and see why there
are failures and what that suggests to us about more efficient ways of caring out clinical
trials. First the treatment works for some but not all. And this is true not just in
the behavioral areas but also for example in clinical oncology where it is recognized
that there are so-called exceptional responders. Some individuals how respond very, very well
to a medication, much better than the average patient enrolled in these trials and although
for a long time there was kind of a reflexive rejection or dismissal of any end of one study,
and most people then would recoil from it saying that is and there is one of those dreaded
three syllable words anecdote if you report on a single subject you’ve reported anecdotally.
But even in areas like clinical oncology there seems to be a, even perhaps drudging acceptance
that end of one can be informative. When we at the [inaudible] executive board were trying
to get evidence based practice going in our field, we approach the people at the Oxford
Group to see if they would consider single subject designs as possible being incorporated
somewhere in their levels of evidence. And they politely demurred but we are seeing now
that even in medicine single subject designs are getting perhaps a better receptance than
they might have a few years ago. Perhaps underlying both of those would be the assumption of the
universal pathophysiology of a condition. This is probably easier to grant in drugs
than it is in behavior. That is, if we assume that Parkinson’s disease is caused by the
same pathological mechanisms than all individuals with Parkinson’s disease can be assumed to
respond to a drug in a certain way. But can we make that assumption for childhood apraxia
speech? That there is one universal pathophysiology? Can we assume this [inaudible] has one common
underlying pathophysiology? Can we assume that specific language impairment has one
underlying pathophysiology? In many of the conditions that we’re concerned with we don’t
necessarily have a guarantee that we’re satisfying the principle of universal pathophysiology.
And three more dreaded, or two more three syllable words that we often dread. Placebo,
where people will benefit perhaps because they believe, even if they are in the control
arm of an experiment, hey, I’m taking a good drug, I’m getting better, I feel much better
this week than last week. Or kind of the reverse of that the nocebo effect which occurs particularly
in individuals with degenerative diseases in which they believe that they are going
to get worse even if they are in the clinical arm of the study. Also questions about clinical
end points when should the study be ceased or what is a reasonable stopping point? And
we already heard examples of that. It’s also possible that different treatments have different
mechanisms of action, different sources of outcome variability, different windows of
optimal effectiveness in the history of a disorder. And that has already been suggested
in the preceding talks. Another very general slide. Within the general field of communication
disorders where we’re hoping to make sure that we have evidence based practice for all
disorders, we have several barriers. One, many of the disorders are of low incidence.
It’s not easy to recruit the participants who will be able to satisfy the inclusionary,
exclusionary criteria. Not just for the rare or orphan disorders but even for some disorders
that seem to occur more frequently. For example childhood apraxia of speech. Not necessarily
an easy group to recruit. We also have the problem of heterogeneity of the affected individuals
including diverse and multi-factorial ideologies. Many of the disorders of interest to us, for
example stuttering, may have a genetic base for some individuals at least, but that genetic
factor somehow is going to be interplaying with various environmental factors which could
vary by individual. So we don’t have simple ideological principles for many of the disorders
of interest. We also have a substantial problem with co morbidity and co-occurrence of disorders.
In the case of specific language impairment co-morbidities have been reported as anywhere
from 5 to 15 percent. For stuttering co-morbidities have been reported as high as 60 percent so
many individuals who stutter may also have phonological or speech sound disorders, language
disorders etc. So these people do not come to us in one nice clean clinical category.
We also have problems of course with limited resources. We don’t have deep pockets. We’re
not funded in the main by large companies such as drug companies. We need to seek support
wherever we can get it. Certainly NIH but perhaps also some private funding sources.
So we have difficulties with funding, patient access and cooperative efforts. Non adherence
can certainly be a problem. And that occurs with both some of the participating clinicians
and also of course with respect to some of the people who are receiving treatments, the
patients or clients. And end point on certainty another problem, another barrier in our field.
To take just one example and I don’t have time to take a lot of example so let me just
consider one. And this is aphasia. And you can see to your left on the slide this is
taken from the ASHA website. This is the practice portal evidence map and if you haven’t seen
it I certainly recommend it to you because it does represent a serious effort by our
association to make available to clinicians summaries of the evidence for the various
treatments that are being proposed. So here we have aphasia and under that you see the
treatment tab and these are a number of different procedures that have been recommended for
intervention of aphasia. These have received various degrees of research, of clinical trials.
One of the most frequently investigated is CILT constraint induced language therapy.
And if you go to the practice portal and click on that you’ll see a summary including a review
of evidence for the efficacy of constraint induced language therapy. Which generally
points out that there is a value of intensity of therapy. But we have — the point is we
have several different types of intervention. These are conceivably useful or more useful
or less useful I should say, at various points post stroke. They might be beneficial within
different types of therapeutic windows and they might even be useful in combination or
perhaps used successively. And any of these could be used in conjunction with ongoing
pharmaco therapy. In a recent doctrine review by Kelly Brady and Andrevey they looked at
speech and language therapy for aphasia following stroke, their assumption you can see in that
text box there, the trials randomized small numbers of participants across a range of
characteristics including age, time since stroke, severity profiles, interventions and
outcome. Of people with aphasia come to us with a variety of different profiles. Very,
very difficult to establish homogenous chemical groups for research. What they suggested is
we need to know for a specific patient groups, not just one large group of people with aphasia,
but for specific patient groups, what is the optimum approach? What particular method of
intervention? Two, the frequency, how often should that be done. Number three. The duration
of allocation and number four, the format of therapy. For example individual therapy,
group therapy or these days even teletherapy. Many different variations that could be imagined
in the service delivery arena. So all I’ve tried to point out here is that there is some
very, very general issues that I think relate to this idea of clinical adaptive designs.
And I’m certainly intrigued but the possibility of using some of the adaptive clinical designs
to give us the opportunity to be sensitive to some of these group differences but also
to make more efficient use of the very difficult to recruit subjects and as we heard from Dr.
Langmore and Dr. Robbins that is a frequent problem. My guess is that the people who are
doing clinical trials in drugs are not the only ones who are having the need for amendments.
And I don’t think there has been a study that I know of that indicates how frequently those
are made for behavioral interventions but just judging from what we’ve heard today that’s
probably pretty common. One particular question I’d like to ask Dr. Yates is, are you aware
of particular cases in which the adaptive designs have been used for behavioral interventions?
Is there a literature that we can look to to give us guidance? And the second question
I was interested in relates to some of the foregoing discussion. What can we do with
conditions in which we have a progressive loss of ability or health? Most of what we’ve
talked about assumes that there is some kind of steady state but many of the conditions
of interest to us like progressive neurological diseases, ALS, Parkinson’s disease. We’re
not dealing with a stable baseline. We’re dealing with a very predictable decline in
ability. And I wonder if there are some designs that may help us look at something like a
rate of change that might be sensitive to those kinds of problems. Thank you.>>Applause.>>So your first question maybe is a little
bit easier. Most of my work is in pharmacologic agents so I can’t point to something specifically
but my — when I first started working in [inaudible] I did a little bit of work with
the addictions group and my guess is that they have made progress by leaps and bounds
in terms of adaptive designs. A lot of their work is in behavior modification therapy for
helping these patients. And I would have to check the literature by I think that might
be a place to take a peek and see what they’ve been doing in terms of adapting with behavior
modifications. Some of the adaptive designs would be very easily translated into those
behaviors. As I said, the dose findings sort of thing where we have to rethink about what
the dose means, what the outcome is might take a little bit more time but the adaptations
that you talked about that you mentioned dropping the losers, things of that sort would be very
easily translatable to those sorts of therapies. Your second question is a little bit more
complicated. Those — the idea of a progressively degenerating condition where we’re trying
to assess how that happens, there are more complicated statistical models which allow
us to assess how a particular patient changes over time? And we can assess that rate of
change? For a treatment versus, you know one treatment versus another treatment. But it
would definitely make some of the earlier phase modeling designs that I talked about
a little bit more complicated. Because really as you suggested, what we’re trying to say
is can we make that rate of change less in the treated population and that’s a little
bit harder to establish.>>Applause. So if anyone in the audience
wants to ask questions we have Dr. Yates for five more minutes. In the back there, come
on up. Everyone come up to the panel please. Yeah?>>[Inaudible]>>So yes ish. So there are adaptive designs
which can be implemented in the confirmatory setting. This last presentation actually highlighted
some of those things like sample size re-estimation. Actually when you think about a phase three
clinical trial that does interim analysis for efficacy or utility that’s actually an
adaptive design. It’s adapting the protocol to stop sooner than you had anticipated based
on what you’re seeing. But we don’t think about it that way because it has been ingrained
in our training for so long. Adaptive to us means new and exciting. That’s not exciting.
So my general — this is just my general feeling, is that adaptive designs are most useful as
you suggested them to be. In the early phase exploratory setting where you are trying to
establish what treatment am I looking at, what sort of effect size am I seeing. Which
patients is it going to work best in. That’s where adaptive designs will really give you
the most bang for your buck. When you get to the confirmatory setting, again this is
my opinion, you should know the answers to the questions that the adaptive designs are
designed to answer. So you shouldn’t have to learn. If you think about it that way,
the adaptive designs are helping you learn from the data as you go. By the time you get
to the confirmatory setting you’re trying to confirm what you know to be a potential
treatment works. You shouldn’t be fiddling with things at that point. But there is a
big push as well to meld sort of the phase two and the phase three together into adaptive
designs that make this process more efficient.>>[Inaudible]>>I guess what we’re saying is rather than
embarking on a large phase three trial which is a confirmatory science stage, you really
need to look at the phase two stage and the phase one stage to make sure that you’re getting
the optimal bang for your buck. And you’re going to have to use these or these optimal
designs will help you in finding dosages and characteristics of delivery of your treatment
in different ways. I should mention that the NIH has a planning grant for clinical trials
and it can be used to considerable degree to work with the [inaudible] statistician
to set up just these kinds of designs, and I think that that stage and that mechanism
has been relatively underused. There is, it’s an r I forget what the r number is but there
is an r number for a planning grant to do just this kind of work.>>[Inaudible] And people don’t use them as
much as they should. They really dive into a confirmatory study before they’ve done the
work on finding out the optimization of the treatment. And that’s what that planning grant
mechanism is for. And so I would really encourage any of you who are thinking of doing clinical
trials to look into that mechanism, contact the staff and discuss how you might use that
mechanism.

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