1
DEPARTMENT OF HEALTH AND HUMAN
SERVICES
FOOD AND DRUG
ADMINISTRATION
CENTER FOR DRUG EVALUATION AND
RESEARCH
JOINT MEETING OF THE
CDER PSYCHOPHARMACOLOGIC DRUGS
ADVISORY COMMITTEE
AND THE
FDA PEDIATRIC ADVISORY
COMMITTEE
Holiday Inn
2
PARTICIPANTS
Wayne Goodman, M.D., Chair
Anuja M. Patel, M.P.H., Executive
Secretary
PSYCHOPHARMACOLOGIC DRUGS ADVISORY
COMMITTEE
MEMBERS
James J. McGough, M.D.
Jean E. Bronstein, R.N.,
M.S. (Consumer Rep)
Philip
S. Wang, M.D. M.P.H., Dr. P.H.
Dilip J. Mehta, M.D.,
Ph.D., (Industry Rep)
Lauren Marangell, M.D.
Delbert G. Robinson, M.D.
Daniel S. Pine, M.D.
Barbara G. Wells, Pharm. D.
Bruce G. Pollock, M.D., Ph.D.
PEDIATRIC ADVISORY COMMITTEE MEMBERS
P. Joan Chesney, M.D.
Deborah L. Dokken, M.P.A.
Michael E. Fant, M.D., Ph.D.
Richard L. Gorman, M.D.
Robert M. Nelson, M.D., Ph.D.
Thomas B. Newman, M.D., M.P.H.
Judith R. O'Fallon, Ph.D.
Victor M. Santana, M.D.
SGE CONSULTANTS (VOTING)
Norman Fost, M.D., M.P.H.
Charles E. Irwin, Jr.,
M.D.
Lauren
K. Leslie, M.D., FAAP
Steven Ebert, Pharm. D.
James M. Perrin, M.D.
Cynthia
R. Pfeffer, M.D.
Robert
D. Gibbons, Ph.D.
Tana A.
Grady-Weliky, M.D.
Richard P. Malone, M.D.
Irene E. Ortiz, M.D.
Matthew V. Rudorfer, M.D.
SGE PATIENT REPRESENTATIVE (VOTING)
Gail W. Griffith
GUEST SPEAKERS (NON-VOTING)
Kelly Posner, Ph.D.
3
PARTICIPANTS
(Continued)
GUESTS (NON-VOTING)
Samuel Maldonado, M.D.,
M.P.H.
FDA
Robert Temple, M.D.
Russell G. Katz, M.D.
PARTICIPANTS (Continued)
Thomas Laughren, M.D.
M. Dianne Murphy, M.D.
Anne Trontell, M.D., M.P.H.
4
C O N T E N T S
Call to Order and Opening Remarks:
Wayne Goodman, M.D. 5
Conflict of Interest Statement
Anuja Patel 6
Opening Comments
Thomas Laughren, M.D. 9
Committee Questions and Discussion 31
Presentation
Diane Wysowski, Ph.D. 152
Committee Discussion of Questions and
Vote 163
Concluding Remarks
P. Joan Chesney, M.D. 402
Wayne Goodman, M.D. 404
5
P R O C E E D I N G S
Call to Order and Opening
Remarks
DR. GOODMAN: Welcome to day two of this
joint two-day session of the
Psychopharmacologic
Drugs Advisory Committee and the
Pediatric Advisory
Committee being held on September 14,
2004, here at
the Holiday Inn in Bethesda, Maryland.
We are convened to address
recent concerns
about reports of suicidal ideas and
behavior
developing in some children and
adolescents during
treatment of depression with selective
serotonin
reuptake inhibitors and other
antidepressants.
Our goal is to gather
information from a
variety of sources and perspectives to
help us
understand this complex situation and
ultimately,
to offer the best possible
recommendations to the
FDA.
Now, I would like to turn the
microphone
to Anuja Patel of the FDA Center for Drug
Evaluation and Research and Executive
Secretary of
this committee to read the conflict the
interest
statement into the record.
6
Conflict of Interest
Statement
MS. PATEL: Good morning.
The following
announcement addresses the issue of
conflict of
interest and is made a part of the record
to
preclude even the appearance of such at
this
meeting.
The topics to be discussed today
are
issues of broad applicability. Unlike issues
before a committee in which a particular
company's
product is discussed, issues of broader
applicability involve many industrial sponsors
and
products.
All Special Government
Employees and
invited guests have been screened for
their
financial interest as they may apply to
the general
topics at hand.
The Food and Drug Administration
has
granted particular matter of general
applicability
waivers under 18 U.S.C. 208(b)(3) to the
following
Special Government Employees which
permits them to
participate fully in today's discussion
and vote:
Jean Bronstein, Dr. Joan Chesney, Dr.
Wayne
7
Goodman, Dr. Lauren Marangell, Dr. James
McGough,
Dr. James Perrin, Dr. Bruce Pollock. In addition,
Dr. Philip Wang has been granted a
limited waiver
that permits him to participate in the
committee's
discussions. He is, however, excluded from voting.
A copy of the waiver statements
may be
obtained by submitting a written request
to the
Agency's Freedom of Information Office, Room
12A-30
of the Parklawn Building.
In addition, Dr. Judith
O'Fallon and Dr.
Victor Santana have de minimis financial
interests
under 5 CFR Part 2640.202 that are
covered by
regulatory waiver under 18 U.S.C.
208(b)(2).
Because general topics impact
so many
entities, it is not practical to recite
all
potential conflicts of interest as they
apply to
each member, consultant, and guest
speaker.
FDA acknowledges that there may
be
potential conflicts of interest, but
because of the
general nature of the discussion before
the
committees, these potential conflicts are
mitigated.
8
With respect to FDA's invited
industry
representative, we would like to disclose
that Dr.
Dilip Mehta and Dr. Samuel Maldonado are
participating in this meeting as industry
representatives acting on behalf of
regulated
industry.
Dr. Mehta is retired from Pfizer and Dr.
Maldonado is employed by Johnson &
Johnson.
With respect to all other
participants, we
ask in the interest of fairness that they
address
any current or previous financial
involvement with
any firm whose product they may wish to
comment
upon.
Thank you.
DR. GOODMAN: Thank you, Anuja.
We will be starting off this
morning with
a presentation from Tom Laughren who will
give us
an overview and also pose the questions,
the five
questions to this committee.
Following his presentation, I
would invite
questions. I also think it would be a good time
before we get into the meat of our
discussions to
ask representatives from the FDA
questions, to
9
further interrogate some of the data that
was
presented yesterday.
Before we get into the actual
discussion
of the questions, I would like us to
think of the
questions that were carried over from
yesterday,
pose those, and then we will take a short
break,
reconvene and start the process of
discussing the
questions.
Is that clear? Okay.
Tom, are you ready?
Opening Comments
Thomas Laughren, M.D.
DR. LAUGHREN: Good morning.
I would also
like to welcome everyone back to the
meeting today.
I would like to do a couple of things in
my few
minutes here.
First of all, what I want to do
is to
briefly review what I think are some of
the key
findings from Dr. Hammad's presentation
yesterday,
so that you have these in mind as you are
considering the questions before you.
Then, I want to talk a little
bit about
10
what I think the data mean and talk about
what some
of the regulatory options are as you are
considering our questions, and then I
want to go
over the questions and the topics again.
These are the 24 trials that we
are
considering. Again, 16 of them were in
major
depression, and the other 8 trials were
in several
various psychiatric disorders - OCD, GAD,
1 in SAD,
and 1 in ADHD.
Again, just for summary, I
think these are
the three contributions that the Division
made to
this effort. Again, we went to a lot of
effort to
make sure that we had complete case
finding. With
the help of Columbia, we accomplished
what I think
is a rational classification of these
events, and
we both obtained and included patient
level data in
our analysis of the suicidality data
again to try
and understand some of the differences
both between
trials, within programs and across
programs.
These are the outcomes that we
looked at
again. The focus of the analysis was on
two areas,
the suicidality event data and also on
the suicide
11
item data.
For the event data, could we
have the
other slide up that we had running
yesterday? Our
primary endpoint, as you recall, was the
combination of suicidal behavior and
ideation,
Codes 1, 2, and 6, where 1 was suicide
attempt, 2
was preparatory actions, and then 6,
suicidal
ideation.
So, that was our primary
endpoint, but we
also looked at secondary endpoints, at
suicidal
behavior, in other words, Codes 1 and 2,
and then
suicidal ideation, Code 6, and then for
our
sensitivity analysis, we looked at this
larger
outcome including 1, 2, and 6, but also
adding in 3
and 10, where again, 3 is self-injurious
behavior
where the intent is not known, and 10 is
not enough
information. Again, these are the cases where
there is injury, but it is not possible
to tell
whether it's self-injury or other injury.
With regard to the suicide item
data, we
looked at two measures about worsening
suicidality
on that item or emergence, and these
again are the
12
cases where the patients are normal at
baseline and
have some increase during the trial.
In terms of our analytical
plan, the major
focus was on doing risk ratio analyses,
both for
the suicidality event data and for the
item data.
In both cases, we looked at individual
trials, as
well as for the event data, we looked at
various
pools.
We looked at both by drug, we
combined all
the SSRIs, MDD trials as a group, we
looked at all
of the other indications combined as a
group and
also did one pooling which included all
24 trials.
For the item data, we looked again at
individual
trials and then a pooled analysis over
all trials.
Dr. Hammad put a lot of effort into
again
trying to explain the differences that we
were
seeing between trials within programs and
across
programs, and I just want to spend a
couple of
minutes talking about exactly what he
did.
He looked for confounding
within trials
using both the univariate approach and a
multivariate approach. There were a total of 17
13
covariates that he looked at. He was not able to
find any evidence for important
confounding in that
search.
He also did stratified analysis
to explore
for effect modification. The three variables that
he looked at were age, gender, and
history of
suicide attempt or ideation, so
basically, what he
did in each of these is to stratify on
these
variables within trials to look to see if
there was
basically an interaction.
Again, he did not find any
evidence for
that, so basically, what that means is
that on
these variables, you find the signal both
in
children and adolescents, you find it
both in males
and females, and you find it both in
those with and
without history of suicide attempt or
ideation.
Finally, he looked at 12 trial
level
covariates, again, as an attempt to try
and explain
the differences across trials using a
meta-regression approach. Again, that approach was
not able to explain the variability.
Now, I would say that one of
the problems
14
in doing these kinds of explorations is
that there
is very limited power, you have a very
small number
of events. When you use an eyeball approach to the
data, you can't help but thinking that
trial
differences might have made a difference.
I just use the TADS, the fluoxetine
situation as an example. The company had three
trials.
There was no signal coming from those
three trials. If you look at the careful screening
that was done to obtain the patients for
those
samples, and the exclusions of patients
with prior
histories of treatment resistance, and so
forth,
and then you look at the TADS sample,
which is many
ways was probably more representative of
the
community of patients who actually get
treated,
there is quite a difference. Again, as you recall,
in the TADS trial, you see quite a
striking signal
for suicidality.
So, even though quantitatively,
we weren't
able to tease that out and to explain the
differences using various quantitative
approaches,
it is hard to think that that may not
have made a
15
difference.
In my next three slides, I am
going to
present very briefly some of the data.
What this slide is, is
presenting the risk
ratios for various poolings. So, in this column,
you have the risk ratios on our primary
endpoint,
which was suicidality ideation or
behavior, 1, 2,
and 6.
In the second column, you have
this
expanded sensitivity analysis, 1, 2, 6,
plus adding
3 and 10.
The first row is all trials, so this is
a pooling across all 24 trials. In the second row,
you have the pooling of the 11 trials
with SSRIs
and major depression.
Now, there are two things I
want you to
notice about this slide. First of all, in every
case, the risk ratios are around 2. They range
from 1.7 to 2.2, but they are sort of in
the
vicinity of 2.
Secondly, if you look at the
confidence
intervals on these risk ratios, in every
case, it
does not include 1, so in that sense, it
is a
16
statistically significant finding. So,
this is the
pooled data.
What I have given you in this
slide are a
different set of poolings. Here, what I am doing
is
pooling the individual depression trials in the
7 programs that looked at depression, and
these are
the 7 programs listed here. Every row is a
separate depression program.
What I have given you here,
first of all,
is the outcome on our primary endpoint a
combination of 1, 2, and 6. I have also given you,
in the second column, the outcome on
suicidal
behavior, and in the third column, the
outcome on
suicidal ideation.
There are a couple of things I want you
to
notice about this slide. First of all, in every
instance where we have events, and we had
no events
for Serzone, but in the other 6 instances
where you
have events, the risk ratio is always
greater than
1.
Now, I want to turn to trying
to tease
apart where that overall effect is coming
from if
17
you break it apart by behavior and
ideation. Dr.
Hammad made this point yesterday, in
three cases it
appears as if the overall effect is
coming from
behavior, in three cases it looks like it
is coming
from ideation.
So, if you look at Celexa, here
is the
risk ratio for behavior, 2.23. There is nothing
happening for ideation.
If you look at Paxil, again, it
looks like
it is coming mostly from behavior.
If you look at Prozac, it looks
like it is
probably coming more from behavior than
from
ideation.
For Effexor, there is a signal
coming from
both, but it is clearly coming more from
ideation.
Here, the confidence interval is almost
significant.
For Remeron, it is all coming
from
ideation, and from Zoloft, there is
nothing
happening for behavior, it is all coming
from
ideation.
I am not sure what this
means. As Dr.
18
Hammad pointed out, this may simply be a
small
numbers problem, but we are not seeing a
consistent
finding in terms of where the overall
effect is
coming from.
Finally, what I have given you
in this
slide is the data from the individual
other 8
trials in non-MDD indications. As you get into
these trials, the number of events you
are dealing
with is very small, and just to
illustrate that, I
have put the actual number of events in
this slide.
So, in each of these
parentheses, the
first one is the number of events for
drug, and the
second one is for placebo. So, you can see the
small number of events that we are
dealing with.
If you recall from the previous
slide, for
Effexor, we were seeing quite a strong
signal for
major depression. These are two GAD studies.
There is nothing at all happening here.
For Luvox, again, Luvox was only
studied
in OCD, there was no depression
trial. Just one
study in depression, only two
events. They were
both happening in the drug group.
19
For the two non-MDD Paxil
studies, one in
social anxiety, one in OCD, again, small
numbers of
events, but in both cases, they were
happening in
the drug group.
The same for the Prozac OCD,
just one
event, but it happened in the drug group.
No events for Wellbutrin.
For Zoloft, this is the only
case where
the one event is happening in placebo,
and not in
drug.
It is hard to know what to make
of all of
this, although the one thing that you
can't help
noticing is that even though there are a
small
number of events, where events occurred,
they most
happen on the drug side.
Just to summarize these data,
again, if
you look at various pooled analyses, the
risk
ratios hover around 2. They range from 1.7 to 2.2.
In all cases for those poolings, it
appears to be a
significant finding.
The signal appears to be coming
mostly
from major depression, although perhaps
not
20
exclusively. Despite those findings, there still
are these inconsistencies in this risk,
both across
trials, within programs and across
programs.
On the other hand, my view
is--and there
isn't necessarily one consistent view
coming out of
FDA on this--but my view is that this is
a
reasonably consistent signal for
risk. You are
seeing it in seven of nine programs. We don't see
any events in Wellbutrin. On the other hand,
Wellbutrin was only studied in ADHD, just
one
trial.
There is no signal coming from
Serzone,
which was studied in major
depression. I am not
sure if that means that Serzone is free
of risk or
it simply may mean that the events, the
ascertainment in those programs was not
good enough
to pick them up. I don't know the answer.
One other point that Dr. Hammad
made
yesterday, that I want to return to, is a
way of
thinking about this risk is in terms of
risk
difference, and if you look over all
these trials
and estimate what the risk difference is,
that is
21
the difference in the risk between drug
and
placebo, so you are subtracting the
placebo risk
from the drug risk, it is in the range of
2 to 3
percent.
What that means is that again,
out of 100
patients treated--this is short term now,
short-term treatment--you can expect 2 or
3 out of
that 100 will have some excess of suicidality
above
and beyond what would be in the
background that is
due to drug.
As a clinician, what you have
to do is to
balance that risk against the perceived
benefit.
The problem here, of course, is that we
only have,
at least from FDA's standpoint, a
demonstration of
benefit for Prozac, but if you take the
TADS trial
as an example of benefit, there, you can
look at
the benefit difference, and the benefit
difference
in the TADS trial, difference between
drug and
placebo in percent of responders, using
that as the
measure of benefit, it is about 25
percent.
Again, you can interpret that
in the same
way, so that if you look at 100 patients
who are
22
treated with fluoxetine, you can expect
that about
25 out of 100 will have that benefit if
you are
looking at response as the benefit.
So, you balance that against
the risk,
which again in that trial, the risk
actually was
greater than the 2 percent, it was
probably more on
the order of 7 percent, but you balance
that risk
against the benefit. That is the kind of calculus
that a clinician has to do.
Finally, as was pointed out,
there were no
completed suicides in any of these
trials.
Again, we did not see the same
signal in
looking at the item data. One exploration we tried
to do to see if that could be explained
by patients
dropping out, and unfortunately, that was
not an
explanation. The analysis of completers did not
show really any difference from the
analysis of the
patients who dropped out.
So, how should these findings
be
interpreted? I think that this is an indication
that there may be some increased risk for
suicidality during short-term treatment,
and I
23
think this is probably a class
effect. Again, you
are not seeing it in every drug that we
looked at,
Serzone and Wellbutrin being the two
exceptions,
but I think there is enough here to suggest
that
this is probably a class effect.
The signal appears to be most
compelling
in major depression. It may not be limited to that
population, but again we are left with
this very
unusual variation in the signal across
trials,
within programs and across programs that
we have
not been able really to explain.
What I want to do next is to
talk about
what some of the regulatory options are,
and I
first want to talk about possible
labeling changes.
As you recall, we already made
a fairly
major change to labeling back in March,
and all of
those changes have now been
implemented. There is
a fairly prominent warning statement that
directs
the attention of prescribers to this
possible
event.
Now, that language as it
currently is
written suggests that causality has not
been
24
established.
One thing that might be done to
modify that, if there is agreement on
this, we
could say that causality has now been
established
for this risk in pediatric patients.
In addition to that, we could
go beyond
that and provide specific suicidality
findings in
the labels for different products. We could also
provide more specific information about
the
efficacy findings for specific products
in that
language.
There are other things to talk about in
terms of that warning statement including
things
like bolding language or putting black
boxes.
These are all options that are on the
table.
The other option that you need
to think
about, and you heard many yesterday in
the open
session ask us to do this, you can think
about
contraindications. The one thing I want to point
out is that in this country, for our
label, a
contraindication means never. It means that that
drug will never be used in treating these
patients,
it is not an option.
25
The other thing I want to point
out is
that the term
"contraindication" has different
meanings in different regulatory
settings. In some
settings, it does not mean never. If you read the
fine print in the UK, for example, there
is a
suggestion that specialists may still use
that
drug.
So, you need to keep that in mind that in
this country, a contraindication means
that that
drug is never an option.
In addition to labeling
changes, there are
some other obvious actions that we can
and almost
certainly will take. Our plan at present is to
write a medication guide. This is
basically
labeling which ideally would be attached
to the
medication when it is prescribed in unit
of use
packaging.
In addition to that, we will undoubtedly
have another public health advisory when
we decide
on what needs to be done, and we will try
and
communicate these findings to our
partners.
Now, what I would like to do
again is to
quickly go through the questions and the
topics.
26
The first topic is again we would like to
have your
comments on our approach to classifying
these cases
and
to our analysis of the data.
One of the questions for which
we really
need to have you vote on is do you feel
that the
suicidality data from these trials
support the
conclusion that any or all of these drugs
increase
the risk of suicidality in pediatric
patients.
If the answer to that question
is yes, to
which of these nine drugs does this
increased risk
apply, in other words, is this a class
effect for
all antidepressants, does it apply to
certain
subclasses within this broader class, or
to
specific drugs?
If this is a class risk or if
it applies
to certain drugs, how should this
information be
reflected in the labeling for each of
these
products, and what, if any, additional
regulatory
actions should the agency take?
Finally, there is this question
about what
additional research is needed to further
delineate
the risks and the benefits of these drugs
in
27
pediatric patients with psychiatric
illness.
At our last meeting, I
suggested one type
of study that you might think about, and
I am going
to make that suggestion again, because we
think
that this is one study that might get at
one of the
deficiencies here, and that is, not only
do we not
have enough information about short-term
benefit,
we also have little information about
longer term
benefit or risk.
One way of getting at longer
term benefit
is the randomized withdrawal study. Basically, the
way the study works is that patients who
are
responders or appear to be responding to
treating,
at some point in the course of treatment,
are
randomized to either continue on drug or
randomized
to placebo, and one looks at time to
relapse as the
outcome.
Now, I know there are concerns
about that
design. You know, one concern is the
ethical issue
of taking patients off a medication when
they
appear to be responding. I agree that is
a concern,
but I think there is a way of dealing
with that.
28
The usual randomized withdrawal
trial is
done after too short a period of time on
treatment.
I mean typically, they are done now after
12 weeks
or so of treatment. That is too soon. No
clinician would take a patient off of one
of these
medications at that point in time.
On the other hand, at some
point in the
course of treatment, whether it is six
months or
nine months or a year, it seems to me
that it is a
reasonable question. At some point, you reach
equipoise where the clinician has to ask
the
question, well, is this long enough, you
know, is
there any benefit in continuing the treatment
beyond this point in time.
Now, that is a much harder
study to do, to
keep patients on treatment for nine
months or a
year before you randomize them, but that
would be a
way of answering that important question
of whether
or not there is continuing benefit beyond
that
point in time.
The other concern that has been
raised
about these trials is the issue of
distinguishing
29
between withdrawal symptoms and
relapse. Again, I
agree that this is a reasonable concern,
but I
think there is also a way of addressing
that.
In clinical practice these
days, these
drugs are tapered. One doesn't stop them cold
turkey.
I think that could also be part of that
design, and that could address that
issue. So,
that is one thing to think about.
Before I end, I want to leave
you with two
thoughts.
We clearly have an obligation at FDA to
inform clinicians and patients about the
risks that
are associated with these drugs, and we
take this
obligation very seriously.
Along those lines, I just want
to point
out that our current regulations do not
require the
same level of certainty with regard to
safety in
terms of causality as is required for
efficacy. In
other words, we can issue warning
statements with
somewhat lesser certainty about causality
than is
required to support a claim.
Secondly, as I have pointed out
several
times, the lack of efficacy data in this
setting
30
for most of these drugs needs to be part
of this
discussion. On the other hand, and I am not making
your job easy, please bear in mind that
depression,
whether in adults or children, is a very
serious
illness that is associated with morbidity
and
mortality quite apart from whatever role
antidepressants might have.
As was pointed out yesterday,
this is the
major cause of death in this population,
the
depression itself, so please bear that in
mind.
I have very profound respect
and gratitude
for the clinicians who are out there on
the front
lines still willing to take care of these
patients
despite what has become a very
controversial and
difficult environment.
I hope that as we discuss these
issues and
make a decision, that we not make it
impossible for
them to practice medicine.
Thank you.
DR. GOODMAN: Thank you, Tom, for a cogent
and clear presentation.
I would like to ask committee
members if
31
they have any questions of Tom.
Committee Questions and Discussion
DR. FOST: This is for Tom or anyone else
who has a handle on the numbers. I know there is
no precise answer to it, but it would be
helpful to
me to just hear you or someone else,
maybe Dr.
Shaffer, if he is still here and is
allowed to
talk, this question.
Suppose there were no SSRIs,
suppose they
were contraindicated, that is,
prohibited,
approximately, let me just ask the
question about
suicides, about completed suicides, and I
understand there is no suicides in the
FDA data,
but based on everything that we know,
approximately, would there be more
suicides, fewer
suicides, or the same amount if there
were no SSRIs
in children?
DR. TEMPLE: There is not going to be any
way to answer that, in part because you
can't do
rigorous studies of the kind that would
answer
that.
No one is going to let you not treat, not
institutionalize, et cetera, someone who
is getting
32
worse and worse, and it would require
long-term
studies presumably against no treatment,
and it is
not easy to figure out how anybody is
going to do
those.
So, you are left with the kind
of data
that people have pointed out is always
uncertain,
the data on suicide rates and whether
they are
going up or down, so it is very hard to
answer that
question.
There were no completed
suicides in the
pediatric data, so that doesn't give you
a clue.
You can form your own judgment about
whether
increased suicidal behavior or thinking
is going to
lead to suicides in a certain fraction of
cases.
It is hard to imagine that it couldn't,
but you
don't know what that ratio is.
The success rate of suicidal
attempts is
relatively low. I gather it is higher in males
than females, but I don't think there is
going to
be ways to put numbers on that.
You have to form your judgment
about
whether you think the overall decline in
suicides
33
has got something to do with therapy or
has
something to do with other aspects of
life in the
United States, and nobody can give you a
firm
answer to that, as Dr. Wysowski said and
as others
have said. So, it is very hard to answer that
question.
Certainly, some of the people
who spoke
yesterday, some of the treating
physicians were
quite sure that they were helping people
with the
drugs, and you heard families who said
that their
relatives were made much worse by the
drugs.
Putting numbers on that, though, isn't
feasible
based on the data we have.
DR. FOST: A related question. To those,
Dr. Shaffer and others who note a decline
in
suicides in the United States, in
parallel with the
increased use of SSRIs, and let's just
say which
should be an increase in suicidality,
suicidal
ideation due to SSRI, what is the
hypothesis there,
that there is fewer suicides, but more
suicidal
ideation?
That is what the data seemed to suggest,
and I am confused by that.
34
DR. TEMPLE: Can I make another comment?
The studies you are looking at are all
the
short-term studies. As Tom was pointing
out, we
have none of the long term sort of
relapse
prevention data. It seems entirely possible that a
drug could be causing early suicidality,
but once
you are over that period, it prevents
relapse,
which could have an impact.
You know, there is just
literally no way
to sort that out with present data. I mean it has
never been my thought that any benefit
these drugs
have consists entirely of their treatment
of the
acute episode, because in adults anyway,
we have
lots of data showing that the likelihood
and timing
of relapse is affected by continued
therapy.
As Tom said, most of those studies go
earlier than you would like to do in a
pediatric
population, because they consistently
show that
quite reliably. Maybe that is where their
importance is, it is very hard to know.
DR. GOODMAN: Dr. Pine is next.
DR. PINE: I have a question about some of
35
the regulatory options. In thinking both about a
number of the comments that were made
yesterday, as
well as your comments at the end about
how
difficult the decision that we will have
today,
related at least in part to the dearth of
data that
we really need.
Are there any options from a
pharmacovigilance standpoint as far as
regulatory
actions that might increase the degree to
which we
are focusing over the next time period on
the
emergence of these events or bring, you
know, new
data over the next months to years based
on a
regulatory action?
DR. KATZ: There is the mechanism of Phase
IV requirements that say we can impose
requirements
on sponsors to do various studies in
Phase IV and
postmarketing environment. The question would be
what those studies would look like. I think that
is the question.
There are other obviously
entities, the
NIMH and others who were set up obviously
to do
large trials, and again the question is
what would
36
those trials look like. You could do I suppose
large long-term, and again, you have
heard, I
think, a lot of people say that there is
a need for
long-term data.
I suppose you could do
long-term
comparative trials, you can't do
long-term
placebo-controlled trials, so other than
the sort
of randomized withdrawal design I think
that Tom
talked about.
So, there is a mechanism to
require
studies.
DR. PINE: I guess I am not so much asking
about studies, and this maybe is a bit of
an unfair
analogy, but in New York, for example, as
well as
other states, whenever you write a
prescription for
a psychostimulant, there are a whole host
of
procedures that kind of go with that,
that are
designed to allow monitoring of the use
of
psychostimulants and the associated
effects.
Is there any--again, I realize
I am
thinking a little bit out of the box--is
there any
form of, I don't know, computer based or
monitoring
37
system that might give us a better handle
on how
many of these events are actually
happening in
regular treatment?
DR. TEMPLE: ODS should comment on that,
but it is worth just looking at, say, the
study Dr.
Jick tried to do. There isn't any
no-treatment
group in that. He is just comparing the risk with
one group of drugs with another, and you
can
definitely do studies like that, but if
you tried
to compare treated people with untreated
people,
there will always be the concern of
whether the
groups are fundamentally different, a
very
difficult problem because people are
treated.
There might be environments in
which
treatment is not so common, where there
is less
likelihood to treat. Maybe in those environments,
you could do something like that, but
Anne wanted
to talk.
DR. TRONTELL: Just to expand briefly, you
are talking about using observational
data as Dr.
Temple pointed out, where you don't have
a control
group, and although you might register
patients, we
38
have seen even in clinical trials that we
have been
discussing this past day, that the issue
of
ascertainment of these events is very
complicated
when you actually have a clinical trial
mechanism
in place to capture those events.
The other challenge that you
face with
observational data, because people don't
receive
the drugs randomly, there is a phenomenon
called
"confounding by indication," in
fact, some of your
sicker patients you might presume are the
ones who
are getting the medication.
We try and control for that,
but it is
very complex. I think the better option is to
think of some systematic way, and then
you are in
the realm of studies, as Dr. Katz was
saying.
DR. MURPHY: I just wanted to follow up on
one last thing. Because we already know that using
the system we have now for follow-up
post-exclusivity because it is already
mandated
that we do one-year reporting once these products,
whether they are approved or not, so we
are looking
at all-use.
39
We do look at that and we
report that, and
we know that that is not going to inform
us, you
know, to answer the questions we need to
answer,
because of all the things that will
impact that
reporting.
DR. GOODMAN: Dr. Temple.
DR. TEMPLE: I just wanted to mention one
related, but not quite on-point
matter. We talked
yesterday about concern that the studies
that had
been done to gain exclusivity might have
been not
as good as we would like.
We weren't particularly talking
about the
design of the studies, which we think is
okay, but
let's say the approach to them. Maybe there was
too much of a rush, and so on. If we were to put
out a written request now, it would be
one that
required a third arm to the study,
namely, a Prozac
arm, because we know that Prozac can be
shown to be
effective.
So, the study wouldn't count
unless it had
been able to show that it had what we
call "assay
sensitivity," the ability to tell
effective drugs
40
from ineffective drugs. We couldn't do
that before
because there wasn't anything at the time
we wrote
those requests that was known to be showable
in
children, but now there is. There is three studies
that all seem to show something.
So, we should have much better
information
about what the pediatric population does
in future
requests.
That doesn't help the present
discussion.
DR. MURPHY: I wanted to address that
issue again, too, because I think I want
the
committee to be very clear on the fact
that the
Agency tells the company very clearly the
type of
studies that need to be done.
We do give them, you know, a
broader
picture of the number of patients. We tell them
what we know will be the minimum, and, in
general,
I think Tom would agree that most of
these studies
have come in with the numbers in each arm
that we
have seen in other studies where they
have shown
effectiveness.
So, the point here being that
we do have
41
control over the types of trials that are
done, the
number of patients, and the
monitoring. However,
because there is a template up on your
web that
basically tells you what we ask for in
depression
trials.
When you look at what the
safety is, as
has been pointed out many times, these
trials were
not set up to answer that question. So, I think it
is those kinds of issues that we would
like to hear
more about today. As Dr. Temple said, it is how
better to do these trials in the future.
Thank you.
DR. GOODMAN: Thanks for that statements,
Dianne. I just want to make sure I
understand it
completely.
I think what you are saying, that if the
conditions had been different at the
time, that is,
that the drug company was required to
show, not
only have a study, but a study that was
positive.
Then, the design would not have been any
different,
the sample size would not have been any
different
under those circumstances than the ones
that
42
existed at the time.
DR. MURPHY: I think what we are saying,
that for the trials that we designed,
they were the
same for the one that did show some
effect, which
is Prozac, as those that did not, and
that what we
don't know is if a company is putting a
trial
together, and let's say we said that they
had to
have 300 patients to get their
exclusivity, but for
other reasons they really wanted this
product
approved, and they felt the enrollment
was not
going the way that they needed, would
there be some
other push within that company to then go
out and
get more patients, so that their
enrollment would
be better versus an exclusivity where all
they had
to do was meet that criteria.
I am making that number
up. I think the
issues that people were trying to get at
is that is
there a difference that affects behavior
when you
just know you have to do certain things
versus you
have another goal, which may be approval.
DR. GOODMAN: Dr. Temple.
DR. TEMPLE: The requirement for a third
43
arm in evidence of assay sensitivity
leaves it up
to the company to decide how they are
going to do a
successful study. They can look at the available
data on Prozac and say, oh, here is the
number I
need, here is the kind of patients I
need. That
succeeded in those three trials.
They would then know that the trial would
have to be one that can show the
difference between
Prozac and placebo. That doesn't mean their drug
has to show a difference between drug and
placebo.
That would be determined by the
results,
and there is no obligation that the drug
be
successful, but we would at least know we
had a
study that was capable of detecting
effective drugs
and distinguishing effective drugs from
ineffective
drugs.
That would then become a
requirement for
meeting the terms of the written request
because
they would have to show that they had an
adequate
study.
Before there was an effective drug, there
was no way to do that. You couldn't tell whether
the study was a good study or not.
44
DR. GOODMAN: Dr. Marangell.
DR. MARANGELL: If I could go back and
address the question of what would the
hypothesis
be for long term, certainly, in the
absence of
data, there is some degree of
speculation. I do
have a question directly to the FDA. Is it okay if
I respond?
I think the number one
hypothesis would be
in the short run when you have depressed
patients
who are not yet stabilized, you may see
an
increased risk, and you do see certainly
in this
population an increased risk of
suicidality.
I imagine that what we would
see with
longer term data is a substantial
decrease in
suicidality over time, and that is what
we are
inferring from the cohort and the
epidemiologic
data.
I think that clinically makes sense, as well
as mechanistically makes sense.
The question for the FDA, can
you give us
a sense, I mean do we feel confident that
we
actually have all the available studies
now in both
children, adolescents, as well as in
adults, and
45
what is the FDA policy on requiring
review of those
studies including negative studies, when
do they
come to you and when do they become publicly
available?
DR. TEMPLE: Well, let me start, others
can comment. When you submit to us an application
to change the labeling, to add a claim,
say, for
pediatric use, you are clearly obliged
under the
law
to provide every study, successful ones,
unsuccessful ones, things that were
interrupted,
and so on.
As far as we know, we are
getting all
those studies. Of course, if there were something
that were done that we didn't know about,
well,
then, we wouldn't know about it, but as
far as we
know, we are getting them all.
So, most of the pediatric
submissions to
us were associated with labeling requests
or
something like that, so as far as we
know, we have
all those data.
Dianne can tell you what is
required under
the best BPCA, and I think there, too,
they have to
46
provide them. We have no rule that affects whether
people have to publish results. Congress is
considering that, so are the journals and
everybody
is talking about that.
Under BPCA, however, when we
grant
exclusivity, we provide summarized results,
and we
have done that for the drugs where the
written
requests were written after the BPCA, and
we have
gone back and asked the companies for
permission to
summarize our analyses for all of the
others where
it wasn't totally clear whether we could
do it or
not.
So, the summarized result, that
is not the
same as a complete study report, the
summarized
results are now available publicly on all
of those.
I am sure between PhRMA's commitment to
provide a
registry between the journals insistence
that they
will get a registry, between
congressional
interest, I am quite confident that there
will be a
change in the way things get published.
DR. MURPHY: The only thing that I could
add to that is that for the committee,
for the
47
routine practice within FDA, if a company
submits
an application, we review it, the studies
are
negative, there is no public
acknowledgment of that
unless the company for some reason wants
to make
that knowledge public. We are not allowed to
comment on that.
Now, under BPCA, it said, it
has a
disclosure section that says you, FDA,
will
publish, as Dr. Temple is referring to,
the
summaries, the medical and pharmacology
summaries
up on the web--make them public, and actually,
we
have chosen to do that on the web--and we
have done
that.
One of the issues that has
happened is
that between the enactment of the new
legislation
and the old legislation, legally, things
were
considered issues under the old
legislation, so
even though the studies came in, we had
to reissue
all those written requests to be able to
say they
now were subject to this new mandate.
So, what again Dr. Temple was telling
you
is that unfortunately, many of the
antidepressants
48
came in, in that period when we had not
yet issued
that letter, but despite that, we have
asked the
sponsors to allow us to put those summaries
up, and
they have given permission to do so.
That is why yesterday we said
up on the
web now are the summaries. Again, this is not the
data.
There is variations in, you know, some
medical officers will put in more
information than
others in how much data is in these
summaries, but
they are up now, publicly available.
DR. MARANGELL: Is that true for adults,
as well?
DR. MURPHY: No, adults are still under
the same standard. In other words, if the study is
negative, we don't talk about it.
DR. MARANGELL: So, as an example, if an
antidepressant manufacturer did a study
in a new
indication for a drug that is currently
available,
found increased risks of suicidality, no
one would
be under any obligation to make that
public?
DR. MURPHY: That is a different issue.
DR. MARANGELL: But that is the question.
49
DR. MURPHY: The issue is safety, and the
Agency always has the ability to make
public safety
issues that arise.
Bob, do you want to say anything else
about that?
DR. TEMPLE: We consider, for example, if
someone with an antidepressant comes in
for, I
don't know, obsessive compulsive disease,
and we
don't buy it, we do not make those data
available,
they are considered confidential
commercial
information. Obviously, a lot of the people, a lot
of the public doesn't like that
approach. We think
that is what we are required to do. I can't
comment on that, I am not the lawyer
here.
However, companies have a
separate
obligation for drugs that are marketed to
report
serious and unexpected, and any serious
adverse
reactions to us, and to do so promptly. A finding
of increased suicidality where that was
not known,
clearly meets that test, and they would
be obliged
to report it to us. If we then thought that was
true, we would add it to the label or do
whatever
50
we are supposed to do.
So, safety data meets a
different
standard.
A new carcinogenicity study or
something, those do have to be reported
to us.
Other studies have to be reported in the
annual report, but they are not
necessarily
reported in detail, and not that much is
necessarily made of them, and they do not
necessarily become public.
DR. GOODMAN: Dr. Pollock.
DR. POLLOCK: Yes, the serious safety
issue would have to be reported while the
trial is
ongoing to you, right?
DR. TEMPLE: Well, if it arises from a
trial, it has to be. Actually, the requirements
for reporting serious unexpected events
in a trial
are more or less identical to the
requirements
before a drug is marketed. They have to be
reported to us within 7 or 15 days.
A finding from an epidemiologic
study,
there is some judgment involved in
whether that
represents the kind of thing that has to
be
51
reported promptly, but they basically do.
DR. KATZ:
There is also some judgment
involved in whether or not an event is
considered
to be unexpected. So, for example, suicide in a
study of patients who are at risk anyway
might not
be reported to us in real-time, because
it might be
considered to be expected, the blind is
still
intact, you don't know if it's drug or
placebo if
it is in the context of a controlled
trial.
Afterwards, though, when the
trial is done
and analyzed, and it turns out that there
is an
increased incidence on drug compared to
placebo,
that is something we would find out
about.
DR. GOODMAN: Go ahead, Dr. Pollock.
DR. POLLOCK: I actually wanted to explore
your thinking a little bit about the
recommendation
for a maintenance trial. I guess there are a
couple of things. One is if there is this
acute
toxicity that we are concerned about,
clearly, it
doesn't address that because you are
dealing with
the children or the adolescents who have
actually
responded, and then are withdrawn.
52
But I wondered if there was
implicit in
your request for that, a concern that still that
the shorter half-life SSRIs seem to be,
maybe not
statistically, but certainly
qualitatively more at
risk in causing this phenomenon.
I was taking that as implicit perhaps
in
your suggestion, maybe I am
over-interpreting it,
but is there a belief that somehow--I
mean it just
seems more than coincidence that signals
seem a
little bit higher.
I know it has now emerged with
Prozac, but
certainly, Effexor, venlafaxine stands
out at one
end, then followed by paroxetine, and if
there was
kind of an implicit question that you
were asking,
assuming that people are still using
after we are
finished, you know, those medications,
that you can
require that those manufacturers actually
conduct a
serious maintenance trial as part of you
were
saying your Phase IV regulatory
requirement.
DR. LAUGHREN: We certainly, you know,
until we saw the TADS data, were
entertaining the
notion that discontinuation might be one
53
explanation for the bigger signal, the
apparent
signal that we are seeing with Paxil and
Effexor.
The TADS finding certainly
challenges that
notion as a unitary explanation, since
that is the
single trial among the 24 that, by
itself, has a
statistically significant finding for
that signal.
That doesn't mean that the other
explanation isn't
possible.
I mean this could be a much more complex
situation than one might seem at first
glance.
But a maintenance trial is not
going to
answer all those questions. I mean a maintenance
trial is only going to answer the
question of
longer term benefit, but the reality is
that many
clinicians, despite these concerns, are
probably
going to continue to use these drugs, and
we have a
dearth of information about what the
longer term
benefits are. The maintenance trial is one way, I
think, of getting at that.
Now, there is this issue of how
to
interpret emerging symptoms in that setting,
you
know, when you take patients off the
drug. Of
course, the drugs like Paxil and Effexor,
that are
54
known to have a stronger signal for
discontinuation, obviously are a
challenge in doing
that kind of trial, but I think that one
could, as
one does in clinical practice, taper
those patients
to try and address that, and then look
for what
would be considered for relapse.
DR. GOODMAN: Dr. Temple.
DR. TEMPLE: There is another reason to do
randomized withdrawal studies. As everybody knows,
in adults, the failure rate for
conventional
clinical trials of the acute episode is
about 50
percent.
That is, half the trials can't tell drug
from placebo, and that is true even when
you
include a third arm of a drug that is
known to
work.
That appears to be the nature of the beast.
Nobody really has a good
explanation
because if they did, they would fix it,
but we at
least think it has something to do with
the
environment and the discussions that go
on even
informally, even if it is not planned as
part of
the
treatment.
In the randomized withdrawal
setting, the
55
success rate for drugs that are known to
work is
nearly 100 percent. Very few of those
trials ever
fail.
There are at least two
reasons. One, only
people who seem to be doing well are in
the trial,
so they are enriched with a responder
population.
You can make of that what you will.
The other possibility, though,
is that the
environmental things that help people get
better
aren't really there, they are just out
living in
the community, there is nothing nurturing
about it.
They are just back in their usual environment.
So, one of the attractiveness
of these is
to find out whether the drugs actually
provide some
benefit, even in people who seem to be
doing well
on them, which seems an important
question here. I
mean, as Tom has pointed out repeatedly,
the
failure of most of the drugs to show
effectiveness
doesn't mean they don't work. On the other hand,
we don't have evidence that they do work,
and that
is not irrelevant either.
A good way to show that, if they do, is
56
the randomized withdrawal study. At least that has
been the history in adults, so there is a
lot of
attractiveness to it.
DR. GOODMAN: Dr. Chesney.
DR. CHESNEY: Thank you.
I have two
questions. The first one is for Dr.
Murphy and Dr. Temple, and the second for
Dr.
Laughren.
The first question addresses the
exclusivity issue. I feel like in this case, we
bypass the Phase I/Phase II stages that
we would
normally go through with new drugs, so we
never did
do the pharmacokinetic/pharmacodynamic
dose finding
in children that we would have done had
these been
new drugs.
I wondered, I probably should
know this,
but could either of you explain, when we
offer
exclusivity with a new drug, if it is a
new drug to
children, do we require those studies, or
do we
not?
I am sure it is not that straightforward.
DR. MURPHY: We did required
pharmacokinetic studies. Actually, on the
template, we outline three types of
studies. They
57
have to do two randomized, double-blind,
placebo-controlled, acute treatment
trials with
recommendation at six to eight weeks for
safety and
efficacy.
They also are to do a pharmacokinetic
study to provide information pertinent to
dosing of
study drug, and they are to do a safety
study.
So, all of those were asked
for. Now, if
you are asking do we go back and demand
redoing
dose finding again in these, no, they
were not
worded that way. It was said that the PK study
could be a traditional PK or,
alternatively, a pop
PK, and actually, I don't think that the
study had
any other information that would have, in
essence,
told the company that they needed to redo
the dose
finding, if that answers your question.
DR. CHESNEY: So, do we have dose
information on all of these drugs? Do we know what
the usual ranges are, and what excessive
ranges
are, all those things?
DR. GOODMAN: Go ahead, Dr. Katz.
DR. KATZ: I think Tom mentioned this in
one of his slides yesterday. The written requests
58
that we issue now are very different from
the
written requests we issued that probably
generated
most of the trials that we are talking
about here
yesterday and today.
As Dianne pointed out, for
example, in
pharmacokinetics, we gave sponsors the
opportunity
to generate the kinetics in kids based on
so-called
population pharmacokinetic analyses,
which is to
say from data generated in the controlled
trials.
So, it was sort of after the
fact. It was
just what is the kinetics of the doses
you happen
to give in the trials.
In the earlier written
requests, it was
sort of the pediatric drug development
was sort of
tacked onto the adults, in other words,
when the
trials were designed even, the treatment
effect
size, for example, was used to calculate
sample
size was taken from the treatment effect
size seen
in adults. We had no information, even preliminary
information in kids.
So, we didn't have a lot of
preliminary
information in those days that could
inform
59
adequate trial design in this population,
in this
setting.
Nowadays, we ask for different
things. We
ask for formal PK, so we can learn before
the
definitive trial design, what the
kinetics are,
what doses give rise to what plasma
levels. We ask
for dose finding studies, so we can
determine
before we design the definitive trials
what the
tolerated dose range is.
So, the written requests are
much
different now than they were at the time
that the
requests are generated, these data were
written.
DR. MURPHY: Just to reinforce that is
that these were some of the earliest
written
requests that went out, so they really,
as has been
stated, and I think we tried to say this
earlier
on, we are learning.
I mean because of the lack of
prior
research and some fundamental scientific
questions
haven't been answered, we are learning
from the
trials that we have now about how to do a
better
job on designing some of these trials,
but these
60
were some of the very earliest ones that
were
issued.
DR. CHESNEY: Dr. Temple, did you want to
comment on that?
DR. TEMPLE: Well, I just wanted to say
there isn't any pharmacodynamic measure
to allow
you to do what is called PK/PD other than
effectiveness itself. In a lot of cardiovascular
settings, there is at least something you
think
relates to the desired effects, so you
can do
relatively short-term studies and get a
PK/PD
relationship.
Here, your only way to do it is
to insist
that every drug, every study be a dose
response
study, which is of considerable
difficulty. We
have trouble getting really good data
even in
adults actually given the sample sizes
involved,
but there isn't any measure yet. Maybe one of
these days there will be an MRI
measurement or
something, but not yet.
DR. CHESNEY: Well, I don't want to
overstay my welcome, and I do have a
question for
61
Dr. Laughren, but one does wonder about
some of
these children who didn't even express
ideation and
just suddenly, very early on, if they
didn't have
excessive levels. I guess that is one issue I was
getting to.
Dr. Laughren, I wanted to come
back to the
point Dr. Pine was making. I thought Dr.
Reisinger's point in the open session
yesterday was
a very interesting one, which is that you
would
have to undergo some kind of
computer-based
learning program or some kind of program
that
authorized you to prescribe psychoactive
drugs.
Certainly, we have to do
computer-based
CBLs for all kinds of things in our hospitals
and
in other areas nowadays. That had a real
attraction to me, and I guess the
question is what
kind of authority does the FDA have in an
area like
that, can you say that anybody that
prescribes
SSRIs must do a computer-based learning
program on
line, or is that something that the
professional
societies take on?
You offered several options,
black boxes,
62
revised label warning, but is this a
potential
option?
DR. TEMPLE: We can certainly recommend
things like that. Every labeling for a cancer drug
says that this should only be used by
people who
are trained in oncology. That comes with
no
enforcement on our part except that
people may be
anxious about the consequences if they
don't have
that training.
A labeling recommendation is
certainly a
possibility. A step further to limit the drugs to
people who have been given that way,
those are very
iffy questions, and it is not clear
whether we can,
in fact, do that. There would have to be a debate
about it.
There are some examples of fairly
interventionist activities. As you all know, you
can't get clozapine unless you have a
white blood
count, so no blood, no drug.
There are not a whole lot of
other
examples like that, but there are other cases
where
patients must be given a form that lists
what some
63
of the adverse effects might be, and
things like
that.
You have to weigh the risk you are concerned
about with the burdensomeness to the community and
to the medical profession of those kinds
of
interventions.
Putting something in labeling
about what
you should know doesn't carry those kinds
of
concerns, so if something sensible,
suggesting that
people ought to be trained in a certain
way seemed
like a reasonable thing, we could
certainly
consider that.
DR. TRONTELL: I would just like to add on
to Dr. Temple's comments, because the FDA
regulates
drugs, but doesn't regulate the practice
of
medicine, and we walk a fine line in
terms of
dealing with some drug products where we
may feel,
as with clozapine, that only very tight
controls on
prescribing and dispensing and use of the
product
are allowed.
There are a very small handful
of drugs,
they tend to be the exception rather than
the rule,
where training has been required as a
condition of
64
approval.
One product in particular is the drug
product dofetilide, where, in fact,
training is
required for pharmacists or
clinicians. There is a
highly structured way in which that
product can be
used.
Again, those have tended to be
reserved
for situations where we feel the drug
cannot be
safely used without that very high level
of
precaution. It is extremely difficult to put those
in place for products that have already
been
marketed and used by professionals.
DR. CHESNEY: The public sees your role I
think in a much broader perspective, as
we heard
yesterday, and I think that is something
that is
useful to clarify as to where your limits
are. You
mentioned there is a fine line, and I
think that is
what we are all looking for, is where
does your
authority end and that of prescribing
physicians
begin, I guess in a sense.
DR. TRONTELL: I don't think we yet have
an answer. I think we always have the authority of
our agency and hopefully, our ability to
persuade
65
individuals, but I think that the actual
legal
authority to do some of these is a matter
of debate
within and outside of the agency.
DR. GOODMAN: Dr. Nelson.
DR. NELSON: I would like to return to the
topic of the incentives on the part of
industry to
perform well-conducted trials.
There has been a lot of
discussion about
the evolution of the written request and
about the
improvement with three-arm studies and
changes in
the ability to request that, but my
understanding,
I am interested to know if this is
accurate, is
that there is still two potential
linkages that
don't exist that might decrease the
incentive to do
a well-conducted study, and that is,
absent safety
concerns, there is no tie to putting any
efficacy
information in labeling, so that they
receive
exclusivity if a labeling change occurs.
Second, is that there is no
link of
exclusivity to a well-conducted study
unless that
has changed with written request, since I
read them
on the current web site, there is one
asthma study
66
where there was members of the drug group
that had
no drug level, members of the placebo
group that
had measurable drug levels, and the FDA
concluded
that the data was uninterpretable, but
nevertheless, exclusivity was granted.
I am wondering, is that a
problem with the
written request that is now fixed, or is
there
other solutions that would need to be put
into
place, such as legislation, to address
those two,
what I perceive as gaps.
DR. MURPHY: I think there was significant
discussion about how exclusivity should
work,
should it be only if the product is
approved. I
was not privy to those discussions, but I
know they
occurred.
The reason for why it was put
in place the
way it is, I can't give you, Dr. Nelson,
but I can
tell you that one of the explanations I
have heard
is that there was such little data, and
FDA was
given the authority to define the trials,
so again,
as you have heard, we would like to
improve, and we
know we have to learn from what trials we
have,
67
that by providing FDA the authority to
define the
trials, that they hope that the trials
would be,
you know, of the best that they could be,
and that,
therefore, we would learn from the trials
even they
were failed, because that is important
information,
failing is important.
So, I guess what you would say,
you are
asking if, and that is in a number of our
labels,
and that is a whole other discussion, but
in
situations, you know, we know that is the
only
study we are going to get and this is it,
failing
is put, that they failed to show
effectiveness has
been put in the label in a number of
situations,
and certain dosing or safety information.
As I said, about a fourth of
the time, we
are describing, even irrespective of
whether the
study is positive or negative, we are
finding
safety signals, you know, important
dosing
information, and we are able to put that
information in a label.
The intent is that the
information that is
obtained, whether the product is proven
to be
68
effective or not is important, and that
safety
information, et cetera, would be
obtained.
So, that is the best
explanation I can
give you as to why it is set up the way
it is right
now.
DR. NELSON: I understand, but let me
focus my question, I guess. Right now the efficacy
or lack of efficacy data is not in the
existing
labeling that we are discussing, so, for
example,
just to pick one, paroxetine, there is
five
studies, and the pediatric use just says
it has not
been established.
Although that is a true
statement, it is a
bit misleading because many people
interpret that
to mean the studies hadn't been done.
The other question is you could
ask them
to do a three-arm active control study,
but if they
do it badly, do they still get the
money? Even if
they have done it, if they do it badly,
do they
still get the money?
DR. GOODMAN: Dr. Temple wants to respond.
DR. TEMPLE: If the written request says
69
you need to do a three-arm study and need
to show
that the trial has assay sensitivity,
that is, the
ability to distinguish active drugs from
inactive
drugs, and the Prozac arm doesn't beat
placebo,
then, they would have failed to meet the