1

DEPARTMENT OF HEALTH AND HUMAN SERVICES

FOOD AND DRUG ADMINISTRATION

CENTER FOR DRUG EVALUATION AND RESEARCH

JOINT MEETING OF

THE ARTHRITIS ADVISORY COMMITTEE AND

THE DRUG SAFETY AND RISK MANAGEMENT

ADVISORY COMMITTEE

VOLUME II

Thursday, February 17, 2005

8:00 a.m.

Hilton Gaithersburg

620 Perry Parkway

Gaithersburg, Maryland

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P A R T I C I P A N T S

Alastair J.J. Wood, M.D., Chair

Kimberly Littleton Topper, M.D. Executive Secretary

ARTHRITIS ADVISORY COMMITTEE MEMBERS

Allan Gibofsky, M.D., J.D., Chair

Joan M. Bathon, M.D.

Dennis W. Boulware, M.D.

John J. Cush, M.D.

Gary Stuart Hoffman, M.D.

Norman T. Ilowite, M.D.

Susan M. Manzi, M.D., M.P.H.

DRUG SAFETY AND RISK MANAGEMENT ADVISORY COMMITTEE

MEMBERS

Peter A. Gross, M.D., Chair

Stephanie Y. Crawford, Ph.D., M.P.H.

Ruth S. Day, Ph.D.

Curt D. Furberg, M.D., Ph.D.

Jacqueline S. Gardner, Ph.D., M.P.H.

Eric S. Holmboe, M.D.

Arthur A. Levin, M.P.H., Consumer Rep.

Louis A. Morris, Ph.D.

Richard Platt, M.D., M.Sc.

Robyn S. Shapiro, J.D.

Annette Stemhagen, Dr.PH., Industry Rep.

FDA CONSULTANTS (VOTING)

Steven Abramson, M.D.

Ralph B. D\'Agostino, Ph.D.

Robert H. Dworkin, Ph.D.

Janet Elashoff, Ph.D.

John T. Farrar, M.D.

Leona M. Malone, L.C.S.W., Patient Rep.

Thomas Fleming, Ph.D.

Charles H. Hennekens, M.D.

Steven Nissen, M.D.

Emil Paganini, M.D., FACP, FRCP

Steven L. Shafer, M.D.

Alastair J.J. Wood, M.D. (Meeting Chair)

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P A R T I C I P A N T S (Continued)

FDA CONSULTANTS (NON-VOTING)

Byron Cryer, M.D. (Speaker and Discussant)

Milton Packer, M.D. (Speaker only)

NIH PARTICIPANTS (VOTING)

Richard O. Cannon, III, M.D.

Michael J. Domanski, M.D.

Lawrence Friedman, M.D.

GUEST SPEAKERS (Non-Voting)

Garret A. FitzGerald, M.D.

Ernest Hawk, M.D., M.P.H.

Bernard Levin, M.D.

Constantine Lyketsos, M.S., M.H.S.

FDA (CDER)

Jonca Bull, M.D.

David Graham, M.D., M.P.H.

Brian Harvey, M.D.

Sharon Hertz, M.D.

John Jenkins, M.D., F.C.C.P.

Sandy Kweder, M.D.

Robert O\'Neil, Ph.D.

Joel Schiffenbauer, M.D.

Paul Seligman, M.D.

Robert Temple, M.D.

Anne Trontell, M.D., M.P.H.

Lourdes Villalba, M.D.

James Witter, M.D., Ph.D.

Steven Galson, M.D.

Kimberly Littleton Topper, M.S., Executive

Secretary

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C O N T E N T S

Call to Order:

Alastair J.J. Wood, M.D., Chair 5

Conflict of Interest Statement:

Kimberly Littleton Topper, M.S. 5

Interpretation of Observational Studies

of Cardiovascular Risk of Non-steroidal Drugs

Richard Platt, M.D., M.S. 8

Review of Epidemiologic Studies on

Cardiovascular Risk with Selected NSAIDs

David Graham, M.D., M.P.H. 37

Committee Questions to Speakers 89

Arcoxia (etoricoxib)

Merck Research Laboratories

Sponsor Presentation

Sean P. Curtis, M.D. 152

FDA Presentation

Joel Schiffenbauer, M.D. 189

Lumiracoxib

Novartis Pharmaceuticals

Sponsor Presentation

Introduction

Mathias Hukkelhoven, Ph.D. 201

Gastrointestinal and Cardiovascular Safety

of Lumiracoxib, Ibuprofen, and Naproxen

Patrice Matchaba, M.D. 205

Open Public Hearing 236

FDA Presentation (Lumiracoxib)

Lourdes Villalba, M.D. 336

Committee Questions to Speakers 346

Committee Discussion 410

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P R O C E E D I N G S

Call to Order

DR. WOOD: Let\'s get started and welcome

back to another day. We are going to begin as on

the agenda seeing we worked late last night.

A couple of housekeeping things first. As

they say in the movie theater, please turn off your

cell phones. We don\'t have the one that sort of,

you know, spars you into space if you do that, the

ejector seat, but then please don\'t answer your

calls in here, so we don\'t have to hear the

beginning of your conversation.

Kimberly, are you going to read the

conflict of interest? Okay. Go ahead.

Conflict of Interest Statement

MS. TOPPER: The following announcement

addresses the issue of conflict of interest with

respect to this meeting and is made as part of the

record to preclude even the appearance of such.

Based on the agenda, it has been

determined that the topics of today\'s meeting are

issues of broad applicability and there are no

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products being approved. Unlike issues before a

committee in which a particular product is

discussed, issues of broader applicability involved

many industrial sponsors and academic institutions.

All special government employees have been screened

for their financial interests as they may apply to

the general topics at hand.

To determine if any of the conflict of

interest existed, the agency has reviewed the

agenda and all relevant financial interests

reported by the meeting participants. The Food and

Drug Administration has granted general matter

waivers to the special government employees

participating in this meeting who require a waiver

under Title 18, United States Code Section 208.

A copy of the waiver statements may be

obtained by submitting a written request of the

agency\'s Freedom of Information Office, Room 12A-30

of the Parklawn Building.

Because general topics impact so many

entities, it is not practical to recite all

potential conflicts of interest as they apply to

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each member, consultant, and guest speaker. FDA

acknowledges that there may be potential conflicts

of interest, but because of the general nature of

the discussions before the committee, these

potential conflicts are mitigated.

With respect to FDA\'s invited industry

representative, we would like to disclose that Dr.

Annette Stemhagen is participating in this meeting

as a non-voting industry representative acting on

behalf of regulated industry.

Dr. Stemhagen\'s role on this committee is

to represent industry interests in general, and not

any one particular company. Dr. Stemhagen is vice

president of Strategic Development Services for

Covance Periapproval Services, Inc.

In the event that the discussions involve

any other products of firm not already on the

agenda for which FDA participants have a financial

interest, the participants involved and their

exclusion will be noted for the record.

With respect to all other participants, we

ask in the interest of fairness that they address

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any current or previous financial involvement with

any first whose products they may wish to comment

upon.

Thank you.

DR. WOOD: Thank you.

Let\'s go right to the first speaker, Dr.

Platt, who is going to tell us about observational

studies.

Interpretation of Observational Studies of

Cardiovascular Risk of Nonsteroidal Drugs

Richard Platt, M.D., M.S.

DR. PLATT: Thanks. The framers of the

meeting thought it would be useful at this point to

have a discussion about observational studies to

put us all on the same page.

There was a view by some that the

expertise around the table might be uneven and it

would be worthwhile to have some discussion about

some of the basics. It is clear that that is not

the case.

I realize that a number of the people here

have written a book and several of my teachers are

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here, so to that extent, I think we can either make

this a quick discuss or use this as an opportunity

for a real interactive discussion, because there

are some hard questions here and no matter how we

sort we out, we are going to be left with less than

in the way of firm answers than we would like.

I also understand that there is a point of

view that says that there are lies, damn lies, and

observational studies, so part of what I think is

worth doing is using this time maybe to take our

temperature about whether and under what

circumstances we can put weight on observational

studies.

We saw a version of this slide last night

actually in the last presentation about why perform

observational studies at all, because I subscribe

to the general view that all things being equal, a

clinical trial, a randomized trial is more

credible, provides more information than an

observational study.

The problem is all things aren\'t always

equal and so there are reasons to ask what we can

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learn from observational studies.

I think the most important of them is no

matter how well a clinical trial is designed, the

individuals who are recruited and consented to a

clinical trial are inherently going to be different

from the actual population of users, and if we want

to understand how an agent performs among real

users in the way they actually use the drug, then,

I think there is no escape but to look to

observational studies.

Additionally, observational data is by

definition there, so when a pressing question

arises, sometimes observational data is the first

way we can get insight into the relationship

between the drugs we care about and the exposures.

I think in that regard, these studies can

often be thought of as helping us identify the

areas in which it would be most fruitful to invest

in full-blown randomized trials. We will never

live in a world where we are able to do all the

randomized trials we care about.

I know that Charlie Hennekens\' landmark

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randomized trial of aspirin was preceded by, as I

recollect Charlie, a large number of observational

trials, it made you think that it was reasonable to

do those randomized trials, so observational

studies can be useful in that regard.

Finally, when we are talking about trying

to understand effects that are relatively unusual,

we stress even the largest clinical trials. We

talked yesterday about the fact that the most

recent drug approvals have used much larger

populations in the NDA phase than had been studied

in the old days, and yet they are still small

compared to the numbers needed to parse out

relatively small differences.

There are a lot of different kinds of

observational trials. I have listed a few of the

most common. The ones between the lines here are

the ones that are really the subject for discussion

here.

Tom Fleming made the absolutely correct

and somewhat counterintuitive point that it is

often more difficult to do good observational

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studies of relatively common outcomes than rare

ones, and because of that, the group of studies

that I think at least are reasonable to consider

for looking at relatively common outcomes are

case-control studies, nested case-control studies

and cohort studies.

We have examples of each in the materials

that have been handed to us. The study by Kimmel

is a pretty traditional case-control study. The

studies by Ray are cohort studies, as is the Aramis

study. The study by Dave Graham, the Solomon study

are nested case-control studies.

Just as a quick reminder, the

distinguishing feature of cohort studies is the

fact that the study population is defined on the

basis of whether people are exposed to the drug or

not, and then we look forward to what happens to

them. In that way, they are exactly comparable to

clinical trials, with the big difference that the

assignment to drug is not randomized.

The strengths of those compared to

case-control studies are you have a reasonable shot

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at the outset of selecting individuals who are

representative of the group that you are trying to

study, and if you organize the study properly, you

have a reasonably good chance of getting unbiased

exposure assessments.

The weaknesses, particularly of

observational cohort studies is that just because

individuals had the right drug exposure at the

outset, they may change that. You can deal with

that with an intention-to-treat design, but you pay

for a price for that, and in observational studies,

loss to followup is a big problems.

We are particularly plagued by that

because the large majority of the observational

studies we are working in are ones that use

administrative data from one sort of health plan or

another, and individuals move in and out of health

plans, so that it becomes difficult to follow them

over time.

Case-control studies, remember are ones

that start with individuals who have the outcome we

care about, myocardial infarction or myocardial

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infarction and sudden death, and compares them to

individuals who haven\'t had that experience, then,

you look back and ask what their drug exposures

are, the reasons for doing those studies are that

they are, first of all, very efficient studies.

You don\'t have to study thousands and

thousands. You can study as many cases as you find

and a reasonable number of controls, and you can

look back and classify exposure however is most

useful, and that is a very convenient and versatile

feature of case-control studies.

The big weaknesses are that it is very

hard to assure oneself that the cases and the

controls are really representative of the

populations that you care about, and for

conventional case-control studies, for instance,

the study by Kimmel that we are going to look at,

it takes a lot of work to be sure that people who

know what they have already experienced an MI don\'t

differentially report their exposure to the drugs

that we care about.

That can be for all sorts of reasons and

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it might not even be wrong, but the individual who

has had an MI and might be just thinking harder

about whether he or she had been exposed to a drug

that we care about.

By the way, nested case-control studies,

for instance, the study that David Graham did is a

hybrid that really, in my view, draws many of the

strengths from both designs, that is, because

nested means the case-control study is nested in a

defined population, so it has a lot of the

strengths of cohort studies and some of the

efficiencies of the case-control studies.

The differences between the observational

studies and randomized studies are pretty clear.

Randomized trials have the tremendous advantage

that there is lots more reason to expect the

treated and untreated groups to be comparable to

one another.

There is a lot more opportunity to be sure

that the outcome assessment and adherence to

treatment are good or at least well known, and we

have reviewed the difference for the observational

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studies.

I think it is worth making the point that

there are a substantial number of similarities

between observational and randomized studies. Just

because we randomize individuals in randomized

studies, it doesn\'t mean that the treated and

untreated groups are comparable.

We talked about a study yesterday that was

a randomized trial where there was a substantial

imbalance in important risk factors. So, it is

incumbent no matter what kind of study you do, I

think to look for comparability, and both studies

have as potential weaknesses that there are risks

of false positive results and doing subgroup

analyses and multiple comparisons increases that

risk.

We talked a fair amount about that

yesterday, and both are at risk for false negative

results. That can be partly because the studies

may not be powered well enough either because there

is insufficient sample size or individuals aren\'t

studied for a long enough duration to see the

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biological effects that we care about, or a

vulnerable group just isn\'t included.

That is a problem with both kinds of

studies and I think all studies have to be

evaluated on their own merits, so let\'s just step

through the various places where observational

studies might be into trouble or at least the

things that need careful assessment when we look at

these studies.

The first is are we studying the right

outcomes. It is essentially impossible in any of

these observational studies to use the kind of

rigorous adjudication that is a hallmark of the

randomized study, so I think we are going to have

to ask ourselves are these outcomes good enough.

The several kinds of outcomes in the

studies that we have been asked to look at are

hospitalized MIs. The case-control study by Kimmel

uses survivors. It had to use survivors because

they were collecting the exposure information by

interview after the individuals had left the

hospital, so if we care about all MIs, then, that

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study isn\'t going to tell us what we want to know.

Some of the studies use MI and

out-of-hospital sudden death by linking to vital

statistics records. I think that is probably the

closest we can get in observational studies to the

intention-to-treat all outcome designs of the

randomized trials, and some of the studies use

composite designs.

You have to ask are these outcomes

measured appropriately. Most of the studies that

we are looking at use some form of automated

medical record or claims data that have been, in my

view, reasonably well validated. That is, there is

a moderate literature showing that claims data are

not so bad for studying acute myocardial

infarction. They have sensitivities in the 90s and

positive predictive values in the 90s.

So, they are not perfect and I think we

will have to ask as we review the studied can the

amount of uncertainty that we know exists in those

account for the effects that we see, or could they

obliterate effects that we would like to see and

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which aren\'t there.

My sense is that that is probably not a

sufficient explanation to dismiss the studies that

we are looking at. The issue of bias is one that I

think always has to live as a sub-text, but quite

frankly, in the studies that do outcomes in the way

we have been describing, I don\'t think that is a

serious problem.

For cohort studies, we have to ask are we

studying the right population, and here I think we

really do have to stop and ask carefully. One is

are these people selected from the population under

study. I think in most of these examples, they are

reasonably representative, that is, a study of the

people of Ontario or members of a large health

plan.

I think that the data systems that are

used to identify the individuals in the cohort are

good enough to give us reasonable belief that we

are identifying either all the people or a

representative sample of them.

I think there is a fair question of

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whether they are representative of the larger

population. We could ask are health plan members

systematically different from the general

population of individuals who are taking these

medications.

The range of studies we have include

health plan members. I think that there is

reasonable information that they probably are

representative, at least with respect to the drug

myocardial infarction outcomes that are studied.

Studies in Medicare and population-based studies,

such as those in Canada, I think also give us

reason to think that they are representative.

But there is an important consideration

about whether there are issues about the way

clinicians practice in those setting that might

have a serious impact on selecting individuals. In

particular, to the extent that formularies are

restrictive of, say, newer or more expensive drugs

like the COX-2 inhibitors, but I think we have to

ask very carefully whether the factors that would

influence the prescribing of one class of drugs

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over another is likely to seriously impact the risk

of these outcomes.

Additionally, if there are cost

differentials for these drugs, it may be that there

is some form of self-selection that causes

individuals who are sicker to receive these drugs,

and I think that it is incumbent on us to expect

that to be a problem in every one of these

observational studies and to ask how well do these

studies do in adjusting for that. I will circle

back to that in a moment.

I think we have to be concerned about

whether we are studying people who have had prior

NSAID exposure, in which case we would be worried

about survivor biases, of finding the individuals

who are relatively immune to these problems.

Finally, there are study design issues

about whether there are restrictions of eligibility

that might importantly color the data. For

instance, at least one of the studies we are

looking at requires individuals to have received at

least two dispensings of a nonsteroidal agent in

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order to be eligible.

That means that you have to live long

enough to have two dispensings, so it certainly

doesn\'t tell us anything about the early effects of

these drugs, and it might in an important way color

the results with regard to later exposure.

There is an important question which is

not unique to the observational studies, which is

who are the right comparators. We had a number of

discussions about that yesterday. I think that all

the issues that we discuss with regard to the

clinical trials are applicable here. In

particular, there is a lot of reason to want to

compare to other nonsteroidal users because that

gives the best chance of having a group that is

similar with regard to underlying disease status

and presumably risk of myocardial infarction.

Similarly, it is possible to say that if

you really care about COX-2 selective agents, you

should compared one COX-2 selective agent to

another.

That leaves us in the uncomfortable

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situation of not knowing what is the risk compared

to no use at all, so we have some comparisons that

do look at non-users or at least remote users, and

that has its strengths. It has the big weakness,

of course, of putting us at risk of making

comparisons against groups that are unrelated.

So, we are really talking here of mostly

about a study like the Kimmel study, not the nested

case-control study. The other kinds of concerns

that raise red flags are the real concern about

losing cases who make the group who are studied

unrepresentative.

I would point out to you, for instance,

that in the Kimmel study, only half of the MI

survivors who were identified were actually

interviewed and therefore part of the formal

analysis.

We already talked about the fact that

since that study was limited to MI survivors, that

restricts us to a less serious set of outcomes.

The other problem that really bedevils

conventional case-control studies is knowing

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whether the group of people who are selected as

comparators are really comparable.

I think that is one of the reasons that

there is so much interest in doing nested case

control studies, because at the end of the day it

is really extremely difficult to satisfy oneself

that controls really are appropriate.

Much of what we need to be concerned about

in these studies is understanding exposures. Part

of the issue is understanding how to characterize

exposure. This is both a strength and a weakness

of these studied.

You will remember I made the point at the

outset that if we want to understand how drugs work

in actual practice, that we have to do

observational studies. On the other hand, that

means we have to find a reasonable way to

characterize these drugs.

We talked yesterday I think about all the

important issues of understanding whether we had to

look at absolute dose or cumulative effects or

whether the effects start early or whether they

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start late.

I think that the best of the studies that

we are looking at tackle a number of these issues.

I will mention in a minute some of the ways that

these studies have gone about that.

I think in terms of ascertaining exposure,

it is probably reasonable to put the most reliance

on the studies that use administrative databases of

pharmacy dispensing, but I will just make the point

that we have to be clear that these studies are

done in situations where we have reason to expect

that the administrative databases are correct.

I think all the studies we are reviewing

are ones where the investigators were careful to

know that the individuals really had a drug benefit

that was operating at the moment, that would likely

find the prescription drug exposures that we care

about, but as a general proposition, you can\'t

assume that that is the case.

Most health plans have some kind of

restrictions on benefits that might lead

individuals to change their benefit status, so

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there would be periods of time when we might know

that they had an MI, and we might not know that

their drug exposure is at the moment.

I will return to a point that we touched

on yesterday, which is that although almost all of

the studies that we are talking about report their

results as relative risks, a 2-fold increase in

risk, a 70 percent decrease in risk. What we

really care about is the absolute difference in

risk.

So, that is not different between

observational studies and randomized studies, but I

think it is really a critical piece of our thinking

about the problem that we are dealing with.

The second thing that is just worth

recalling is that when we talk about a 95 percent

confidence interval, that our expectation about

where the true value lies is not uniformly

distributed over that interval.

Our best guess about where the true value

lies is around the point estimate, and if that

point estimate is wrong, the large majority of the

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uncertainly is pretty close to that point estimate,

so that it is particularly not helpful, in my view,

to pay enormous attention to p values.

The difference between a p value of 0.05,

as shown here, and a p value of 0.01 and a p value

of 0.13 is not all that enormous in terms of the

biological impact.

I think one of the things that is a

particular concern that we need to pay attention to

in these studies is the fact that it is easy to

look at a lot of different comparisons, and to the

extent that we do that, we are going to have to

just be careful to know that the strength of any

one comparison is weaker than it appears to be.

For instance, this is a quote from one of

the studies that we are looking at. We undertook

an observational study examining the association

between rofecoxib, celecoxib, other nonsteroidals

and myocardial infarction.

Well, there is no primary hypothesis

there, and the results for all of the

nonsteroidals. They are all interesting to look

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at, they are all associated with p values. Those p

values are all relatively too extreme given the

fact that there are so many comparisons.

It is a problem for randomized trials. We

talked about subgroup analyses. It is important to

do those studies, those subgroup analyses, but

absent having specified a principal hypothesis at

the outset, I think that we have difficulties in

knowing how much weight to put on any particular

one.

We talked a lot about confounding. That

is one of the most important concerns in randomized

trials. I know you all know what confounding is.

It wasn\'t obvious to me when I was making these

slides that everyone knew that, but the example, so

that we have it in mind is if what we know is drug

A versus drug B, and MI or no MI, and we don\'t take

into account important confounders, we can get

importantly incorrect results.

So, here is an example of an aggregate

analysis with a relative risk of 1.5 among 2,000

people who are exposed to two drugs. If you break

29

it apart and see that in the high-risk group, drug

A accounted for 80 percent of the exposure, and in

the low-risk group, drug B accounted for 80 percent

of the exposure, you see that in each of those two

categories, the high-risk group and the low-risk

group, that, in fact, there is no association

between drug and outcome, but you have to take them

apart to do that.

Well, the good news is if you know what

the confounders are, and you have measured them

accurately, it is possible to adjust for them, and

all of the studies we are looking at do a pretty

job of adjusting for the confounders that we know

about, so I guess one of the questions is how well

do they do at identifying the important

confounders.

I would say not bad on a lot of that.

That is, if you take, for example, the Graham study

or the studies that Wayne Ray did in Tennessee

Medicaid, there are a number of strengths. I will

sort of stop and back up on the things that make

these look like relatively more credible studies in

30

the scheme of the factors that we care about.

They are inception cohorts of nonsteroidal

users, that is, they are individuals who had to

have been members of the health plan for at least a

year before they received their nonsteroidal.

There was a lot of information about their

underlying medical status that was available to the

investigators using both claims data and medical

record data to ascertain cardiovascular disease

along a number of dimensions, utilization of

procedures like surgery or angioplasty or

diagnostic procedures that are intended to find

cardiovascular disease, hospitalizations, emergency

room visits, and a substantial amount of

information about the medications that these

individuals took that was related to or plausibly

related to cardiovascular risk factors.

Those large number of factors were used to

create separate risk models using only the

unexposed, and then to use those risk models to

create risk indexes for the individuals to use as

an adjuster for underlying cardiovascular risk.

Is it perfect? No. Is it pretty good?

It seems to me that it meets the sniff test of

saying that it has a reasonable chance of

31

identifying important confounding.

Unfortunately, there are a number of

important confounders for which health care systems

typically don\'t have good data, like smoking, OTC

NSAID use, obesity, family history, and those are

typically much more problematic.

Some of these studies have worked pretty

hard to try to either deal with it or understand

whether it could be an important problem. One of

the handouts we had, for instance, was the study by

Schneeweiss and colleagues who looked back at one

of the studies by Solomon that was performed in the

Medicare data set, and asked how important could

these unmeasured confounders be.

They actually had access to information

from the Medicare Beneficiary Survey that asked

representative Medicare beneficiaries detailed

questions about many of the things that we would

are about. They weren\'t the people who were

32

involved in that case-control study, but if you

assume that the beneficiary survey, members were

representative and they gave plausible answers, it

is possible to extrapolate back to the source

population, and the take-home message from that

work, the answer didn\'t change very much, which is

really what we want to know, not sort of the

absolute difference, but whether those unmeasured

confounders are important enough that they could

cause a difference.

I think we still have to be concerned at

the end of the day, we still have to be concerned

about residual confounding as a potentially

important problem.

One way I think that we can draw relative

assurance from that work of adjusting for

confounding is to ask how much did the estimate of

risk change between the unadjusted and the adjusted

result.

I think there is a world of difference

between an unadjusted result of 10 and an adjusted

result of 1.5, and having an unadjusted result of

33

1.6 and an adjusted result of 1.5. The former, I

think the reasonable assumption is we arguably

haven\'t been able to deal with confounding in a way

that would let us believe that 1.5 means something.

I think there is a much stronger case to

be made when adjusting for important confounders

that we know about doesn\'t change the risk estimate

very much, that that is a relative more credible

answer.

Having said that, I think that

observational studies are best at finding relative

risks that are more than 2. I think that I would

pay some attention to relative risks of 1.5. I get

very nervous about adjusted relative risks of 1.2.

That doesn\'t mean that they are not right

and I don\'t ignore them, but if we ask is that for

sure the answer, my response to that is I am just

less certain about that.

I think we are always left at the end,

while we spend a lot of time thinking about and

adjusting for confounding, and I think we can do a

pretty good job of that, it is much harder to

34

adjust for misclassification, and it is essentially

impossible to adjust for bias.

So, I think one of the things we have to

ask about is are there plausible sources of

misclassification and bias, and if there are, in

which direction do they work and would they

seriously change our interpretation.

We talked about the fact that absolute

differences are the important ones that we care

about. We have already started to look at data

that talks about person level risk and population

level risk, so beyond saying that at the end of the

day, I think these are the answers that we really

need to talk about, not about relative risk.

Personally, I think that we need two kinds

of answers. One is what is the information that

patients and their physicians need to have to make

decisions for them personally about whether to

accept certain kinds of treatments in exchange for

certain kinds of anticipated benefits.

I think there is a population level

concern that we have to have that emerges from the

35

same set of analyses, but takes on a different

form.

So, you will be pleased to know that I am

wrapping it up now, and I would say that both the

cohort and nested case-control designs, which are

the bulk of the observational studies that we are

looking at, are relatively strong ones and I think

deserve the committee\'s real attention.

I am sorry that not every one of these

studies prespecified a primary hypothesis that we

can attend to, but we should whenever possible do

that. Even though we don\'t find important effects

in some of these studies, I think it is important

to recognize that they don\'t exclude one.

As I have said, I am least certain about

attaching great weight to relatively small excess

risks even understanding that when they are

extrapolated to a large population, they could

account for very important public health problems.

Finally, I would say that the things that

support the studies\' conclusions are the fact that

when we do subgroup analyses and look for

36

dose-response effects, that they strengthen the

cause-effect relationship, and I think that there

is reason to look for consistency across studies.

I take the point that was made yesterday

that it is possible that a dozen studies of

naproxen could all have the same underlying bias

that shift the point estimate in the same

direction, but it is not so clear to me what that

bias is.

So, I think that we would have to have a

reasonable idea of what might explain consistent

differences across studies and ask if they are of

sufficient magnitude to explain that. As I say, I

am not clear that there are those kinds of biases.

I think we have to be cautious about the

fact that residual confounding bias and

misclassification are all issues with these

studies. So, I think that while they add to our

discussion, they have to be considered in light of

the fact that they are imperfect vehicles.

Thanks.

(Applause.)

DR. WOOD: Thanks very much.

Let\'s just go straight on to the next

speaker and then we will take questions for Dr.

37

Platt after David Graham\'s talk.

The next speaker is Dr. David Graham from

the FDA.

Review of Epidemiologic Studies on

Cardiovascular Risk with Selected NSAIDs

David Graham, M.D., M.P.H.

DR. GRAHAM: Good morning. Today, I will

give a review of epidemiologic studies and

cardiovascular risk with selected NSAIDs. I will

be evaluating epidemiologic data from the published

literature plus two currently unpublished studies

that I have evaluated.

My focus will be on providing estimates of

risk of acute myocardial infarction in the setting

of the use of COX-2 selective NSAIDs or naproxen,

although I will have some comments in light of

yesterday\'s discussion about other NSAIDs on those,

as well.

The methodology was to do a PubMed search

38

by specific NSAIDs and then cross-check the

citations in those articles to see if there are

other articles I had missed.

I would also like to take this moment to

thank Dr. Crawford for his leadership in making it

possible for me to present some of our preliminary

data from a study in California Medicaid, which Dr.

Gurkiepal Singh from Stanford and I recently

completed.

Before I get into the substance of my

talk, I just want to comment a little bit on excess

cases and projecting to the national population

what was the impact of rofecoxib use, and I am

doing this for two reasons - one, because it has

been a source of controversy and concern. We cite

a number in a paper that I and others have

published from Kaiser Permanente in which we made

an estimate of the impact of rofecoxib use.

Tomorrow, FDA will present its estimation

of the number harmed by rofecoxib, modeling

randomized clinical trial survival curves. A

couple of things I would like the Committee just to

39

be aware of when they see that data tomorrow. It

assumes a grace period at the beginning of use that

is based on the VIGOR study and the APPROVe, 6-week

grace period in which there is no difference in MI

or increased risk of MI, and the first six weeks of

high-dose use with the first 18 months of low-dose

use of rofecoxib.

As I will show later in my talk, I believe

that this is unreliable due to low statistical

power early on, because we are only talking about

in each of these studies a handful of cases early

on in the study. Two or three cases of MI and wide

confidence intervals, you could have divergence of

the curves very early.

The epi studies, however, that I will

present will show that there is a 3- to 50-fold

more events to work with, more statistical power,

and it suggests a different outcome.

The second is, is that the patient

enrolled in randomized clinical trials are

generally healthier than patients in the real

world. So, if you are going to model what is the

40

number of people who have been harmed in the

population, you have got to assume what is the

background rate that you are modeling off of.

If you use a background rate from healthy

people to model what is happening in the population

of people who really aren\'t so healthy, who have a

higher background rate, you will underestimate the

actual population impact.

So, in any event, now on to the substance

of my talk.

The next three slides provide a very dense

overview of the major features of each of the

epidemiologic studies that I reviewed. I am

looking at COX-2 usage in acute myocardial

infarction.

You can see that they are grouped in

several groups. The top three studies I consider

from an epidemiologic perspective to be stronger

studies to have been done better. In terms of the

things that Dr. Platt just talked about, I thought

that these studies were the stronger studies.

The next two studies from the published

41

literature I thought were less strong, and I will

describe why. Finally, I have separated out these

last two studies, one submitted by Merck to the

FDA, performed by Ingenix, and the other, the

Medi-Cal study that Dr. Gurkiepal Singh and I have

recently completed of unpublished studies, so they

are separated out from the group.

You can see we are talking about different

source populations, and so if we can see

consistency of results across different

populations, different age groups, and different

study designs, I think that that adds support to

the notion that there is a real effect.

If we begin to see that there is a lack of

consistency across the studies, then, many of the

things that Dr. Platt talked about before need to

be considered sort of the individual level of the

studies, so what might explain why one study shows

something and another one doesn\'t.

This next slide shows the case definitions

and in a number of cases that we were working with

to come up with the relative risk estimates that I

42

will show you.

All of the studies began with hospitalized

acute myocardial infarction. Several of the

studies were able to link members of their base

cohorts to death certificate data to identify

sudden cardiac deaths, as well. So, those are the

ones that have the +Sudden Cardiac Death.

The asterisk next to the Kimmel study is

to remind me and to remind you that the Kimmel

study was based on nonfatal MIs only. By their

design, they had to interview their cases in

person, so the patient had to survive their

myocardial infarction to be interviewed. So, there

are those differences in study design.

In the end, what is very important in an

epidemiologic study in dealing with this issue I

think in particular, is what is the statistical

power of the study, and that is driven primarily by

the number of events in the exposed group that we

have to deal with.

So, in this column here, you will see the

total number of cases of myocardial infarction that

43

were identified in each of the studies. The

asterisk next to the Ingenix study 628 is to remind

me that in that study, they identified about 1,700

MIs in total, but they excluded 1,100 of the MIs

because they occurred in people who weren\'t exposed

to an NSAID at the time of the myocardial

infarction. So, as a result, they left them out,

because in the previous slide, when we look at the

reference group, most of these studies used either

non-use or remote use as the comparator. The

Ingenix study used active treatment with either

diclofenac or ibuprofen.

I would like to say one thing about

reference groups. Dr. Platt brought it up before.

In this issue, I don\'t believe that there is a

single best or optimal reference group. What you

really want to do is get as close as you can to a

placebo group that has been randomized and has all

the risk factors of the people who are getting the

drug.

In the observational world we can\'t get

there, and so at the end of the day, if you want to

44

do a study, you are in a sense forced to pick among

the least evil of that you think, and then it has

to do with how you define things.

So, non-users, for example, could be

viewed as being close to the placebo group, they

are not getting the drug. The problem is people

who don\'t use drugs tend to be healthier than

people who do use drugs, so that raises a host or

problems.

Yes, we can try to adjust for confounding

and the like, but you are still left with that

concern that they may be, in some way that we can\'t

measure, different from the people who get the

drug.

In the study I did, and in several other

studies that people have done, we opted to use

people who had been treated with NSAIDs in the

past, but weren\'t currently taking an NSAID at the

time of the event or the study, the reasoning there

that whatever the selection factors are that lead

to a patient getting an NSAID, that some of those

selection factors are there in people who

45

previously received NSAIDs.

That is still not a perfect group, though,

because you could argue that patients who are no

longer taking NSAIDs might be healthier than people

who are currently taking NSAIDs.

Finally, the problem that is posed by

using an active comparator. If you have an active

comparator, and I am comparing another drug to an

active comparator, and I see a difference, I don\'t

know what it means. I need some place to anchor

the result, and for that reason, although none of

them are perfect, I believe that the non-use and

the remote use analyses at least give us a way of

pegging results, and if we want to compare one drug

to another drug, if we had that common reference

point, at least it allows us to accomplish that.

The one other thing I would like to point

out about the number of cases is that for

rofecoxib, especially at the high doses of

rofecoxib, most of these studies had relatively few

exposed cases. The exception is the California

Medicaid study where we had 157 exposed cases to

46

the higher dose of rofecoxib.

Now, this is a very busy slide and I won\'t

spend a lot of time going over it, but I will be

happy to answer questions later.

Basically, before we heard there are

unmeasured risk factors in automated databases that

frequently can\'t be accounted for, aspirin use and

smoking are among the most common. So, you can see

here that most of these studies, that information

isn\'t obtainable.

Kimmel was able to get both because they

interviewed the patients, the cases and the

controls. In the Medi-Cal study, it turns out that

aspirin is reimbursed, and so we have a handle on

it there.

In the Graham study, a survey of controls

was done to see what these unmeasured factors might

look like in the source population. The Solomon

study did the same thing, relying on the Medicare

Beneficiary Survey that Dr. Platt talked about

before.

Important limitations I think that need to

47

be highlighted are that in the Mamdani study, they

excluded patients who had less than 30 days of

NSAID use, so the survivor bias Dr. Platt talked

about before, in my view, is big concern with this

study, and for that reason I ranked it in sort of

that category of low quality studies.

In the Kimmel study, as Dr. Platt also

mentioned, there was low participation rate.

Basically, half of the cases and half of the

controls who approached volunteered to be in the

study. More importantly I think in that study, and

it\'s unfortunate, is that there was what I would

refer to as the potential for, in quote \"reverse

recall bias.\"

Normally, with recall bias, we think oh, I

have had a heart attack, I am going to remember

more efficiently what happened to me immediately

before the heart attack compared to some control

where I say to the control what were you doing four

months ago on this particular day.

That is the classic recall bias. This

situation I think had what I would describe as

48

reverse recall bias. They interviewed the people

who had heart attacks within four months of getting

out of the hospital - what happened to you the day

and the week before you had your heart attack four

months ago.

For the controls, they call them on the

phone and they way what happened to you yesterday

and the week before, so it is actually the reverse.

The controls actually would have better recall of

what they were actually doing than the cases

potentially, and we will see how this is reflected

in some of the results.

Finally, with the Medi-Cal study, I think

the single greatest concern for the committee in

considering these data (a) that it is preliminary

data, and (b) that this is a new database for

research purposes.

For that reason, I am just including a

slide to orient people to that. The other

databases are ones that have been used before.

This is a database that only in the last two years

has come online to be sort of a quality sufficient

49

to begin contemplating doing studies.

Its strengths are that it is very large,

it captures aspirin use, it doesn\'t censor people

by age. It combines Medicare coverage when you go

over the age of 65 with the prescription benefits

of Medicaid, so you get the drugs and the outcomes.

Matching has been done to multiple cause

of death tape, so that we have death data in this

database up through 2002. We didn\'t include it in

the data I will show today because we really want

the information up through 2004.

Once people get into Medicaid or Medicare,

they don\'t tend to drop out. The limitations are

that we can\'t get medical records, and that is

something to understand, and that is a very

complicated database. Dr. Singh from Stanford who

is the principal investigator for our Medi-Cal

work, and who has worked to bring this database

online, spent two years putting things together and

working out the kinks in it before contemplating

doing research with it, so at least you understand

the limitations of that.

There is always the concern about

unmeasured risk factors and Dr. Platt talked about

that. I want to review for you very briefly some

50

of the evidence from the published literature where

efforts were made to look at what unmeasured

confounding looked like and did it differ across

NSAID type.

In our study using Kaiser Permanente data,

we did a survey, a random survey of random sample

of controls, and we looked at aspirin use, smoking,

and over-the-counter NSAID use. You say see by

NSAID that there really was not significant or

substantial differences in the distribution of

these risk factors.

So, if they don\'t vary in the control

group, they can\'t really confound that observation

that you see very much.

In the Solomon study, these are the data

from the beneficiary survey. Dr. Platt already

mentioned a further analyses of these data that

showed that the actual impact of all these

unmeasured confounders on the measure of the

51

relative risk at the end was measured in the

hundredths of an odds ratio, so if the odds ratio

was 1.34, adjusting for these things and projecting

it out would change it to maybe 1.35 or 1.33. We

are talking about minuscule differences, not

qualitatively important differences.

Finally, in the Kimmel study, they also,

through their interview, were able to see that for

most of these factors, there was similarity across

NSAID groups except for current smoking where the

rofecoxib group had much lower current smoking than

any of the other NSAID groups, but for past

smoking, it was more than the other NSAID groups or

the remote groups, and if you added these two

together, the rofecoxib was very similar to these,

but the celecoxib group had more smoking.

My own conclusion from this is that yes,

it is possible that some of these unmeasured risk

factors could be influencing the results. I don\'t

think that there is strong evidence that there is a

systemic bias that would sort of lead to

interfering with trusting the results and thinking

52

that these factors are confounding the observations

that we see.

So, first, I will talk about rofecoxib,

then I will talk about celecoxib, then I will talk

about valdecoxib in terms of epidemiologic data.

These studies on the left, with their

reference groups, are the ones that looked at

myocardial infarction with rofecoxib. What I have

shown is for all doses and where it was present

less than or equal to 25 milligrams and over 25

milligrams, what the fully adjusted odds ratio and

95 percent confidence intervals were.

These studies varied in the extent of

adjustment that they did. The Ray and the Graham

studies each adjusted for about 30 cardiovascular

risk factors. The Solomon study was a somewhat

smaller number, Mamdani was a somewhat smaller

number. Kimmel, they adjusted for somewhere in the

20s, the Ingenix study somewhere in the 20s, the

Medi-Cal study adjusted for about 40 cardiovascular

risk factors.

What you can see is when you look across

53

the All Doses is that, in general, the point

estimates were elevated and for many the 95 percent

confidence intervals excluded 1.

More importantly, though, is looking at

the low dose and the high dose data because we know

from the clinical trials data, and we would suspect

it on just pharmacologic grounds, that if there is

an association that it might be worse with the

higher dose than with the lower.

So, four studies provide us estimates at

the low and the high doses, the Wayne Ray study and

our study from California Medicaid, and then the

two unpublished studies, one from Ingenix and the

other from California Medicaid.

We see there that in three of the four

studies, there is an elevation in the point

estimate. In the Graham study, it included one.

When we look over 25 mg, we see greater consistency

although in the Ingenix study, there is this

paradoxical finding of sort of basically a neutral

relative risk. I don\'t have an explanation for why

that happened, but it makes me concerned to some

54

extent about what was going on in that study,

because it is a result that goes in a very

unexpected direction.

What I would like to point out, because I

will come back to it again, is that when we are

dealing with drug safety, and the goal now is what

risk can I exclude, if my job is\--now I am not

talking about efficacy anymore, what I am talking

about is safety\--if my job is to protect the public

from harm, what risk can I exclude based on the

data that I have, I believe that is much more

relevant to look at the upper bound of the

confidence interval than the lower bound.

What traditionally happens is we look at

the lower bound of the confidence interval and we

say if it includes one, there isn\'t a problem, but

the biggest reason, as Dr. Platt showed in his

previous slide, for a wide distribution and a wide

confidence interval in your study, is that the

study doesn\'t have enough statistical power to get

you a narrow enough confidence interval to say that

you have the 95 percent certainty that you want.

So, if your mission is above all else I

want to do no harm, that I want to protect patients

from harm, then, based on the data you have, I

55

would submit that the upper bound of the confidence

interval provides greater assurance to patients,

and then if you are going to compare a benefit to a

drug, that you might want to consider that benefit

against that upper bound of the confidence

interval, because that is compatible with the data.

In any event, that is my view, and not the FDA\'s.

This is a slide from California Medicaid.

It is preliminary data and I wanted to present it

to you, because what it shows is a dose-response to

rofecoxib from 12.5 mg up to and through 50 mg.

You can see that we have very wide

confidence intervals for some of them, and that is

a reflection of the limited number of cases, but I

want to point your attention to the very narrow

confidence intervals in the 12 to 25 mg and in the

25 to 50 mg, just to point out that in the previous

slide here, where we are talking about what are

these point estimates, that now you can what we

56

have done is we have fleshed them out a little bit

more.

Another comparison that I think is

important to consider, certainly it was for us,

when we did our study in Kaiser Permanente, was at

the time there were two COX-2 selective inhibitors

on the market, celecoxib and rofecoxib.

The bigger study raised a question about

high-dose rofecoxib. Our question as researchers

was, and public health scientists, was, well, let\'s

suppose that rofecoxib increases the risk of

myocardial infarction.

We don\'t know that it does, but let\'s

suppose that it does, what about celecoxib, because

it actually had a larger share of the market, and

if it turned out that these drugs have a benefit,

and that benefit is worthwhile, then, it would make

more sense from a practical perspective to use the

drug that had a better safety profile.

So, to us, it was very natural to want to

compare rofecoxib to celecoxib, and so several of

the epidemiologic studies felt similarly and in

57

their design they included that analysis, and some

of them it was, as Dr. Platt said, part of a we are

going to make comparisons of everything against

everything.

The Solomon study, for example, did that.

They did not state in that study what their prior

hypothesis was. In our study, we did state it. I

mean yes, in a sense we had multiple comparisons,

but we were interested in two different things. We

were interested in rofecoxib versus remote use, and

we were interested in rofecoxib versus celecoxib,

but we thought it beforehand and we planned that

analysis.

But in any event, what we say is, when you

look at the all dose analysis, in all of the

published studies, rofecoxib increased the risk

compared to celecoxib. When we looked at low dose

rofecoxib, we see the increased risk. When we look

at the high doses of rofecoxib to celecoxib, again,

we see the same pattern.

Dr. Platt, in his talk before, talked

about relative risks, risk differences, individual

58

risk, and population risk. The next two slides are

intended to address this at the level of the

individual and at the level of population.

What I have done on this slide\--and these

slides now, no one should interpret this as meaning

this is what actually happened in the

population\--the next slide is going to have numbers

on it that are for illustrative purposes only, to

help the committee understand what does a relative

risk of 1.3 translate into at the individual level

and at the level of population.

Your typical COX-2 user is somebody in

their 60s who has several other health problems, so

I went to the National Center for Health Statistics

and got the myocardial infarction rate for 65- to

74-year-old men in the United States. That rate

turns out to be 1 per 50 per year.

What I did is I took that as the

background rate and I said if I have an individual

using this drug with that background rate and then

I applied to that person the relative risks or odds

ratios found in these studies that are shown in the

59

previous slides, what would the excess risk to the

person be, sort of what would that risk difference

translate to for the individual.

For example, in the Ray study, if you

remember, for 25 mg or less, the odds ratio was

1.02. Basically, it doesn\'t change. If we based

it on the point estimate, that 0.02 would translate

to 1 out of 2,500 in a year increased risk of heart

attack.

Another way to view that number is, is

that is the number needed to harm. If I treated

2,500 65- to 74-year-old men for a year with

rofecoxib, and the rate was 1.02 that Ray found,

treating 2,500 patients would produce 1 extra heart

attack.

Now, with the other studies that found

higher estimates for the lower doses of rofecoxib,

you can see that the number needed to harm ranges

from about 90 to 200. That is saying for every 90

people to every 200 people I treat with low-dose

rofecoxib, I would generate 1 other case.

For high doses, because the relative risks

60

were higher, the number needed to harm becomes

lower.

I have also shown it based on the upper

bound of 95 percent confidence interval to show you

that based on the data we have at hand, these are

the excess risks that are consistent with the data,

and from a public policy perspective, from a public

health perspective, that is what I react to, and

when I want to see a benefit and say does benefit

exceed the risks, well, I want to know what is a

real benefit in the population in terms of reduced

hospitalization, lives saved, and does that benefit

exceed what I can say is possibly the risk of these

products.

At the population level, now we have gone

from an individual. Remember in the Wayne Ray

study we said it is 1 out of 2,500. Well, that

would translate to 400 additional cases of heart

attack if we treated a million men who were 65 to

74 years old, and we treated them with rofecoxib

low dose for a year.

With the others, you can see that those

61

relative risks that might not look so impressive,

that 1.23, that 1.30, that 1.4, that it projects

out to a substantial number when you multiply it by

the large number of people who use these products.

For high doses it ends up being even

greater, and then if we focus on the upper bound of

the confidence interval, we again see that the

numbers are larger still. This very high number in

our study was the result of our having low

statistical power in addressing the high dose

rofecoxib.

One other question that I think is

important to consider is when does the risk of

myocardial infarction with rofecoxib kick in. Now,

we have seen data yesterday presented by both FDA

and by Merck of various survival curves.

We saw the bigger curve that showed the

separation after about 6 weeks with an overall

relative risk of about 5. We saw, for the APPROVe

study, this close overlapping line at about 18

months, and then they diverge with an overall

composite hazard ratio of about 2.

I would submit to the committee that the

reason for the failure of these studies to show

divergence of the line shortly after the drugs are

62

used are low statistical power, that they just

don\'t have enough events to show it, and as a

result, you can interpret because of the low

statistical power you basically\--how to describe

it\--you presume that there is nothing there, and

you err on the side of the drug rather than erring

on the side of what could the risk be to the

population.

If you really want to know what is going

on in the population, then, you want to reduce the

uncertainty. The more uncertainty you have, if you

act basically on the lower bound of that confidence

interval, which is what you are doing when you are

saying the risk doesn\'t begin until 18 months, you

are basically saying that the absence of evidence

is evidence of absence.

I would say that in safety, what it is, is

you just don\'t have enough power.

Looking at the epidemiologic studies, I

63

think that we have evidence to suggest that the

risk begins much earlier. I will point it out, and

you guys and women can consider it for yourselves.

In the Graham study, when we looked at low

dose and high doses of rofecoxib, 50 percent of our

cases at the low dose and at the high dose had used

at the time\--remember these are inception cohorts,

so these people, their total use, this was 1.8

months, this was 2.7 months\--50 percent of our

cases occurred within 2 to 3 months of starting the

drug.

That is a lot of power and that really

speaks against the notion that the risk is

backloaded, you know, it is for the low dose, that

the risk doesn\'t happen until after 18 months.

Nobody in our study was on rofecoxib for more than

about 15 months. I think that was the longest

duration of use we had in our study.

Now, in the Solomon study, they looked at

the low dose and the high dose, and they presented

data in several ways. One is that they grouped

things in 1 to 90 days, and what they showed was

64

that for both the low dose and the high dose, there

was evidence or risk early on.

The Kimmel study, for all its

deficiencies, most of it was low dose rofecoxib,

and almost all the patients used it for less than

12 months. So, their finding on rofecoxib, if

anything, would also speak to that the low dose

effect kicks in long before 18 months.

Finally, the Solomon and the Ingenix study

looked at the first 30 days of use of these

products, and both of them found elevated odds

ratios of 4 for cardiovascular risk in the first 30

days.

Now, in both of these studies, they didn\'t

separate it out by low dose and high dose, so this

is a composite, but in both studies, about 85

percent of the use to 90 percent of the use was low

dose.

So, basically, what I am concluding from

this slide is that risk of myocardial infarction

with rofecoxib begins when rofecoxib use begins,

and that the inability to separate out those curves

65

is based on the fact that if you were to count the

actual number of events in the bigger study in the

first 6 weeks, we are probably talking about 3 or 4

events, and if you look at the confidence

intervals, you are going to see they are wide.

For the APPROVe study, the same thing

holds, that you have too few events. The whole

study had 45 events, and I don\'t recall how many of

those were on rofecoxib and how much of those were

on placebo, but when you think about it, compare

that and then look at the epidemiologic studies,

and look at the number of cases that were in the

epidemiologic studies, and for all their problems,

and we can talk about those, they suggest there is

a big discordance, and I think the answer, the

reason is absence of statistical power in the

clinical trials.

In the epidemiologic literature, this has

been recognized, and people have written papers

saying that when you are trying to summarize the

overall risk from a survival study, and you want to

look at specific time periods, that you are better

66

off taking the overall risk estimate for the entire

study than focusing on a small segment at a time

because of this issue of low statistical power, so

I didn\'t invent this.

Now, switch over to celecoxib. There are

a number of studies that have been done to look at

celecoxib risk. What I have tried to do here is

plot out for you the relative risk or the odds

ratio, the author of the study, and then the point

estimates in the 95 percent confidence intervals.

What you will see basically is that for

most of these studies, there is no evidence of a

protective or an injurious effect except for the

Kimmel study that found a substantial protective

effect.

Remember the Kimmel study and what I

believe is this reverse recall bias, as well as the

low participation rate, and I personally discount

that study. The committee can decide for

themselves that they want to do.

What about celecoxib lower dose versus

higher dose? Well, unfortunately, the only place

67

where this is adjusted, is looked at are in the two

unpublished studies. We have the Ingenix study and

we have the Medi-Cal study.

What I would focus your attention on are

the low dose and high dose, the low dose and the

high dose. What we see is in both studies,

evidence of a dose response. Now, the 95 percent

confidence interval in the Ingenix study includes

1, but the point estimate is pretty elevated. That

is 1.18 or so at 400 mg.

In the Medi-Cal study, we go from 1.01 up

to about 1.24. Here, you can see the 95 percent

confidence intervals.

What I would conclude from this, although

they are unpublished studies, that there is

evidence of a dose response at the higher doses of

celecoxib do confer an increased risk of myocardial

infarction.

I should point out that in the Medi-Cal

study, the methodology that we used in that study

is the exact methodology that we used in our Kaiser

Permanente study that Dr. Platt before was gracious

68

enough to say is one of the better done studies.

There are no published studies on

valdecoxib, so what do we do? Well, preliminary

data from Medi-Cal, we had 54 exposed cases and we

found a point estimate of 0.99. Now, this was

mostly 10 and 20 mg use. I think that out of all

the patients that we had in the study, there were 2

or 3 who had 40 mg valdecoxib use.

In Medi-Cal, they only reimburse for the

10-mg tablet, and they do this in an effort to try

to discourage people having larger dose tablets and

then taking more of it.

So, this is all the epidemiologic

information that I am aware of, that I have had an

opportunity to review on valdecoxib.

I will now move to naproxen. The issue of

naproxen is important for several reasons. One,

with the VIGOR study, the medical community was

confronted with the hypothesis that naproxen was

the single greatest and most effective

cardio-protectant in the history of mankind, that

it was far better than aspirin.

We heard yesterday that aspirin reduces

cardiovascular risk about 20 to 25 percent.

Naproxen, if we were going to believe the VIGOR

69

results, would have to reduce the risk of

cardiovascular events by about 80 to 85 percent.

So, this stimulated a lot of research.

Here, I have summarized in the same fashion as I

did for the rofecoxib studies, the various studies

that have been done. Again, I have separated them

out by the studies that I think are better done,

the studies that have more significant limitations,

and then the two unpublished studies.

I point out the Rahme study to say that

the only reason the Rahme study is listed among

this group of suboptimal studies is that its

reference group was other NSAIDs, primarily

ibuprofen, because ibuprofen was the predominant

other NSAID used in Quebec during the study.

Again, we have the various outcomes that

were done. What I would point is that you can see

the number of cases that we had to work with in

these various studies, and I would point out that

70

for the Solomon study, they had about 240 MI cases

that they studied overall, but as you will see in a

few minutes, that exposure could occur anytime in

the past 6 months, so they don\'t see in the paper

how many people were actually on naproxen at the

time they had their event, so I can\'t put down a

list of how many people were currently exposed.

The Watson study is the only study that

used a composite outcome. It included myocardial

infarction, stroke, subarachnoid hemorrhage, and

subdural hematoma. Why subarachnoid hemorrhage and

subdural hematomas are in there is beyond me. In

any event, 26 cases of that composite outcome and a

much smaller number of actual myocardial

infarctions. So, that is why that asterisk is

there.

With the Ingenix study, the asterisk next

to the 179 is that this included both prevalent and

incident cases, and the best studies, the best

results come if you base it on incident cases only

or incident use only as opposed to prevalent use,

because prevalent use can have survivor bias. But

71

in any event, in the Ingenix study, they had a

number of different analyses, and they didn\'t

always use their full number of cases.

There are important limitations to note.

I think the one to focus is to realize (a) there is

no perfect study, we have talked about that before,

and, two, that among all the limitations listed

here, I think the most important one to note was in

the Watson study, was this composite outcome which

really just makes it very difficult from an

epidemiologic perspective to study things.

Myocardial infarction is very well

validated in claims data, and Dr. Platt has already

gone over that with you. Stroke is notoriously

difficult to work with in claims data, and subdural

hematomas most commonly occur because as people get

older, their brains shrink. They bump their heads

and then they get a little bleeding on the surface

of the brain. What that has to do with myocardial

infarction risk, which is what we are really

concerned about today, is beyond me.

I have got two slides on the results.

72

This slide shows the studies that found no

protective effect. There is four studies that

found a protective effect, and I am saving them for

a separate slide, because I want to look at those

individually.

What you can see from the majority of

these studies, and I would point out that the

studies that were the best done studies in the top

tier, they are on this slide, that all of them sort

of suggest that there is no cardio-protective

effect of naproxen. Several of the studies point

to the possibility of a small increased risk with

naproxen.

But we have four studies of positive

results, and we will probably all remember the

Archives of Internal Medicine publishing three of

the articles in the same issue with an accompanying

editorial that stated the issue is solved, naproxen

is cardio-protective.

I want to look at those studies and just

describe to you my view of them. The top three

studies were the ones that were\--well, no, not the

73

Kimmel study\--Rahme, Solomon, and Watson were the

Archive studies.

In the Rahme study done in Quebec, they

compared current naproxen use versus other NSAIDs.

That other NSAID was, by and large, ibuprofen, and

they found a protective effect. Well, if ibuprofen

increases the risk of myocardial infarction, let\'s

just say that it does, and naproxen doesn\'t,

naproxen could look like it\'s protective compared

to ibuprofen, but not be protective really.

The data presented in that paper, if we

re-analyzed it versus non-use, we get an odds ratio

of 1.28, statistically significant. Now, this is

not adjusted. It is not possible from the data

there for me to adjust this result, but based on

what is in the paper, when you compared the

unadjusted to the adjusted point estimates, they

don\'t change very much, and what that suggests to

me is that this effect, this 0.128 is probably not

far off the mark.

That would then make it comparable to the

analyses I showed on the previous slide, that all

74

of these slides use non-use or remote use, so then

it would add a fourth study to an elevated point

estimate for naproxen.

Now, the Kimmel study, we have already

talked about low participation rate and this

reverse recall bias, and a small number of NSAID

cases. In fact, they don\'t even tell us in the

paper how many cases they had.

We move on to the Solomon study. This was

the result that was reported in the paper and was

picked up by the press, a 16 percent reduction in

heart attack risk with naproxen. The problem, in

my view, was that their definition of exposure in

the study was any use of naproxen in the past 6

months, which means that if I took naproxen 6

months ago and stopped it, I could be included in

this study as being exposed to naproxen.

So, the question is then, you know, how do

we interpret the study. Well, Solomon was good

enough to present data by current use and in recent

use, and recent use included people who stopped

their naproxen. Their naproxen prescriptions day

75

supply ran out between 1 day and 60 days before the

MI or the index date for their controls, and remote

users, their NSAID use, their naproxen use ended

from 61 days to 180 days prior to the event.

So, let\'s look at what those results are

then, and what we see is they are identical. So,

unless the committee is prepared to believe that

naproxen confers lifetime immunity to

cardiovascular disease, I think we have to conclude

from these data that what we really have here is

selection bias, and it is not the fault of the

investigator. Dr. Platt talked about before that

there are some things you can\'t adjust for. You

can\'t adjust for bias. What you can try to do is

identify bias, and if you identify it, then at

least you know what you are dealing with.

Here, I think we have what is classic

selection bias. It is not naproxen that protects

you again myocardial infarction, it is some other

factor that in this health plan, that they used to

study this drug, the patients who were being

treated with naproxen happened to have lower

76

cardiovascular risk.

I can\'t explain why that happened. Dr.

Solomon probably can\'t explain why it happened, but

it\'s not due to naproxen.

Finally, the Watson study. This study was

sponsored by Merck, and it was authored by Merck

investigators. The result that was published as

being the basis for the conclusion was this top

result, a 39 percent reduction in cardiovascular

risk.

First, I just want to remind everybody,

composite outcome here, subarachnoid hemorrhage,

subdural hematoma, stroke, as well as heart attack,

26 events total, much smaller number of heart

attacks.

For this event, you can see the

checkmarks. These are the various variables that

they adjusted for in the study. The way they

handed cardiovascular risk, if you read the paper,

I would have to say that it doesn\'t measure up to

the standards that were set by Dr. Wayne Ray.

We modeled our study in Kaiser and in

77

Medi-Cal, and Dr. Wayne Ray, I think that he has

set the standard for how one needs to go about

adjusting for cardiovascular risk. It is not enough

to rely on diagnoses. You have to use the

medications, because medications are much more

accurate predictors of disease than diagnoses in

these administrative claims data.

In any event, they didn\'t adjust for

cardiovascular risk, and they didn\'t adjust for

smoking although they had that data. Then, they

present later on another analysis that now includes

cardiovascular risk and it is no longer, in quotes,

\"statistically significant,\" and then they include

smoking, and again it is not statistically

significant.

My conclusion on the Watson study was that

\(a\) they have got a composite outcome that, in my

view, isn\'t very informative towards the question

of myocardial infarction; (2) that it is very small

numbers; (3) that a variety of approaches were used

in the analysis that inadequately account for the

risk factors that could confound the result, so I

78

have discounted that, as well.

So, a conclusion when I look at these, in

quotes, \"4 positive studies,\" I conclude that none

of them provide credible evidence of a protective

effect.

In light of yesterday\'s discussion in the

afternoon about other NSAIDs and what might explain

the differences, let\'s say, celecoxib and rofecoxib

studies, the rofecoxib studies used naproxen as a

background, a comparator, the celecoxib studies

using ibuprofen or diclofenac.

Dr. FitzGerald is talking and saying,

well, you know, all of these drugs could increase

the risk because what is happening, you know,

biochemically, with the balance of prostacyclin,

could be influenced by these different drugs in

ways that aren\'t immediately obvious or detectable

in a clinical trial.

I thought I would just share some of that

information on other NSAIDs with the committee,

recognizing a couple things that no single study is

definitive and what you want to look for I think is

79

consistency across studies, but as far as

randomized trials go, I would like just to mention

that there are generally too small, too few events,

and you are not going to get the answers that you

need from them unless you make these clinical

trials substantially larger than anything people

have contemplated up to now.

So, from our California Medicaid study, it

is all preliminary and it has not been published,

for ibuprofen we found a small but statistically

significant increased risk. For indomethacin we

found a risk of 1.7. I would like to say on

indomethacin that we found an increased risk with

indomethacin in our Kaiser Permanente study. It

was 1.3 and it was highly statistically

significant.

In at least two other studies that I

reviewed in preparation for this advisory meeting,

indomethacin is noted to have an increased risk of

myocardial infarction.

It is not commented on in the text because

that wasn\'t a primary analysis, but what I am

80

talking to you about now is consistency, and I

would submit to the committee that indomethacin is

a lot of smoke, there is a lot of smoke for

indomethacin.

In our study, in our Kaiser study, for

example, we did not think in advance to look at

indomethacin separately. I mean we knew we were

going to look at it, but it wasn\'t a primary

hypothesis. We didn\'t adjust for gout. I mean

everyone knows that indomethacin gets used in gout.

Gout increases the risk of cardiovascular disease.

Well, in the Medi-Cal study, we adjusted

for gout. Yes, gout increases the risk of

myocardial infarction. It didn\'t change the odds

ratio here.

I think this next finding, Meloxicam, is

important. Meloxicam is now the number one selling

branded NSAID in the country. With the removal

from the market of rofecoxib, the medical

community, shying away from the coxibs, are moving

to other drugs that they perceive would have the

advantages of COX-2 selectivity without the bad rep

81

that coxibs appear to be acquiring.

So, you now have a shift in the

marketplace to Meloxicam. There have been articles

in the Wall Street Journal and the New York Times

on this. The company recently raised the price on

the tablets.

In any event, we are presenting these data

just to say that we found an increased risk. It is

one study, but I think it is the only study. We

looked at this in Kaiser. Meloxicam is almost not

used in Kaiser, so we couldn\'t study it.

In our California Medicaid study, we only

looked at drugs that had more than 50 currently

exposed cases. Nabumetone came out in this study

as not showing a whiff of a problem. Sulindac,

there was an increased risk.

Regarding ibuprofen, in our Kaiser study,

we found an increased of 1.06, which sounds really

trivial. It wasn\'t statistically significant, but

the confidence intervals were pretty narrow. It

was 0.96 to 1.17.

My concern is, as Dr. Platt talked about,

82

you know, above 2 you feel really comfortable,

above 1.5, you can believe it, below that you begin

to get really edgy. The problem is most of the

risks that we are probably facing, if it turns out

that the non-coxib NSAIDs increase the risk of

cardiovascular disease, that is where the risk

level is going to be, and that is what we are going

to have to contend with, because it has tremendous

effects on the population.

Finally, dose response. This slide shows

for diclofenac. This is from California Medicaid.

What we wanted to do was show evidence of dose

response, consistency in the data. Remember we

pointed out diclofenac before. Diclofenac in this

study overall did not have an increased risk, but

at the high doses there is a suggestion of a dose

response.

I will skip that. This slide was to say

that depending on your reference point, you can get

different results, if I use an active comparator

versus remote, and this is showing the three NSAIDs

from California Medicaid compared to non-coxib

83

NSAIDs, and you can see the rofecoxib is different

than them, and the other two aren\'t necessarily

that different.

My conclusions, and I am sorry to have

gone so long. Celecoxib, we believe that based on

the evidence we have at hand, that there is no

apparent effect of risk at doses of 200 mg or less.

Above 200 mg, we think that there is evidence of

increased risk.

For rofecoxib, we believe that there is

evidence of increased risk at both the lower doses

and the higher doses, and that risk begin early in

therapy and is apparent during the first 30 days of

use.

With valdecoxib, there is a paucity of

information, but the information we have at this

time suggests that the risk is not increased at

doses of 20 mg or less.

As a class, non-coxib NSAIDs may increase

the risk with differences between each of the

NSAIDs. I don\'t think we are going to be able to

talk so much about class effects. In the end, it is

84

going to have to be looking at individual drugs.

The COX-2 hypothesis may be true, but if

it is, we are still going to have to look at these

other drugs in terms of their individual properties

and what they do.

Finally, naproxen is not

cardio-protective.

Thank you.

(Applause.)

DR. WOOD: Thanks very much. David, it

will come as no surprise to you that every time

practically I pick up a newspaper, I read about

what you are not going to tell us.

So, my question to you is what have you

not told us that you think we should know, because

I would like to make sure. Lots of other people

have shown up here without slides that they forgot,

so I just want to be sure that if there is anything

else we need to hear, we hear it.

DR. GRAHAM: Well, as far as the science

goes, I think I presented the evidence that I am

happy to be able to share with the committee that I

85

thought it was important for the committee to have

an opportunity to hear.

The source of controversy surrounding my

presentation related to the unpublished studies

that I was going to be permitted to present or

asked, actually asked to present the Ingenix

results, the unpublished study from Merck, but that

I was being told not to present the unpublished

data from the California Medicaid study, and

personally, I had great difficult standing here

before this committee as an investigator and as a

scientist, as a physician, and telling you the

information that I have, that I am allowed to talk

about, and remaining silent on things that I know

about that I am not allowed to talk to you about.

Fortunately, Dr. Crawford exercised great

leadership in making it possible for me to present

that data, recognizing it\'s preliminary, but the

methods that we used are identical to our Kaiser

study for the California Medicaid, and for me, I

think the big reservation is, is that it\'s an

untested database, but I think that everything that

86

could be done to develop the database and to do

quality assurance and to work out the kinks has

been done.

If you look at the findings in the

California Medicaid study and you compare them to

the clinical trials data, and the anomalies and the

questions that you were discussing yesterday about

the clinical trials\' data, you look back at the

California Medicaid data, and you are going to see

I think great consistency between the findings that

might help explain and interpret some of the things

that seemed questionable or uncertain yesterday.

So, in any event, I have been able to

present what I thought was important to present,

and I am happy to have had that opportunity.

DR. WOOD: So, the answer is we have seen

it all, is that right?

DR. GRAHAM: You have seen it all.

DR. WOOD: Okay, good. Let me ask you a

question. If you go back to your slide that showed

the excess population risk, put that in proportion

for us in terms of, say, the other drugs that have

87

been withdrawn from the market. I mean what sort

of numbers would we be expected to see?

DR. GRAHAM: That is a great question.

The typical drug that has come off the market in

the United States, like the leading cause of drug

withdrawals in the United States in the last 20

years has probably been acute liver failure.

Rezulin came off the market because of it,

troglitazone, bromfenac, a number of other drugs.

Acute liver failure in the general

population has a background rate of about 1 per

million per year. We are talking about that is the

rate of being struck by lightning, 1 per million

per year, and these drugs were pulled off the

market because it increased the risk of that. It

might increase the risk 5-fold, it might increase

the risk 10-fold, it might increase the risk

100-fold. The fact is the background rate was 1 in

a million and what that means is that the actual

number of people affected is sort of measured in

the tens and the hundreds for the liver failure

that could be life-threatening.

In this situation, and this is why the

lower relative risk becomes so critical, we are

talking about a serious event that has a very high

88

background rate. Heart attack is not a rare event,

and as I pointed out before, there is a 1 in 50

chance that the average American male age 65 to 74

is going to have a heart attack this year, 1 in 50.

That is an extraordinarily high risk. You

increase that risk 5-fold with a high dose. That

is what happened with VIGOR. If I have got

millions of people taking the high doses, and that

is what had in the United States, and I have

increased the risk 5-fold, you are going to get

numbers that balloon out like this.

So, there is no comparison in terms of

what the population impact is of the typical drug

that has come off the market in the United States

and what we are dealing with here, and that is

because of the high background rate of the

underlying event that we are talking about.

DR. WOOD: So, this would produce many

more cases from what I understand.

DR. GRAHAM: Many more.

Committee Questions to Speakers

DR. WOOD: From the committee, we have

questions. Let\'s start with Dr. Shafer.

DR. SHAFER: Dr. Graham, tomorrow we are

going to be asked, as a committee, to consider the

89

question about a class effect for the selective

COX-2 antagonists and for the non-selective NSAIDs.

One of the things that I am finding, that

I am having trouble putting together here, is we

have a lot of conflicting data, and for the COX-2

antagonists we have a lot of data from randomized

controlled trials.

Certainly for the NSAIDs, we are going to

have to go with a lot of these observational

studies because we don\'t have a lot of data on the

topic at hand from randomized controlled trials.

As I look at this, if we come up with some

sort of common warning as a class, and it applies

to everything, we have, in fact, communicated no

relevant information. On the other hand, if we are

going to come up with individual drug-specific

90

recommendations, we are going to have to have very

different evidentiary standards in some ways,

because for some of these, we have very little

information, as you pointed out, and yet your data,

particularly the unpublished data from the Medi-Cal

trial, and I appreciate that there is all the

issues of not being previewed and stuff, but we are

all familiar with that process and know how it

works.

What can you tell us to guide us? Should

we try to go drug by drug specific? How do we set

our evidentiary standards when we talk about class

effects where in some cases, we are just not going

to have a lot of data here?

DR. GRAHAM: Right. What you are going to

be getting now, of course, is my opinion, not FDA\'s

opinion. Probably if you were to talk to Bob Temple

or John Jenkins, or anybody else, everybody is

going to have a slightly different answer.

What we talking about now I think to some

extent is philosophy, so what that preamble, first,

I believe based on the evidence that there is a

91

COX-2 effect and that that COX-2 effect is dose

dependent, and that we see evidence of that with

rofecoxib, with celecoxib, and with valdecoxib.

The difference between rofecoxib and the

other two coxibs on the market is that a safe dose

for rofecoxib wasn\'t identified, the dose wasn\'t

low enough. That raises a question in my mind

about what is an appropriate therapeutic index for

a drug.

I am giving you my opinion now, but when I

listened to Dr. Cryer\'s presentation yesterday, the

bottom line conclusion I came to at the end of that

was there really doesn\'t appear to be a need for

COX-2 selective NSAIDs based on what I heard

yesterday. There is probably other information out

there why I am wrong, but that was the conclusion I

came from.

So, in any event, that is answer one. I

believe there is an effect and it\'s dose related,

and with celecoxib and valdecoxib, I think we have

evidence. You said before we have a good

evidentiary base based on clinical trials for the

92

COX-2s. I would challenge that in the sense of the

survival curves and the things that I talked about

there, that we have a very weak evidentiary base

for things like protective, you know, is there a

grace period for use, and also on the dose issue,

we really don\'t have a great evidentiary base. But

that being said, you understand me.

Now, for the non-coxib NSAIDs, my own view

is that as an epidemiologist first, I try to report

the phenomenon I observe and leave it to brighter

minds to figure out why what I observed happens.

You are asking me sort of what do I think

is happening underneath it all. I am attracted to

the COX-2 hypothesis personally. Dr. Gurkiepal

Singh, my colleague and co-author in Medi-Cal, he

has a different view on that, but I think that we

can these in vitro tests that say, oh, this is the

COX-2 selectivity of this NSAID, you know, in a

test tube.

What happens in the human body could end

up being surprisingly different. We saw yesterday

that the dynamic response of these differences,

93

that the platelet effect is very quick, the

thromboxane effect is a very quick effect, the

prostacyclin effect seems to be a more gradual

effect, that this creates very complex interactions

that ibuprofen, that any of these drugs could, in

the end, end up with a deficit, a prostacyclin

deficit that results.

I think Dr. FitzGerald showed that slide

yesterday with the normal distribution of the time

area under the curve and then this little sliver

where they are not protected, and that may be the

reason why, for these different drugs, that we end

up with these different relative risks and these

different odds ratios.

In the end, for the non-selective NSAIDs,

my own advice would be let\'s look to see are there

somewhere in studies\--it is going to be

observational studies\--in observational studies

that we believe have been reasonably well done.

By \"well done,\" here, they have to be

large. The literature is full of really small

studies. I mean I could have presented Meloxicam

94

studies, 5 patients, no risk. Well, da, you know,

you have got a confidence interval that goes from

zero to infinity. They need to be large. Look in

a systematic way to identify what the body of

evidence is.

Can we identify bad actors? I believe

indomethacin, for example, is clearly a bad actor,

and if people looking at the data concluded that,

take appropriate action, weed the garden of the bad

actors.

Try to identify drugs that based on the

evidence we have, appear to be less risk in the

totality of their evidence, looking for consistency

study to study to study, and then, in a rational

way, suggest these are the drugs we think that the

public should use, and these other drugs, well,

then you have to decide do you want them on the

market or not.

I am not really going to comment on that,

but I think that is the approach I would take. I

would be trying to sort of identify right off the

bat the bad actors and let\'s get rid of them.

Things that look like they may actually be

safe, and when I say \"safe\" now, I mean that they

don\'t appear to have cardiovascular risk, identify

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them and shift the market towards that, and then

deal with the others.

DR. WOOD: Dr. Friedman.

DR. FRIEDMAN: Thank you. Several

comments. First, as both Dr. Graham and Dr. Platt

have mentioned, observational studies are

essential, but they have a number of limitations,

and because of those limitations, it is easy after

the fact to critique away those whose results you

don\'t much care for as we have seen.

But a couple of other points. One, can

these particular drugs, their primary use, we are

dealing with chronic conditions, conditions that

last years, sometimes many years, and so the drugs

are intended for use over those many years

potentially.

Yet, most of the clinical trials we heard

reported yesterday are 12, 18 weeks, a few of them

go longer. You mentioned that one of the reasons

96

we didn\'t see the problems early on may be numbers,

and I agree that is potentially it, but the fact is

we didn\'t see problems arise in the studies until

14, 18 months.

We often see analyses by patient years of

exposure. In this particular setting, I don\'t know

whether patient years are always equal to patient

years, and therefore, I guess I would say why

aren\'t we doing more bigger, longer randomized

clinical trials for these chronic conditions?

DR. GRAHAM: I am not speaking for the

agency now.

DR. WOOD: We got that. Don\'t say it each

time.

DR. GRAHAM: Okay. I think they are

incredibly expensive and companies don\'t want to do

them. There is not an incentive for them to do

them, and you would have to talk to the people from

the new drug side of the house, but the fact is

that they are not requiring them.

So, that is a very legitimate question.

You know, working as an epidemiologist, we try to

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make do with what is, and so we use the

observational data. You are going to get better

quality data if you are able to do this, but just

to give you a sense of the size of the studies that

I think you would need to do, I mean you talked

about before that you have the APPROVe study and we

see no effect until 18 months, but there was study

090 that was talked about briefly by Dr. Villalba

yesterday. It was a 6-week study at 12.5 mg, and

it showed a difference, the suggestion of a

cardiovascular risk within the 6-week study at the

lowest dose. Now, it\'s a small study, as well.

But I am just saying that to say that I

think the epidemiologic data, in my mind at least,

answers the question about when the effect begins.

The question is if you want to have\--this is the

philosophy\--how much certainty do you need to make

a decision.

Right now, when it comes to efficacy, the

effect, does the drug work, you are looking at the

lower bound of the confidence interval, and you

want to see is that different than 1, because if it

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is, then, I will conclude with 95 percent certainty

or greater that the drug actually has an effect.

When it comes to safety, you are doing the

same thing. You are looking at that lower bound.

You want this 95 percent certainty that the drug is

harmful. You are presuming that the drug is safe

rather than let\'s presume we want to do no harm to

patients.

Let\'s start off at the beginning assuming

that the drug isn\'t safe, and we want to have a

certain level of confidence about how bad this drug

could be, and that is still tolerable to us. We

want to cap the risk. It will be a completely

different way of looking at studies for a safety

perspective, one that actually gives a priority to

safety and it maximally protective of patient

safety, just as that high standard for efficacy is

maximally protective of patient safety, because by

keeping drugs off the market that don\'t work, I am

protecting patients from unsafe drugs, and if I

have pneumonia and I am given a drug that doesn\'t

work, well, I get a harm from that.

But that\'s philosophy, and I think it\'s an

outcropping, it\'s a development, a natural

extension of the development of clinical trials in

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the United States where the focus has always been

on efficacy.

DR. WOOD: Let\'s try and keep both the

questions and the answers reasonably short,

otherwise, we will be here until after midnight.

DR. GRAHAM: I apologize.

DR. WOOD: That\'s okay. Let\'s go on to

Dr. Elashoff.

DR. ELASHOFF: First, I have one comment

and then one question. In terms of confounding,

just because you put a lot of variables in some

model doesn\'t necessarily mean that you have

adequately removed the confounding effects even of

those variables.

The second has to do with Dr. Graham\'s

slide 13, the excess population risk. I note that

the Ingenix data has been left out of the bottom

category.

DR. GRAHAM: That\'s right, because for the

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high dose.

DR. ELASHOFF: Yes, but the negative sign

needs to be on the slide, otherwise, it\'s a biased

presentation.

DR. GRAHAM: Well enough. I take that

correction. Okay, fair enough.

DR. WOOD: Dr. Bathon.

DR. BATHON: Yes. As we weigh the

risk-benefit ratio of these drugs, one

consideration is that there are subgroups of

patients in which the benefit might outweigh the

risk possibly.

With that in mind, it would be helpful for

us who are not cardiologists or epidemiologists to

be able to put the relative risks that we have been

seeing over the past day or two in context with all

the cardiovascular risk factors that exist.

So, for example, if you were take the

presumed relative risk of rofecoxib of 1.5 to 2.0,

at least at the higher dose, and put it into some

context for us of the 20 to 40 cardiovascular risk

factors that exist in a sort of rank order, where

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would you put the COX-2 drugs?

DR. GRAHAM: For the high dose it would

be probably more significant than smoking or

diabetes or hypertension, maybe more important than

the combination of several of those factors in a

patient. For the lower dose, it is probably more

than hypertension, a little less than diabetes, and

a little less than smoking.

I know, David, you know the cardiovascular

risk factors much better than I do, and so does Dr.

Hennekens, but that would be my ballpark on that.

DR. WOOD: Dr. Abramson.

DR. ABRAMSON: Yes. I want to go back to

the question Dr. Shafer asked about if these

classes of drugs or this group of drugs could be if

there was a hierarchy of risk, and you first

answered that you thought the coxibs were more

risky, but I would challenge you a bit simply on

your own presentation.

I would like you to discuss your data,

because you then went on to talk about how

indomethacin has a risk, Meloxicam has a risk.

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Based on your data, the message that came through

is that there was a dose response risk for

cardiovascular outcomes, that we saw it within the

coxibs, but we also saw it where the data were

available in the non-selective NSAIDs.

There are data that we have seen that

ibuprofen might increase risk. We didn\'t talk

about the McDonald and Way paper that in

cardiovascular discharge patients, people given

ibuprofen had a higher mortality 2-fold.

So, as the smoke clears, I am not sure

that the simple answer that the coxibs were

different was actually supported by your data, nor

your ultimate explanation. Can you defend that?

DR. GRAHAM: I think you are accurate.

What I was saying was I was referring, I think, to

the underlying COX-2 hypothesis and that it is

clearer, I believe, and, well, maybe it\'s an

overgeneralization, because we have the n that we

are viewing is so small, that looking at rofecoxib

as sort of the example where we can see very

clearly the dose response at all the levels and its

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progression, and understanding its mechanism of

action, and then seeing similar things with

celecoxib and valdecoxib.

I think what you are saying is fair.

Maybe a better thing to say is, in the end, that

you do need to look at it drug by drug.

What I was saying, though, in that answer

that I gave to Dr. Shafer, I was really talking

more about sort of the COX-2 mechanism and the

coxibs as being, in quotes, \"COX-2 selective,\" but

I think your observation is correct.

DR. ABRAMSON: Add to that, that although

there is a hazard that we don\'t accomplish a lot by

simply saying the class of NSAIDs may have risk, I

think we have under-appreciated that over the last

10 years.

It is not that different from the

mid-nineties recognizing that there was a class GI

effect of these drugs, and that compared to

placebo, whether it\'s hypertension or long-term

potential adverse outcomes, this is something that

doctors have to be aware of, even the simple thing

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of checking blood pressures when you put people on

any nonsteroidal drug.

So, I don\'t know that it is necessarily a

bad outcome to call attention to this class effect

until we get better information on each of these

individual drugs.

DR. WOOD: Dr. Day.

DR. DAY: I have a comment about recall

bias and reverse recall bias. There is a huge

research literature on how memory works both in the

laboratory and in the every-day world, and there

are two phenomena that have been very heavily

studied that I think might be relevant here.

One is called flashbulb memory, and the

idea is when an emotional spectacular event

happens, such as when you first learn that JFK had

been shot, or the Challenger blew up, or the World

Trade Center had been hit, it is as if the old-time

flashbulb from an old-time flash camera went off

and captured all the details, and you remember all

of those details forever afterwards associated with

the event that you might otherwise have just not

105

even noticed or forgotten.

So, there is a lot of research on

flashbulb memory that shows many of those details

are indeed correct, but some are notoriously false.

For example, there are accounts of people who

remember a certain even with great emotional

aspects to it, and they remember listening the

world series when so-and-so is pitching and it was

the bottom of the 9th, da-da-da, all these details,

and when you go back and check the evidence of what

was going on, on that day and time, that particular

game was not on.

So, that phenomenon number one, flashbulb

memory, and the second is eyewitness testimony.

How you ask a person a question will affect what

answers you get. So, if you have in the courtroom,

someone who has witnessed a car accident, if the

lawyer asks this witness, \"Did you see the broken

glass,\" then, the witness is more likely to say yes

than if you ask, \"Did you see any broken glass,\"

because the broken glass presumes that there was

some, and so forth.

So, I take your points seriously about

potential recall bias and reverse recall bias, but

we would have to look at both, whether there is an

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emotional component or not. Those who have had an

MI, for example, would have that most likely, but

also how the questions are asked in these surveys,

and it is not trivial how you ask people questions

about were you taking any medications or were you

taking medication X, and for how long, and what was

the dosage, and so on.

So, I don\'t think that these details are

always published with the studies, and I would like

to encourage people who ask people about their

experiences with drugs, take a look at the memory

literature for some of these points.

DR. WOOD: Dr. Gibofsky.

DR. GIBOFSKY: Dr. Graham, I am wondering

if you separated out your populations based on the

indication for which they were taking the drug. I

ask that because we heard yesterday, and it\'s well

known, that rheumatoid arthritis is itself a risk

factor for cardiovascular disease, and higher doses

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of coxibs, in particular celecoxib, are usually

given to patients with rheumatoid arthritis as

opposed to osteoarthritis.

So, I am wondering if you look at that in

your breakdown.

DR. GRAHAM: Several of the studies that I

reviewed have looked at the indication, but in

automated claims data, it is very difficult to be

sort of be sure does the patient have rheumatoid

arthritis, and there are different algorithms one

could use, but in general, what has been found in

the studies where they have looked at that, that

the prevalence of rheumatoid arthritis in the study

populations has been low, very low, and that its

impact on the results when they adjusted for it

didn\'t materially affect things.

Now, in the California Medicaid study, one

difference in that study was that our base

population was limited to patients who had

diagnoses of osteoarthritis or rheumatoid

arthritis. Now, these are diagnoses, and so does

that mean that they really had osteoarthritis or

108

rheumatoid arthritis, I don\'t know, but when we did

try to eliminate in that study at least were the

people who might be using an NSAIDs for a muscle

injury, a short-term complaint as opposed to a

chronic illness.

In none of those does the presence of

rheumatoid arthritis seem to affect things, but

again I think the prevalence is pretty low in all

of these studies.

DR. GIBOFSKY: One quick question for Dr.

Platt, if I might. I need to understand the

concept of survivor bias somewhat in that I think

there is a difference between a patient who is

drug-naive, then put on a drug, and then an event

happens versus a patient who may have seen a drug,

perhaps seen another drug after that, 3 or 4 agents

of the class, and is then switched to another agent

and something happens.

I think we have talked about remote versus

current, but there is also this issue of sequential

effect, and I am wondering how you deal with that

as a survivor, particularly because of the paper we

109

saw a few weeks ago in the Archives suggesting that

discontinuation of an NSAID may itself be a risk

factor for a thrombotic event.

DR. PLATT: Your point is exactly right.

I think that the concern about survivor bias is

that if we think that some people are particularly

susceptible, which is almost certainly the case,

then, if we start the clock after a person has

already been exposed to a drug or to one that has

the same effect, then, it is very much less likely

that those individuals will have a problem.

That may be the explanation, for instance,

for the reason that the literature was so badly

wrong about postmenopausal estrogens and heart

disease, that most of the epi studies started with

prevalent users.

I think the majority of the studies that

we were reviewing here, these were individuals who

are known to have had at least a year of prior

experience without exposure to the nonsteroidals.

Your study in Kaiser I know was an

exception cohort at least with regard to a year of

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prior history, but I am not aware that any studies

have a longer drug-free prior interval than that.

DR. WOOD: Dr. O\'Neil, do you want to

comment particularly on this?

DR. O\'NEIL: Yes, this is an important

point and a lot of things have been covered in

Richard\'s and David\'s presentation, but one thing I

think that is relevant that Richard did not cover,

that is, the value of a randomized trial, is the

ascertainment and follow-up, and knowing the status

of individuals in the sense of who goes off therapy

and how long they stay on therapy.

That is very critical relative to the time

dependency of the risk. It was mentioned, for

example, the use in the observational sense of

recent and remote and current use. Those are all

terms that are nice, but they don\'t get at the

issue that we are trying to get at with regard to

the clinical trials, and that is essentially when

does time zero start for you.

So, I think the appropriate question to

ask is what is the duration of exposure since your

111

initial exposure to the drug, because I think that

is very relevant to the interpretation of the three

clinical trials that we have, two of which are in

placebo-control populations.

There is a rofecoxib-naproxen control

trial for one years, there is a placebo-control

trial in polyp prevention for three years, and

there is a placebo-control trial in Alzheimer\'s

disease for four years, and the time dependency

from time zero matters as you have seen in the

plots.

It is relevant to the excess risk

calculation. So, I would ask the committee, as

well as I would ask David, of the observational

studies that you have reported, how many of them

are cohort studies, and how many of them are able

to identify new initial use, and then track

continued use for that individual, so that one

could look at the relationship between the hazard

rates and the hazard ratios that we are identifying

in the randomized trials and match that to the odds

ratios that are being reported in the observational

112

studies.

DR. GRAHAM: On one of my initial slides,

you can see what the cohort studies were, and in

some of the nested case control studies, you are

also able to get the time on drug. Actually, in

Wayne Ray\'s cohort study, most of these cohort

studies include prevalent and incident users, so

they will do what is called a \"new user\"

subanalysis, which is to try to get to this issue

of when does time zero begin.

We addressed that problem in our study

here by the inception cohort design in our base

population, so that we can identify what time zero

was for the cases.

Now, none of those studies presented data

in the form of a survival analysis, which I think

in the end, that is what Dr. O\'Neil would like to

see.

DR. O\'NEIL: No, my question is not so

much in survival. I don\'t believe, and again that

is why I am asking you, I don\'t think any of those

studies were designed or able to capture the

113

question I am asking.

In fact, if I am not mistaken, in the

Wayne Ray study, he defined new use, but he did not

define any time from new use, which is essentially

critical to when those risks start.

DR. GRAHAM: That study isn\'t cited as one

of the studies where we are able to derive that

information. This slide was a slide that I

presented to show that from the epidemiologic

literature, those studies where the investigators

had identified when time zero began for rofecoxib

use, and they didn\'t present the data as a survival

analysis, but they identified when time zero began

and then, in various ways, showed you either what

the distribution of the cases were, so that you can

see that it was impossible for the risk to have

been delayed for 18 months, because nobody in the

study used the drug for 18 months, or they parsed

time out and looked at the first 30 days of use

from time zero, and found the risks that they found

down here.

But you are right, those studies aren\'t

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designed that way, and we haven\'t had time in our

Medicaid study to do these analyses yet, but we

have the data to now do the cohort study and time

to event, so we will have an opportunity actually

within the data to actually compare and look to see

exactly the question you are driving at.

But I would say that from the published

data, in each of these studies, time zero for

rofecoxib was identified and in some way or

another, information that I think could be useful

to the committee in establishing when does risk

begin was contained in those studies.

DR. O\'NEIL: Well, the other point here,

which is the value of clinical trials, and it was

the question that was discussed yesterday with

regard to the intent-to-treat analysis, and that is

to say to analyze all outcomes once randomized to

the trial regardless of whether you want to track

the individual to 14 days post-exposure.

You can\'t really maybe get access to this

information in the observational studies. That is

a conjecture, but it\'s one or the other biases, and

115

it was interesting to the comment, whether one

would believe this or not, that discontinuation,

discontinuation from an NSAID alone raises risk.

If that were to be the case, that is a

different analysis altogether.

DR. GRAHAM: In that actual paper, it

could be that people were discontinuing the NSAIDs

because they were having chest pain and it was

being interpreted as dyspepsia or something, and

then they go to have their infarct.

I mean you are right about that, but this

is the nature of how epidemiology is done, and I

can\'t change it. I didn\'t make the rules, I am

only following them. Nobody is arguing that

clinical trials, if they could be large enough,

that they would give all of us answers that we

would have greater comfort trusting what they are

saying.

What I am proposing is that we don\'t have

that kind of data in the clinical trials. As large

as the clinical trials are, for the questions that

this committee is facing, you don\'t have the data

116

you need, and what I presented is the epidemiologic

data, and it is imperfect and it has its warts, and

that is why I would emphasize looking at

consistency and trying to sort of derive from that

a general sense.

I mean does it make pharmacologic sense

that you would have an 18-month delay? I mean I

guess I suppose it depends on what you think the

mechanism of action is for the underlying disease,

but even in the clinical trials, study 090 was 6

weeks long, 12.5 mg, and it had a cardiovascular

effect.

DR. WOOD: I am happy to facilitate a

discussion among the FDA, but I think we would

rather hear from the committee right now. Dr.

Farrar, you are next.

DR. FARRAR: I think that the

recommendations of the committee tomorrow are going

to depend on the assessment of the overall risk and

the overall benefit of this class of drugs.

As a researcher and after all the data

that has been presented, I am more than happy to

117

accept the fact that there are serious risks even

of death from taking NSAIDs. In fact, though,

there are serious risks in taking any medication at

all.

For some of the NSAIDs, it is

cardiovascular risks, for some of them it is

clearly GI bleeding. As a doctor, though, who

takes care of patients, I know that treating pain

or not treating pain and not treating the

disability of arthritis also has very serious risks

even of death.

Given the extensive work that you have

done, on the risk of both the cardiovascular and

the GI bleed, I wonder what level of risk is

acceptable you, and remembering that the only other

drugs that are really available is analgesics or

narcotics, and the only other drugs that are really

available in terms of limiting inflammation are

biologics or immunosuppressants, I wonder what drug

is safe enough that you would recommend that I

actually would be able to use it in patients to

prevent some of their suffering.

DR. GRAHAM: Well, I am not going to give

a product endorsement. A couple of things, though.

DR. WOOD: Try and make it brief.

118

DR. GRAHAM: One, the benefits of the

treatment for the traditional NSAIDs compared to

the COX-2 selective NSAIDs with GI bleed, we have

clinical trial evidence that suggest that there may

be a difference, but here, to me, is an anomaly.

Rofecoxib got the indication for being

GI-protective, celecoxib didn\'t based on the

clinical trials data you guys looked at yesterday.

There are two published studies in the

literature looking at what I would say is actual

benefit. There, they were looking at

hospitalization for GI bleed\--they didn\'t look at

death from GI bleed, but I wish they had\--but

hospitalization for GI bleed, and what they found

was, in both of these studies, that celecoxib was

actually more beneficial, you know, lower rate of

hospitalization for GI than rofecoxib. So, that is

the population, two large studies.

You have got your clinical trials that

119

would have said it should be the reverse. So, I

throw that out as one sort of conundrum.

The second is that I don\'t think that the

actual benefits of these drugs are understood well

enough to sort of try to weigh these very well.

The case fatality rate for myocardial infarction in

the United States approaches 40 percent. The case

fatality rate for hospitalized GI bleeding is

probably somewhere around 5 or 10, it is a much

lower case fatality rate.

Nobody that I have seen anywhere has sort

of worked this out very well, so I would submit to

you and to the committee that you actually know

very little about the actual population benefit of

any of these products.

DR. WOOD: I don\'t think we are going to

get an answer to that question, so let\'s move on.

Dr. Nissen.

DR. NISSEN: Let me briefly answer the

earlier question about what does the hazard ratio

of 1.5 to 2 mean. Before I came to the meeting, I

made a point to look this up, because I thought it

120

would be very relevant.

It is equivalent to raising a cholesterol

from 200 to 260, or taking up smoking. Another way

for the committee, I mean as a cardiologist I have

to deal with this all the time, the most effective

drugs we have for prevention of morbidity and

mortality are statins, and they reduce risk about

35 percent.

So, a hazard ratio of 1.5 to 2 is really a

very, very big effect when you are talking about

the most common cause of mortality, and that is why

this discussion is so important.

Now, my question is this. We are going to

be asked to balance risk and benefit, and so the

magnitude of the hazard ratio is very important to

all of us, and I am trying to reconcile what we see

in the randomized control trials with, let\'s take

rofecoxib for a moment, where it looks like the

hazard ratio in the randomized trials is in the

range of 2, 3, 4, maybe even higher, and in the

observational data it is significantly lower.

I would like to propose a hypothesis to

121

you and just ask you if you think this is right.

In your observational data, you are looking at

mostly short-term exposure, so you are looking at

less than 12 months typically of exposure.

It may well be that the hazard increases

over time, so that by the time you get to 18

months, you can actually see it in a much smaller

randomized trial, and so it doesn\'t rule out the

possibility that, in fact, both observations are

right, that, in fact, there is an early hazard, but

that early hazard has a smaller hazard ratio than

the hazard at 18 months or 24 months or even 36

months, and if we ever were to look out 5 years, it

might still be increasing.

Do you think that is a reasonable

hypothesis?

DR. GRAHAM: I think more likely it is,

that in your clinical trials, early on you don\'t

have enough power to distinguish the risk. The

hazard is the same, but the lines are closer

together, because we are closer to the origin.

I think one other explanation for the

122

lower risk ratios in observational studies, I would

think is more likely due to misclassification of

exposure and misclassification of outcome. It is

likely to be nondifferential, so it would tend to

reduce the odds ratios and relative risks towards

1\.

Exposure, because people are going to take

it, a lot of these people are taking it on a prn

kind of basis. In a clinical trial, you have a

greater certitude that they are actually taking it

every day. That introduces a lot of

misclassification, so the a priori hypothesis going

into an observational study, with misclassification

going on, you are fighting an uphill battle to see

an effect.

DR. WOOD: We have got lots of people who

want to ask questions. I want to make sure that

the people who are asking questions have questions

they want to ask for clarification of the speakers

who have spoken rather than just general points.

Dr. D\'Agostino.

DR. D\'AGOSTINO: I have a couple of

123

questions along the way here. I have spent a good

part of my career in the Framingham Heart Study,

and it\'s an epidemiological study and a cohort

study, and we take joy when somebody runs a

controlled trial on hypotheses and then later on

confirms it.

The first question is I am concerned that

even though you have gone through this careful

analysis, your conclusions are no apparent effect,

probably increased effect, probable increased risk.

They really don\'t help us in the sense of pinning

things down. We have a couple of very strong I

think good studies, the APPROVe study and the APC

study as placebo-controlled trials.

Tell us quickly where is the weight of how

we should look at these two pieces, the controlled

trials we have versus what you have produced.

DR. WOOD: Really quickly.

DR. D\'AGOSTINO: Really quickly, it can be

done quickly.

DR. GRAHAM: My belief is that for the

controlled clinical trials, for the levels of risk

124

that we are concerned about, that they do not have

the statistical power early on to show risk

differences.

DR. D\'AGOSTINO: I think Bob O\'Neil\'s

comment is very important here.

The other two points, and again I will

make them quick, I am very concerned about the high

dose effect you have, and I am really concerned

about the MI and the number of cases. I mean blood

pressure, cholesterol, diabetes, smoking, this is

what drives people to have heart attacks and what

have you, and that is completely missing on your

assessment of how many new cases, so I guess it is

more of a comment that I am really concerned that

that sheet needs sobering interpretation.

DR. GRAHAM: But it was based on the odds

ratios and relative risks where those factors were

adjusted for, so as well as they are adjusted for,

that is what the projection represents, the excess

after adjustment.

DR. D\'AGOSTINO: Yes, but I mean the

comment was made by you, throwing in the analysis

125

doesn\'t necessarily adjust for them.

The last one, you made a very nice point

about the cardio-protective effect, and you tried

to show that these uses, and what have you, somehow

or other all have the same risk, and your

interpretation that there must be some confounding

going on, why doesn\'t that hold for all the studies

you gave, why don\'t that hold for the Solomon

study, which you thought was a great study, yet,

this one result you don\'t like?

DR. GRAHAM: For what, the Kimmel study?

DR. D\'AGOSTINO: Wasn\'t it the Solomon

study that had the naproxen as the

cardio-protective?

DR. GRAHAM: That is because the cardio

protection was present when they were on the drug

and when they weren\'t on the drug.

DR. D\'AGOSTINO: I understand what you are

saying, but if that\'s a problem, then, it means

there is some confounding going on.

DR. GRAHAM: No, it\'s selection bias.

DR. D\'AGOSTINO: Well, it\'s selection

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bias, but why isn\'t it for the whole study? Why do

you throw out a result you don\'t like and keep all

the results you like?

DR. GRAHAM: No, that is not what I did.

I pointed out a result where they showed the

presence of the selection bias. In other studies,

the Ingenix study is the only other study that

looked at this. I don\'t have a slide of it.

DR. D\'AGOSTINO: I don\'t know if it\'s a

selection bias or misinterpretation of the data.

DR. GRAHAM: Well, to me it looks like

selection bias.

DR. WOOD: Let\'s continue that

conversation later.

Dr. Morris.

DR. MORRIS: David, would you go to slide

14\. That is the risk, the duration of use. I

think one of your points was that if you look at

your study, tell me if I understand this right,

that with the lower dose, that the median time to

an AMI is sooner than with a higher dose, did I

understand that right?

DR. GRAHAM: Yes.

DR. MORRIS: A month?

DR. GRAHAM: Had more cases, a greater

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proportion of our cases, but the other thing is

remember, down here, we are talking about 18 cases

or so. The N here is small, the N here is like 58,

and the N here is 10. So, I wouldn\'t read too much

into the difference.

The more important point is that at the

low dose, nobody was out there beyond 18 months, so

all the action happened before 18 months, and the

same for the others. I see what you are saying. I

can only say that is what our data were.

DR. MORRIS: One interpretation is what

you said earlier, that for this particular drug, we

are talking about, as you said, no safe level. I

was wondering if that is the way you interpreted

it, that because we are talking about Vioxx here,

and there is no safe level, that something is going

to happen sooner, or is it something with the

populations are different.

DR. GRAHAM: The populations could be

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different, but I think, you know, you would expect

the higher dose to have a shorter latency to onset

than the higher dose, but the numbers are so small.

DR. MORRIS: Okay, it\'s a small number

problem.

DR. WOOD: So, the answer is too small

numbers at high dose.

Dr. Boulware.

DR. BOULWARE: I just want to make sure I

understand something that you had proposed in your

excess population risk slide, if you would put that

back up.

As a rheumatologist, I use these drugs in

a population much greater than what you have here

with a 65 to 74 where the risk of an MI is fairly

high in that group.

Did you want us to believe that this

excess risk that you are proposing would be

extrapolated to other population groups, too?

DR. GRAHAM: Well, no.

DR. BOULWARE: Do you have any numbers

that may demonstrate that?

DR. GRAHAM: Well, the answer to the

second is no. This was an example in conversation

with people planning the talk, to try to help

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people connect with what it means.

Cardiovascular risks go up. I mean in the

next age group higher, the risks are higher. In

the age groups lower, they are lower, but

cardiovascular risk begins to increase in the 40s.

DR. BOULWARE: I understand, but it

wouldn\'t be a linear type of thing.

DR. GRAHAM: No, the background risk isn\'t

linear, the relative risks, though, are adjusted

out.

DR. BOULWARE: Because one of the

questions we will be faced with is are there

subpopulations or groups that these may be safe in,

and I just want to make sure I understand the

relative risk in different age groups.

DR. GRAHAM: Nobody in any of the studies

where they have looked at it have reported effect

modification, which would be that the level of risk

differs at different ages.

DR. BOULWARE: One more question here. I

want to make sure I understand. I think I heard a

comment that says when the risk approaches

2.0\--maybe I just assumed that you said this\--that

it was an unacceptable level of risk.

Is there ever a case where a drug may have

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a clinical benefit in which that risk is

acceptable, because for the patients I see, not

giving them any of these drugs will confer a great

deal of risk on them, and physical impairment, and

we have studies that show that the functional

classification of rheumatoid arthritis patients

carries with it a significant mortality as that

class goes up?

DR. WOOD: I think that is a question for

the committee to answer rather than Dr. Graham.

Let\'s move on to Dr. Cryer. Do you have a

question?

DR. CRYER: I do. The comment and

question I have of Dr. Graham addresses an issue

that I think is an important difference between the

observational studies and the prospective studies,

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and this difference relates to assessment of drug

compliance and missed doses, and I think it is

critical as it relates to assessing drugs which

potentially affect platelet function.

A huge difference, as you know, between

aspirin\'s effect and every other NSAID including

the COX-2 inhibitors, is that with the non-aspirin

NSAIDs, as soon as you remove the drugs, whatever

potential effect they would have had on the

platelet are immediately reversed.

So, with naproxen specifically, my

preconceived bias, which may be wrong, but my

preconceived bias based upon everything I know

about the pharmacology and the things that Dr.

FitzGerald has reviewed for us, is that it should

have some mild anti-platelet effects which would

only be present when the drug is on board in the

system.

So, the specific question is, in the

observational studies, recognizing that in clinical

practice people miss doses of their NSAIDs, they

are not taking their NSAIDs consistently, how do

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you account for the missed doses in the

observational studies recognizing that this could

potentially lead to a mitigation of whatever

negative effect or positive effect that they may

have?

DR. GRAHAM: It ends up being

misclassification. Generally, what that means is it

will force the observed level of risk, the relative

risk of the odds ratio closer to 1. So, if we had

an increased risk, it would make it lower, if we

had a protective effect, it would sort of make it

higher, closer to 1.

DR. CRYER: Right, we agree on that. The

specific question is, is there a way to actually

recognize or to account for when people do not take

their doses in the observational databases?

DR. GRAHAM: No, there isn\'t, so when you

are studying, say, an increased risk, that is why I

said if you find something, you have to realize you

found it despite the misclassification.

DR. WOOD: Okay. Dr. Domanski.

DR. DOMANSKI: I will save it for

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tomorrow.

DR. WOOD: Okay, great. Dr. Furberg.

DR. FURBERG: No.

DR. WOOD: Okay, great.

Dr. Temple, who does speak for the FDA.

DR. TEMPLE: I am just asking questions.

A couple. Actually, one point is it seems to me

that since we expect that people are going to be

getting one drug or another, comparisons with other

NSAIDs seems like as good a comparison as we should

make. You might want to leave out indomethacin if

you are worried about it. That\'s one thing.

I guess my main question, though, is

everybody has paid appropriate lip service to the

idea that very small differences are hard to

interpret in epidemiology.

People have said 1.5, 2. Actually, I

notice in one of his editorials, Dr. Furberg cited

a paper of mine where I said anything less than 2

really needs a lot of questions. Jerry Cornfield,

who sort of invented all this stuff, used to say 3.

Well, we are talking about differences

134

here that are 0.1 differences, not that they

wouldn\'t be hugely important if they were true,

that is absolutely true. So, I guess I want to

know what Richard and you make of all this, because

the numbers are very small, and yet, just as an

example, there is a very great consistency that you

cite that celecoxib looks sort of okay, but you

found one study where there is a little hint that

maybe the higher dose is a problem, and since

probably we all think dose response is likely, that

looks good to you.

DR. GRAHAM: Two studies, there were 2.

DR. TEMPLE: Okay, 2. The valdecoxib

data, which shows nothing, doesn\'t look so good

because we probably all believe that there is

likely to be a class effect.

What I am asking is, with numbers like

this, how do you know what to do with them? That

seems very fundamental for the epidemiology.

DR. WOOD: But, Bob, there are 4

randomized clinical trials here, and your comments

don\'t apply to them, I assume.

DR. TEMPLE: No, they don\'t, although they

are not perfectly consistent either. But, no, I am

asking, what do we make of differences of this

135

magnitude with everybody having given lip service

to the idea that small differences are hard to

interpret, and yet we seem to be enthusiastically

endorsing them, so I just want to know what Richard

and David think about that.

DR. GRAHAM: Rich, do you want to go

first?

DR. PLATT: I think we have to be cautious

about how we interpret it, so I would say the

finding of a relative risk of 3 in an epidemiologic

study, as David found, is meaningful\--

DR. TEMPLE: For high dose rofecoxib.

DR. PLATT: For high dose rofecoxib.

DR. TEMPLE: I would not dispute that at

all.

DR. PLATT: It seems to me that in that

context, that a dose response effect, that the

information about lower doses gains weight by

borrowing from that. I think that is also worth

136

keeping in mind when, in other studies that are

working in that range that make us all nervous,

there appears to be a dose response effect.

It is the kind of consistency that makes

the study, in my mind, be worth more attention. I

think there is something to be said for giving more

weight to relatively small excess risks if they are

seen in a number of different environments when we

can\'t have good reason to think that there is a

similar kind of biases that might be contributing

to it.

After that, I agree with you. We are in

relatively difficult terrain. I think that it is

not the same as no data, though. I think we ought

to distinguish between the situation in which we

have no evidence from ones in which we have

relatively weak evidence.

We didn\'t talk at all, for instance, about

the enormous number of spontaneous reports of

myocardial infarction following exposure to

nonsteroidals. There are thousands and thousands

of them. In my mind, they don\'t contribute at all

137

to the discussion, whereas, I think these need to

be weighed in the mix when we don\'t have clinical

trial information to depend on.

DR. GRAHAM: My answer is similar to his,

but I think that what you are identifying is, is

that we are hitting or at least right now the

frontier is the limits of what the available tools

we have to define the levels of risk that we are

talking about.

We are talking about small levels of risk

that turn out for this particular event to be

enormously important in a population level. If you

are talking liver failure, we wouldn\'t be having

this conversation. For that reason, it becomes

important and what I would say is sort of

emphasizing what Rich said, is I would be looking

for consistency across different studies, and if I

found a number of studies, say, as with Indocin,

for example, to me, that is more persuasive.

If I found a number of studies that

pointed to a particular set of NSAIDs that seems to

have low risks, I would take comfort in that in the

138

absence of perfect information. I mean some light

in a storm is probably better than no light In a

storm.

DR. TEMPLE: I take it if the differences

were at the level of 10 percent, 1.1 versus 1.2\--

DR. GRAHAM: I am thinking more in a very

qualitative sense of things that they seem to

cluster around 1. I mean 1.1 for ibuprofen, it

could be that, for example, may naproxen increases

the risk 3 percent in the real world, we are never

going to figure that out, maybe ibuprofen increases

it 10 percent or 15 percent, maybe we could figure

that out, I don\'t know, but there is going to be a

place where qualitatively, if we see enough studies

kind of sort of pointing to the same place, you

know, most of them, they are not all going to say

the same thing, there is going to be these

conflicts, just like we have in clinical trials

data.

But if most of the compass arrows are sort

of pointing in the same direction for particular

NSAIDs, I think those are the ones that at least

139

that I sort of place on a suspect list.

DR. TEMPLE: So, very low hazards need at

least multiple support before they are credible.

DR. GRAHAM: I think so, and I think that

you want to try to encourage to collect that

information sort of to test that out.

DR. TEMPLE: Alastair, could I take half a

second to answer a question Larry raised before?

DR. WOOD: Sure, a second.

DR. TEMPLE: Well, it\'s a very good

question, you know, if the drug is going to be used

forever, why don\'t you study them forever. The

only thing I would point out here is that what sort

of started people thinking was VIGOR, and VIGOR

didn\'t take 3 years to show anything, it showed up

in 9 months.

So, what you have seen is for, say,

lumiracoxib, a humongous study of about the same

length, but, of course, they didn\'t know about

APPROVe, did they, and whatever you think APPROVe

means, whether Bob is right that it\'s late, or

David is right that there weren\'t enough cases,

140

people were pointing toward a study that by every

reasonable thought, if you think platelets are

involved, ought to be long enough to show things

up.

But then you form a new hypothesis once

you have APPROVe, and you have to adapt it, and I

think that goes on all the time. It would not be I

must say for most things my first thought unless

you are looking for cancer that you need a 3-year

study to find it, but maybe you learned that it

does.

Just for what is worth as an example, you

can\'t get an anti-arrhythmic drug approved in this

country without showing that you don\'t alter

survival unfavorably. One result is there are

hardly any being developed, but, you know, we had

bad experiences, we didn\'t like the results of

CAST, so you change.

I think there is no doubt that things

evolve and you have to expect that, and APPROVe,

depending on what you think of it, changes the

nature of what you expect.

DR. GRAHAM: Bob, just one point on that.

I think if the APPROVe study had been 5 or 10 times

larger than it was\--I am talking about retrospect

141

now\--you would be able to answer with much greater

confidence what is happening month 1 to 18. I

guess what I am saying is that you could also

shorten the latency to identification of a problem

if it turns out that the risk is early on.

DR. TEMPLE: David, I think that is

entirely possible, and if it involves platelets, I

would believe you, but if it involves a small,

long-term increase in blood pressure, then, I am

not so sure.

DR. GRAHAM: Right, but we saw yesterday\--

DR. TEMPLE: We don\'t know.

DR. GRAHAM: We don\'t, but if it\'s

prostacyclin, that effect could occur immediately.

DR. TEMPLE: Yes, but the blood pressure

effect could be delayed.

DR. WOOD: Right. So what, Bob, you are

saying is that it is easy to be a Monday morning

quarterback, but the data were not there before.

DR. TEMPLE: I would never be that rude.

DR. WOOD: I think you are right.

Dr. Stemhagen.

DR. STEMHAGEN: I would like to clarify a

couple things. First, I am a little concerned in

terms of the unpublished data. I appreciate that

142

we are able to get data very quickly, right at the

minute that it is being generated, but none of us

have had a chance to really review that, so I do

have some concerns about the weight putting on this

unpublished data when the rest of us haven\'t had a

chance to look at it.

I think there needs to be some

clarification. There was some discussion about the

recall bias, and so on. Certainly, there is a major

concern about that in case- controlled studies, and

we don\'t have the questionnaires, but there were a

lot of sort of subanalysis done in the Kimmel

study, about trying to look at whether recall bias

is a problem, and I am not sure that you have

highlighted that enough that looking at all those

different things, there were really no differences

143

found.

Similarly, in the Watson study, it\'s a

GPRD study, it is different than a lot of the large

databases, the automated databases.

There is a lot more personal involvement

in terms of the data and the data collection and

the adjudication of results, and I think it just

needs to be clear that all of these studies are not

the same in terms of a Medicare study where we

can\'t go back and validate records. A lot of them

had a much more careful review, and I am just not

sure that that was totally clear and if you hadn\'t

read each of the papers.

I would like to just ask a question in

terms of your definition of the inception cohort,

if you could just go over that again, because of

your comments about the short-term use.

DR. GRAHAM: Inception cohorts are where

people enter the cohort with their first-time use

of a specific agent, so it\'s basically like an

incident cohort, it\'s new users. That is to be

distinguished from a prevalence cohort where

144

starting January 1st, everybody who was on an NSAID

is in our cohort.

Some of those could be people who were on

it before January 1st, and others could be people

who start an NSAID after January 1st, so you are

mixing people who are prevalent on the drug, who

may have survived, or whatever, and people who are

newly starting it.

In those types of cohort studies, a new

user analysis was designed to focus on those people

who, during the study window, were new initiators

of the particular drug under study, so that time

zero could be identified for those people.

That is what Alec Walker & Company did in

their Ingenix study. It was a prevalence cohort,

but they did a new user analysis in which they

identified new users, and it was that new user

analysis that showed the 1 to 30-day increased

risk.

Wayne Ray did the same thing in terms of

new user analysis, and in our study, the nested

case control, everyone was an inception user in the

145

base population.

DR. STEMHAGEN: I guess just a comment in

terms of people thinking about clinical trials

where we have washout periods, is that people are

really switching.

If they are RA or OA patients, they are

not starting new with the drug, they have been on

something for a long time, and they are switching.

So, we have to think about those risks in terms of

the weight we are putting onto that inception

cohort, as well.

I guess the last point is based on the

question that Ralph had about the other studies. I

just want us to keep in mind also that a lot of

those studies come from very unique populations -

the randomized clinical trials, the colon polyp

study, and the Alzheimer\'s disease patients, so are

very different.

We can\'t tease out in any of these

observational studies whether we have patients that

meet those criteria or have those indications, as

we also pointed out.

DR. WOOD: Tom.

DR. FLEMING: I think Drs. Platt\'s and

Graham\'s presentations were informative, but with

146

certainly a lot of complexities for methodologic

issues that I assume tomorrow, we will give our

perspectives about, so let me ask a question and

then a clarification.

The question relates to the slide on the 4

positive naproxen studies, I think slide 22. While

you are getting that, just very quickly, these

large linked databases certainly are very useful

from the perspective of getting defined populations

with numerators and denominators, but have many

challenges that people have been talking about

along the lines of lack of randomization, no

confounder information, specificity and

sensitivity.

Bob O\'Neil got at a point that I think is

critical, and that is the complexity of not having

a time zero cohort with the ability to do what

would be the analogous ITT analysis with complete

follow-up or minimize loss to follow-up.

You bring out in the Solomon example

there, David, a very nice illustration of this very

point that you recognized, which is the selection

bias that can go on when you are characterizing

people into these groups, and it\'s misleading to

think that you are really seeing the causal effect

147

of any use versus current, versus recent, versus

remote, the causality could be going in the other

direction.

Intrinsic differences in patients could be

influencing whether they are, in fact, in those

four categories. But don\'t you, in essence, even

though your conclusion might be right, aren\'t you,

in essence, doing the same thing at the top when

you are looking at naproxen, say, when you are

looking at other NSAIDs, it is protective, but you

don\'t know whether it\'s, in fact, truly the harmful

effect of the other NSAIDs, so you try to get in a

non-use population, you are trying to simulate a

placebo, but how do you know that those non-use

people weren\'t intrinsically better? Isn\'t it the

same issue?

DR. WOOD: I think we have had this

discussion.

DR. FLEMING: But this is important, I

want to get his views, because it\'s important for

naproxen.

DR. WOOD: Okay.

DR. GRAHAM: There is no perfect reference

group. It turns out that this non-use group is

really they are remote users, but it is a question

148

and I can\'t answer it except to say that when you

adjust for all the confounders you are able to

measure, you try to remove those effects, but there

still could be effects that you cannot remove.

The data are what the data are, and here

what I was trying to show is that based on\--if

these data were looked at the way most of the other

studies were done, it gives a very different

result.

If it turns out that all of the NSAIDs

increased the risk a little bit, the fact that

naproxen doesn\'t increase it as much, could look

protected, and you really don\'t know.

The real conundrum is to get an anchor

point to help you interpret everything, and there

is no perfect anchor point.

DR. FLEMING: Your motivation for wanting

to know what the placebo-controlled result is, is

clear and justified. This analysis, though, has

the same potential flaws as the Solomon analysis.

So, the motivation for the question is clear, as

you are just restating, but the reliability of the

conclusions are suspect for this very reason that

you correctly noted, due to the selectivity in the

Solomon categorization.

149

DR. GRAHAM: You need then to sort of

generalize that to all of the observational

studies, because all of them, you had\--

DR. WOOD: Why don\'t we continue this

conversation later, and, Tom, you can present

discussion on that later.

DR. FLEMING: Well, there is much more to

say, but I will defer to tomorrow.

DR. WOOD: I am sure there is.

Dr. Hennekens will be our last question

150

before the break. Just to encourage you, we will

be back here just after 20 to, so make it fast.

DR. HENNEKENS: A question and a comment.

Ten years ago, a large body of basic science,

clinical studies, case-control, and prospective

cohort studies consistently showed that patients

with hypertension prescribed calcium blockers had

1.5 to 2-fold increased risk of MI even after

controlling for a large number of available

confounders.

I wrote a JAMA editorial asking for

randomized evidence, but I assume, based on what I

heard you say, that you would have asked the agency

to withdraw the drugs. So, I would ask you to

consider whether protecting the public from harm is

an optimal goal.

It is far more simple and straightforward

than trying to maximize benefit and minimize harm,

which would do the most good for the most people,

but doing the most good for the most people does

not, strictly speaking, protect the public from

harm.

DR. GRAHAM: Do you want a response to

that? Okay. I think that when you are faced with

a large risk that affects large numbers of people,

151

and has a large consequence, that you don\'t have

the luxury of time to wait 10 years to get

clarification on the issue, and you have to use

what data you have available at the time.

I think that just as we have imperfect

measures of risk, I would submit that we have even

more imperfect measures of actual benefit. In the

case of hypertension, I think, you know, that has

been studied dramatically and we actually know that

not all antihypertensives lowering blood pressure

at the same amount, confer the same population

benefit.

I would say that with this class of drugs,

we really haven\'t even demonstrated\--I mean

yesterday, the question came up why would a company

do a study on polyp prevention, had they thought

about what the benefit of this was, and nobody had

started to think, well, how many lives are we going

to save by giving people these drugs, and I would

152

submit that if you were to ask the agency or ask

the company on this, if you don\'t have a good

measure on benefit, so you want to make a

benefit-risk assessment.

We have measures of risk, they may be

imperfect, but I would argue that from a population

perspective, you don\'t really have nearly as good

information as you might believe you do from the

clinical trials, what the benefit in the population

is, how many lives are actually saved by the

COX-2s, for example.

DR. WOOD: On that note, I am told the

lines are building at the men\'s room, so we need to

be back here at exactly quarter to.

(Recess.)

DR. WOOD: Let\'s get going.

Arcoxia (etoricoxib)

Merck Research Laboratories

Sponsor Presentation

Sean P. Curtis, M.D.

DR. CURTIS: Mr. Chairman, members of the

Joint Advisory Committee, FDA, ladies and

153

gentlemen: My name is Dr. Sean Curtis, Senior

Director, Clinical Research, at Merck and Company,

and I would like to thank you for the opportunity

to review data from the Etoricoxib Development

Program.

I believe the committee will find these

data informative and contribute to the further

evaluation of this therapeutic class, a goal we all

share collectively.

Drs. Konstam and Loren Laine are serving

as consultants today and are available as a

resource to the committee.

Following an introduction, results from

the development program will be summarized

beginning with efficacy, followed by a review of

the safety findings. I will first review the

gastrointestinal and renovascular safety, followed

by thrombotic cardiovascular safety.

I will then review the design of three

studies, which together are designed to further

characterize and assess the cardiovascular safety

of etoricoxib in arthritis patients.

154

Cardiovascular safety data from the first of these

three studies, the EDGE study, will be reviewed,

and I will conclude with a summary.

My presentation will focus on the

following points. Etoricoxib, as a selective COX-2

inhibitor, has a role among the current treatment

options for patients with diseases and conditions

characterized by pain and inflammation.

Supportive data will be reviewed, namely,

efficacy that has been demonstrated to be similar

and, in some cases, superior to NSAIDs,

specifically naproxen 1,000 mg; gastrointestinal

safety and tolerability, favorably differentiated

from NSAIDs; and a renovascular safety profile,

which is dose dependent and generally similar to

the effects observed with comparator NSAIDs at

therapeutic doses.

With regards to thrombotic cardiovascular

safety, cardiovascular events occurred at a similar

rate on etoricoxib as compared to non-naproxen

NSAIDs over the course of approximately 1 year.

Data are currently limited beyond 1 year of

155

treatment, and events occurred at different rates

in comparison to naproxen.

The other key point for my presentation is

that large, randomized clinical trials are

currently ongoing to further characterize the

long-term cardiovascular safety of etoricoxib as

suggested by many members of this joint committee.

These results will provide a full

characterization of the cardiovascular safety

profile of etoricoxib in arthritis patients as

compared to diclofenac.

These data are critical to the current

scientific debate over cardiovascular safety.

Specifically, we will address whether the long-term

cardiovascular safety of a selective COX-2

inhibitor is similar to, or different, than that of

a traditional NSAID.

Let\'s begin reviewing the data.

Etoricoxib represents a distinct chemical

entity. It consists of a bipyridine ring with

methyl sulfone side chain. In the clinical dose

range, etoricoxib has demonstrated selectivity for

156

the COX-2 enzyme using human whole blood

biochemical assays.

Its absorption is rapid with a peak plasma

concentration achieved by approximately 1 hour and

with an effective half-life of approximately 22

hours, it is suitable for once daily dosing.

Etoricoxib is currently approved in

approximately 60 countries. Core indications

include osteoarthritis at a once daily dose of 60

mg, rheumatoid arthritis at a once daily dose of 90

mg, and acute gouty arthritis. The dose is 120 mg

for the acute symptomatic period only.

In the United States, the FDA issued an

approvable action on our new drug application.

I would now like to summarize efficacy.

The efficacy of etoricoxib has been demonstrated

across a range of conditions and diseases

characterized by pain and inflammation.

For these conditions, efficacy data have

been published or accepted for publication

including 3 diseases and conditions for which an

indication is not currently granted in the United

157

States for a selective COX-2 inhibitor. These

include studies in chronic low back pain,

ankylosing spondylitis, and acute gouty arthritis.

As you will remember, the acute gouty

arthritis data were discussed with the Arthritis

Advisory Committee in June 2004 in the context of a

committee meeting design to look at gout study

designs.

Efficacy data are summarized in your

background package, however, I would like to draw

your attention to results obtained in three

specific disease models.

The rheumatoid arthritis program included

2 pivotal double-blind, placebo and active

comparator- controlled studies in approximately

1,700 patients. In one study, etoricoxib 90 mg

demonstrated efficacy that was statistically

superior to naproxen 1,000 mg for all primary

endpoints and all additional endpoints including

the ACR20.

In the other study, etoricoxib

demonstrated efficacy that was similar to naproxen,

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and in patient with the ankylosing spondylitis, we

performed a single pivotal double-blind, placebo

and active comparator-controlled study which

enrolled approximately 390 patients.

Over the 52-week treatment period,

etoricoxib demonstrated efficacy that was

statistically superior to naproxen 1,000 mg for all

3 co-primary endpoints, and in patient with acute

gouty arthritis, we performed 2 double-blind,

active comparator-controlled studies enrolling

approximately 350 patients in total.

In those studies, etoricoxib at a dose of

120 mg for 7 days demonstrated efficacy that was

comparable to indomethacin.

I would now like to begin reviewing the

safety data.

The gastrointestinal safety program, as

summarized in your background package, was designed

to evaluate the entire GI tract. Clinical outcomes

based on pooled data from the entire development

program were prespecified for analysis. These

include a combined analysis of upper GI clinical

159

events, or PUBs, and a combined analysis of GI

tolerability.

Here are summarized results from the

prespecified combined analysis of upper GI clinical

events which occurred in Phase IIB and III studies

from the entire development program by displaying

the cumulative incidence of confirmed events by

treatment group over the entire duration of the

studies involved in the analysis.

As you see, a statistically significant

relative risk of 0.48 favoring etoricoxib was

demonstrated. This represents a 52 percent risk

reduction. It was observed early and maintained

over the entire study duration. These results are

largely driven by comparisons to naproxen.

For purposes of summarizing renovascular

safety, we will focus on data from the

osteoarthritis and the rheumatoid arthritis

studies, which represent the majority of the data.

Presenting results by disease types ensures the

patient characteristics are similar among the

treatment groups.

This slide displays the incidence of

hypertension adverse experiences by treatment group

observed over a 12-week treatment period, in OA

160

patients on the left, and RA patients on the right.

In the OA population, the dose response is

observed most clearly from 30 to 60 and 60 to 120

mg, 90 mg is outlying likely due to the smaller

sample size, and in the RA population, the dose

response is also observed although less evident as

compared to osteoarthritis.

Overall, the rates observed for

etoricoxib, specifically the doses indicated for

chronic use, that is, 60 and 90, are within the

range observed with comparator NSAIDs, numerically

higher than naproxen, numerically lower than that

observed with ibuprofen, and in both patient

populations, it was rare for patients to

discontinue from this adverse experience with no

clear difference observed between treatment groups.

In addition to hypertension, we looked

closely at adverse effects related to edema and

congestive heart failure. Tabulated here are the

161

incidence of congestive heart failure adverse

effects as spontaneously reported by investigators

in our placebo-controlled population of up to 12

weeks duration.

As you see here, incidences are low among

the active treatment groups. I would like to show

you the cumulative incidence of congestive heart

failure adverse events which occurred over the

entire duration of our chronic exposure studies.

We see here that etoricoxib as compared to

comparator NSAIDs pooled are associated with

similar rates of congestive heart failure adverse

events. The grouping of terms is indicated on the

bottom of the slide.

The data provided in your background

package and summarized thus far support the

improved gastrointestinal safety and tolerability

of etoricoxib compared to non-selective NSAIDs,

with clinical outcomes data including PUBs and GI

intolerance endpoints, as well as endoscopic data.

These data also provide evidence of the

renovascular profile of etoricoxib, that is,

162

hypertension, edema, and heart failure are dose

related as would be expected, and generally similar

to the effects observed with comparator NSAIDs, in

some cases numerically higher and in some cases

numerically lower.

I would now like to move on to

cardiovascular safety data review. The process

that Merck instituted for prospectively

adjudicating all potential thrombotic events as

described by Dr. Braunstein yesterday for

rofecoxib, was operative for etoricoxib from the

beginning of Phase IIB.

We prespecified an analysis of all such

events using individual patient data from studies

of at least 4 weeks in duration across the clinical

development studies.

In total, there were 12 studies included

in this analysis including approximately 6,700

patients and 6,500 patient years of exposure. For

the analysis, comparisons of etoricoxib were made

to placebo or active comparator NSAID using data

only from the studies that contained the treatments

163

being compared.

The etoricoxib group and analysis you will

be seeing shortly consists of data combined from

doses of 60, 90, and 120 mg in order to improve

statistical precision, and for the comparison to

NSAIDs, naproxen was compared to etoricoxib

separate from the other 2 NSAIDs, diclofenac and

ibuprofen, based on the fact that naproxen is

distinct pharmacodynamically from both ibuprofen

and diclofenac, and because qualitative differences

were observed in the comparison to naproxen versus

the comparison to non-naproxen NSAIDs.

The endpoint specified as primary for the

assessment of cardiovascular safety in the

etoricoxib development program was a composite

endpoint of all confirmed thrombotic events

confirmed by the Adjudication Committee, and

includes cardiac, cerebrovascular, and peripheral

vascular events.

The primary results for the pooled

analysis are summarized here by presenting the

point estimate of the relative risk and the

164

corresponding 95 percent confidence interval for

the comparisons of etoricoxib to placebo, to

non-naproxen NSAIDs, and to naproxen for the

composite primary endpoint of confirmed thrombotic

events.

The naproxen-controlled data set is the

largest of the 3 data sets, and the

placebo-controlled data is the smallest of the 3.

This is indicated numerically on the right in

patient years at risk and correspondingly reflected

by the size of the triangle representing the point

estimate of the relative risk.

When comparing etoricoxib to placebo and

to non-naproxen NSAIDs, the relative risk

approximates 1.0 indicating no discernible

difference in thrombotic cardiovascular events

between those treatment groups.

However, it is important to keep in mind

that the maximum duration of the placebo-controlled

period was 12 weeks, and when comparing etoricoxib

to naproxen, the relative risk is greater than 1,

indicating a difference between the 2 treatment

165

groups in a trend favoring naproxen in that

comparison.

Shown here are the cumulative incidence of

confirmed thrombotic events in the

non-naproxen-controlled data set. The amount of

data are limited at longer term time points

particularly for the non-naproxen NSAID group.

In total, the event rates are similar

between treatment groups.

All individual events were categorized by

the Adjudication Committee as either cardiac,

cerebrovascular, or peripheral vascular. In

reviewing the specific events in the

non-naproxen-controlled data set, using this

categorization, cardiac and cerebrovascular events

were observed in both treatment groups.

Numeric differences between treatment

groups trended in both directions and were observed

at the level of individual events.

As indicated previously, the largest of

the 3 data sets is the data set which compares

etoricoxib to naproxen. As you can appreciate from

166

these cumulative incidence curves, the etoricoxib

and naproxen groups separate early with a lower

cumulative incidences observed on naproxen as

compared to etoricoxib.

In the naproxen-controlled data set, the

specific confirmed thrombotic events occurred in

all 3 vascular events. In considering the overall

difference between the naproxen-etoricoxib group,

no single event predominates, however, a higher

incidence of ischemic cerebrovascular strokes was

observed on etoricoxib in this comparative data

set.

Analyses were performed to explore the

relation between dose of etoricoxib and rate of

thrombotic events. The left two panels summarize

the results of a pair-wise analysis, an approach

that includes data only from studies that contained

the doses being compared.

The righthand panel represents results

using a summary approach, which incorporates rates

by dose from all studies in the pooled

cardiovascular analysis.

The data do not indicate evidence of a

dose effect across the 60 to 120 mg etoricoxib dose

range.

167

Summarized in your background package are

results of subgroup analyses from the

naproxen-controlled data set including patients at

increased baseline cardiovascular risk and by

arthritis disease type particularly OA versus

rheumatoid arthritis.

These subgroup analyses, as well as

additional analyses including those subgroups

identified to be potentially at increased risk

based on the rofecoxib APPROVe study failed to

identify any specific patient subgroup at increased

relative risk for thrombotic event.

It is important to remember, however, that

the amount of etoricoxib cardiovascular safety data

currently available do not allow us to make firm

conclusions for any specific subgroup.

All-cause mortality in the etoricoxib

development program is summarized here as rates per

100 patient years by treatment group. Included, as

168

well, are results from the EDGE study, a study of

approximately 1 year\'s duration in over 7,000

osteoarthritis patients comparing the GI

tolerability of etoricoxib to diclofenac.

Rates for etoricoxib and non-naproxen

NSAIDs in the left panel are similar and

numerically higher than those observed on naproxen

and placebo, which are similar to each other. The

rates here are represented as a point estimate with

a corresponding 95 percent confidence interval.

As you see, the confidence intervals are

broad and overlapping between the treatment groups.

Based on these data, there is no evidence for a

true difference in all-cause mortality between

treatment groups.

In the EDGE study, on the right, rates

were numerically similar between treatment groups

in all-cause mortality again with confidence

intervals that overlap the point estimates between

treatment groups, at this point indicating no

evidence of a difference.

The cardiovascular safety data from the

169

original development program can thus be summarized

as follows. There is no clear evidence of a

difference between etoricoxib and placebo based on

limited amounts of short-term data.

There is no discernible difference in

cardiovascular event rates between etoricoxib and

non-naproxen NSAIDs. This comparison is limited,

however, by the amount of active

comparator-controlled data with both diclofenac and

ibuprofen, and naproxen, at a regimented dose of

500 mg twice daily is associated with a lower rate

of thrombotic events as compared to etoricoxib.

As you saw from the Kaplan-Meier curves,

the cumulative incidences, a difference, separates

early, and is, in fact, this is an observation that

has been seen with the rofecoxib data and similar

to the observations made from the lumiracoxib

TARGET study, which we will be hearing about later.

Recent results from long-term

placebo-controlled studies with rofecoxib and

celecoxib have important implications for

etoricoxib. Specifically, these recent data

170

showing a difference in cardiovascular safety in

long-term studies versus placebo do, in fact,

suggest a class effect.

Despite the large size of the original

development program, over 10,000 patients,

approximately 5,800 of which were receiving

etoricoxib, there are limitations on the amount of

accrued cardiovascular safety data. Specifically,

the long-term data were limited in quantity, and

limited primarily in comparison to naproxen.

Because of questions raised with respect

to naproxen, we decided we needed a different

approach to accrue additional data, and I would now

like to review the strategic approach we took and

then discuss the specific studies that resulted.

Our primary objective was to further

establish the long term general and cardiovascular

safety of etoricoxib in arthritis patients who

required treatment. At the time the strategy to

meet this objective was formulated, there were

ongoing long-term placebo-controlled studies with

other selective COX-2 inhibitors, largely focusing

171

on exploring novel indications for

cyclooxygenase-inhibiting therapies. Examples

include Alzheimer\'s disease and chemoprevention.

For etoricoxib, rather than explore novel

indications with placebo-controlled studies, we

chose to further evaluate the group of patients who

required treatment for arthritis. Therefore, the

plan we developed was to perform active

comparator-controlled studies in osteoarthritis and

rheumatoid arthritis patients.

Studying this patient population ethically

precluded use of a placebo for more than a short

period of time, because these patients require

active treatment. Diclofenac was chosen as the

active comparator, and I will review our rationale

for that choice shortly.

Although the recent study results with

rofecoxib and celecoxib were not available when we

designed the studies that I will be describing

shortly, our studies are extremely relevant as they

compared etoricoxib to diclofenac and thus address

the current clinical question of comparative

172

cardiovascular safety between a selective COX-2

inhibitor and a traditional NSAID.

In order to choose an appropriate

comparator NSAID, we established criteria and

evaluated numerous agents and ultimately determined

that diclofenac was the most suitable choice.

Diclofenac is effective in treating both

osteoarthritis and rheumatoid arthritis patients

and can be dosed twice daily, which enhances

compliance and convenience for the patient.

Secondly, it has been established that

diclofenac does not interfere with low-dose

aspirin\'s anti-platelet effects. Ibuprofen, on the

other hand, does interfere with low-dose aspirin\'s

anti-platelet effects.

This interaction posed two issues we felt

precluded use of ibuprofen as the comparator. We

were not comfortable enrolling patients who

required low-dose aspirin with knowledge that its

anti-platelet effects could, in fact, be inhibited,

and secondly, we were concerned that interpretation

of study results, which showed comparable

173

cardiovascular safety, to an agent that inhibits

aspirin\'s anti-platelet effects could be

problematic.

Diclofenac inhibits both COX-1 and COX-2

and confers partial inhibition on platelet-mediated

COX-1 thromboxane. Since it lacks potent and

sustained anti-platelet activity, we would not

expect confounding effect on the interpretation of

cardiovascular safety results as would be expected

with naproxen based on the cardiovascular data from

the development program which I presented.

Data from some of our clinical trials

indicate that diclofenac\'s effect on blood pressure

is generally similar and, in fact, in some cases

more pronounced than the effect observed with

etoricoxib.

In consideration of the established

cardiovascular complications of elevations in blood

pressure, a comparison of thrombotic cardiovascular

safety between etoricoxib and diclofenac can, in

fact, be considered conservative.

I wanted to briefly review some

174

pharmacodynamic data which supports diclofenac

having COX-1 inhibiting effects. Represented on

this slide are the ex-vivo COX-2 and COX-1

inhibiting effects of various agents.

Displayed on the X axis is the percentage

of COX-2 inhibition as measured by inhibition of

lipopolysaccharide-induced serum PGE

2\. Displayed

on the Y axis is the percentage of COX-1 inhibition

as measured by serum thromboxane as a weighted

average at steady state with 84 percent joint

confidence regions around the point estimate of the

mean.

Rofecoxib at 12.5 and 25 mg inhibits COX-2

on the order of 60 to 70 percent in this

experiment. Diclofenac at a dose of 150 mg

inhibits COX-2, but also inhibits COX-1.

Endoscopic data are also available which

support the COX-1 inhibiting effects of diclofenac.

Shown here are results from two endoscopy studies

performed with valdecoxib which included a

diclofenac treatment arm. In each case, the

cumulative incidence of gastroduodenal ulcerations

175

observed at the end of the study period are

displayed by treatment group in these two studies.

On the left are results of a 26-week study

of rheumatoid arthritis patients. The incidence of

gastroduodenal ulcerations observed on diclofenac

was significantly greater than observed on either

dose of valdecoxib in this study.

On the right are results of a 12-week

study in osteoarthritis patients. The incidence of

gastroduodenal ulcerations on diclofenac was

significantly greater than placebo and valdecoxib,

and, in fact, similar to the incidence observed on

ibuprofen.

Lastly, I would like to point to some GI

clinical outcomes data which also support the COX-1

inhibiting effects of diclofenac. Dr. Braunstein

reviewed the cumulative incidence of confirmed

upper GI clinical events of rofecoxib versus

individual NSAIDs yesterday based on final data

from the rofecoxib development program.

What I have done here is instead of

looking at confirmed PUBs, I have also added the

176

confirmed plus unconfirmed results, which are very

consistent with what Dr. Braunstein showed

yesterday.

You see here the relative risk of

confirmed plus unconfirmed upper GI events observed

on rofecoxib is, in fact, significantly different

than the effect observed with diclofenac, so again

to provide some clinical data that support a COX-1

inhibiting effect of diclofenac.

The overall approach to further

characterize etoricoxib that I have been describing

consists of a prospectively designed analysis of

cardiovascular safety data will accrue from three

studies, which I am going to briefly review here.

All three studies compared etoricoxib to

diclofenac. The first is the EDGE study, a study

of 7,111 osteoarthritis patients with a primary

objective to compare the GI tolerability of

etoricoxib to diclofenac. This study is now

complete.

Secondly, EDGE II, a study of

approximately 4,090 RA patients with a primary

177

objective identical to that of EDGE. The dose of

etoricoxib in EDGE II is 90 mg. This study is

fully enrolled and ongoing. The predicted mean

duration of this study is expected to be

approximately 19 months.

Thirdly, MEDAL, a study of approximately

23,450 osteoarthritis and rheumatoid arthritis

patients with the primary objective of comparing

the cardiovascular safety of etoricoxib to

diclofenac. This is an endpoint-driven outcome

study. MEDAL is fully enrolled and currently

ongoing. The predicted mean duration of therapy in

MEDAL is approximately 20 months with some patients

expected to be on therapy an excess of 3 years.

Although EDGE and EDGE II are designed as

primary GI tolerability studies, the cardiovascular

safety data that will accrue from those two studies

are being adjudicated and will be combined with the

cardiovascular safety data from the MEDAL study in

order to improve the precision of the comparison.

The primary hypothesis for this analysis

is that etoricoxib will demonstrate a

178

cardiovascular safety profile that is non-inferior

to that of diclofenac. There are 2 key analyses

that are designed to support this hypothesis.

The primary analysis will consider the

minimum required 635 confirmed thrombotic events

from all 3 studies combined, and the secondary

analysis will consider the minimum 490 confirmed

thrombotic events that are required from the MEDAL

study alone.

As I mentioned, MEDAL was designed as an

endpoint-driven outcome study and on its own

represents a sufficiently powered assessment of

cardiovascular safety. The patient population that

has been enrolled in these studies consists of

patients with a range of baseline cardiovascular

risk and includes patients with pre-existing

cardiovascular disease.

As clinically indicated, such patients, as

well as others, are being prescribed aspirin, so we

expect the total study cohort to include

approximately 30 percent aspirin users.

MEDAL and EDGE II will generate a

179

tremendous amount of long-term cardiovascular

safety data. As summarized on the previous slide,

the predicted mean duration of therapies in EDGE II

and MEDAL are 19 and 29 months respectively, and it

is predicted that out of the 635 confirmed

thrombotic events, approximately 200 of those

events will occur in patients who have been on

study therapy for at least 18 months.

In this cohort alone, the minimum between

treatment group difference that would be

statistically significant expressed as a relative

risk is approximately 1.3.

An external Data and Safety Monitoring

Board was chartered to monitor emerging data from

MEDAL, EDGE, and EDGE II. Since 2002, they have

been meeting regularly, most recently in November

of 2004, at which time they reviewed a large amount

of data. At that time, in total, there were

approximately 21,000 patient years of exposure and

approximately 300 confirmed thrombotic events were

available at that time for their review.

In addition, there were approximately

180

3,000 patients who had been on study therapy for at

least 18 months at that time. Based on their

review, their recommendation was to continue the

ongoing studies without interruption or without

modification.

Of the 3 studies that we have been

discussing, EDGE is the first to be completed, and

I would now like to review the cardiovascular

safety data from the EDGE study.

In this study, the 7,111 osteoarthritis

patients were on study therapy for a mean duration

of approximately 9 months, resulting in

approximately 5,400 patient years of total

exposure.

The study population included patients

with a range of baseline cardiovascular risk. Here

are summarized some selected baseline

characteristics. As you see, approximately 38

percent of the patients in this study were at

increased baseline cardiovascular risk defined as

patients having 2 or more risk factors for

cardiovascular disease or a documented history of

181

symptomatic atherosclerotic cardiovascular disease.

This slide summarizes the cardiovascular

safety data from the EDGE study by presenting again

the point estimate of the relative risk and the

corresponding 95 confidence interval, for confirmed

thrombotic events versus diclofenac, for events

which occurred on therapy or within 14 days of

study therapy discontinuation, on study therapy or

within 28 days, and importantly, an all patients

treated analysis.

In the EDGE study, all patients who

discontinued were followed up closely with regular

phone contact to ascertain any events that occurred

long term off-of-study therapy, and this was done

for all patients until all patients had completed

the study.

The cumulative incidence of confirmed

thrombotic events in the EDGE study are summarized

here, and indicate no evidence of a difference

between the treatment groups over time.

This slide summarizes the specific

confirmed events by type in the EDGE study

182

beginning with events which occurred on study

therapy or within 14 days of discontinuing study

therapy.

As you see, there are events reported in

all 3 vascular events with more cardiac event

overall irrespective of treatment group.

Evaluation of individual event types indicates that

the absolute number of any event was small with

numeric differences between treatment groups for

certain events with some occurring at a higher rate

on etoricoxib and some occurring at a lower rate.

For example, differences were observed in

ischemic strokes numerically favoring etoricoxib,

however, differences favoring diclofenac were

observed for acute myocardial infarctions. Neither

of these differences were statistically

significant.

It is important to remember that even in a

study of this size, results at the level of

individual events should be interpreted cautiously.

For example, when looking at events which occurred

on study therapy or within 28 days, as requested by

183

the agency, the numeric differences between

treatment groups has, in fact, narrowed slightly

due primarily to an increase in the number of acute

myocardial infarctions which occurred on the

diclofenac group.

Data from ongoing randomized clinical

trials will be critical to more precisely assess

the comparative rates of myocardial infarctions on

diclofenac versus etoricoxib.

Summarizing results of the EDGE

cardiovascular safety data next to the results of

the pooled analysis that I presented previously

indicate that the EDGE data are, in fact,

consistent with, and add precision to, the

observations from the pooled analysis when

comparing etoricoxib to non-naproxen NSAIDs.

I would now like to summarize. We have

demonstrated efficacy with etoricoxib that is

similar and in the cases I have pointed out, in

fact, superior to comparator NSAIDs particular

naproxen 1,000 mg.

We have a GI safety program that did

184

demonstrate improved GI safety and tolerability in

relation to shift to non-selective NSAIDs primarily

in relationship to naproxen, and the renovascular

effects observed with etoricoxib are, as again

would be expected based on the mechanism of action

dose related, but at the doses recommended for

chronic use are, in fact, generally similar to the

effects observed for the comparator NSAIDs.

We saw numeric differences against

naproxen favoring naproxen, but we also saw rates

of hypertension that were very similar to those

observed with ibuprofen even at their maximal

chronic dose.

Based on thorough and ongoing reviews of

cardiovascular safety data, there is no clear or

discernible difference between etoricoxib and

non-naproxen NSAIDs up to a year. As I said, we

have limited amounts of data beyond 1 year at this

time.

Differences were observed between

etoricoxib and naproxen rates of thrombotic events.

Based on the data we have, the limited amounts of

185

short-term placebo data, there is no clear

difference between etoricoxib and placebo. That

being said, emerging data from long-term

placebo-controlled studies with rofecoxib and

celecoxib showing a difference in cardiovascular

safety versus placebo do, in fact, suggest a class

effect.

MEDAL, the largest NSAID trial known, and

EDGE II are currently ongoing and based on current

cardiovascular event rates are expected to be

completed next year. Results from these studies

will further characterize the cardiovascular safety

of etoricoxib, and we will have data to address

numerous questions including cardiovascular safety

in both osteoarthritis and rheumatoid arthritis

patients, and cardiovascular safety in patients

with a range of cardiovascular risk, and will

include experience in aspirin users and non-users.

We will be able to further explore the

effect of dose as both 60 and 90 mg are included in

the study, and perhaps, most importantly, the

long-term cardiovascular safety will be assessed as

186

we will have large amounts of data in patients who

have been on study therapy for at least 18 months.

These studies directly address whether the

cardiovascular safety including the long-term

safety of a selective COX-2 inhibitor, such as

etoricoxib, is similar to or different than that of

a traditional NSAID.

In countries where etoricoxib is currently

approved, Merck has consistently taken a proactive

approach with regulatory agencies. From the time

it was first approved years ago, the etoricoxib

product label has, in fact, contained a precaution

for use in patients with ischemic heart disease.

We continue to work aggressively with

regulatory agencies and are currently actively

engaged with European regulators, and have

participated in a referral process in Europe. Our

goal there is to ensure that the product label

accurately reflects all accruing safety information

that is relevant to prescribers based on data that

are currently available.

In conclusion, etoricoxib has a role among

187

the current treatment options for patients with

conditions characterized by pain and inflammation.

However, it is critical to ensure its safe and

effective use, that a product labeling continues to

be revised to ensure that all currently available

data are incorporated to help guide appropriate

use.

We remain committed to help address public

health questions and currently, with etoricoxib,

largely through the conduct of the MEDAL and the

EDGE II studies. These questions posed yesterday

include, For patients who require chronic

anti-inflammatory therapy for established

indications, what is the risk and benefit of a

selective COX-2 inhibitor as compared to an NSAID?

MEDAL and EDGE II will provide information

to this question in comparison to diclofenac, and I

have provided you the data we currently have

available that provides information relative to

naproxen.

Other questions which remain at this time

include Can patients at increased cardiovascular

188

risk be identified, so the benefit is maintained

and the risk minimized?

MEDAL, again due to its unparalleled size,

and with the additional data from EDGE II, will

provide information and data to allow further

exploration to help answer this question.

Next, Is the increased cardiovascular risk

a class effect of COX-2 inhibition, and if so, how

large is the class, and what are the long-term

cardiovascular effects of a selective COX-2

inhibitor and traditional NSAIDs?

Again, MEDAL, with its long-term direct

comparison to diclofenac, will provide information

to address both of these questions.

This concludes my presentation. I would

like to thank the Chairman, members of the Advisory

Committee, the FDA.

Thank you.

DR. WOOD: Thanks a lot. Let\'s go

straight on to the FDA\'s presentation.

FDA Presentation

Analysis of Cardiovascular Thromboembolic

Events with Etoricoxib

Joel Schiffenbauer, M.D.

DR. SCHIFFENBAUER: Thank you and good

189

morning. My name is Joel Schiffenbauer. I am

going to be presenting an analysis of

cardiovascular thromboembolic events with

etoricoxib.

I will be presenting the results of trials

for the following indications listed here in the

NDA. In addition, I will be presenting results of

the EDGE trial separately from those of the trials

here.

I will first present briefly exposure data

followed by mortality data and then spend the

remainder of the time discussing the cardiovascular

thromboembolic events data. Again, I will present

data first for the NDA and separately for the EDGE

study.

First, exposure. This slide summarizes

the chronic exposure to etoricoxib across the NDA.

As you can see for the 60, 90, and 120 mg doses,

which were the proposed doses for the drug, the

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total number of patients is shown here and the mean

number of days is shown here.

For the EDGE study, there was

approximately 3,500 patients in each arm, exposed

for a mean of 9 months. Total patient years is

shown at the bottom.

Let me turn now to the mortality data.

This is the mortality data across the NDA. Rates

are shown as per 100 patient years, and I have

listed the comparators here, placebo, non-naproxen

nonsteroidals, and naproxen.

If we first look at the first line of

total deaths, we can see that the rate of deaths in

the placebo group is similar to naproxen, followed

by the non-naproxen nonsteroidals, and then

etoricoxib.

Let me next draw your attention to the

third line, thrombotic cardiovascular deaths.

There were no deaths in the placebo group, followed

by naproxen, etoricoxib, and then non-naproxen

nonsteroidals.

These 2 events I would point out occurred

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at greater than 36 months exposure to the

non-naproxen nonsteroidals, and I will come back to

this point when I present the Kaplan-Meier analysis

looking at non-naproxen nonsteroidals.

The deaths in the EDGE study, the total

deaths are similar, 8 and 6, for cardiovascular

thrombotic related, it was 3 and 1.

Let me now move on to a discussion of the

cardiovascular thromboembolic events.

The sponsor proposed a composite endpoint,

which you have already heard about, which included

events related to the cardiac, peripheral, and

cerebrovascular system. I will present results for

both the composite, as well as the components of

the composite, and I think this is an important

point because we do not yet know the effects of

COX-2 inhibitors on each of these specific

cardiovascular events.

In addition, I will not present data for

APTC events or investigator-reported events.

Although the numbers vary slightly, the trends are

always in the same direction as the events that I

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will show here.

These events were referred to an

Adjudication Committee, that you have heard about

already, and after being reviewed in that

committee, were then described as confirmed

cardiovascular thromboembolic events.

This slide shows an analysis of the

confirmed thrombotic cardiovascular serious adverse

events across the NDA. This is exclusive of the

EDGE study. The sponsor performed 3 comparisons -

etoricoxib to placebo, etoricoxib to non-naproxen

nonsteroidals, and etoricoxib to naproxen.

The number of patients, the cases in

patient years of exposure is shown here, rates, and

relative risk. I will show this slide over again.

First, let me start on the first line. I

draw your attention to the rate of events in the

etoricoxib group 1.25 versus placebo 1.19 for the

relative risk shown here, and an analysis of those

events is shown in this slide.

These are the rates I showed you, 1.25 and

1.19. There were a total of 7 patients in the

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etoricoxib group versus 4 in placebo, and this

breaks down to 4 cardiac events, which are listed

here - MI, fatal MI, unstable angina, and sudden

death versus zero in placebo.

The number of events in peripheral and

cerebrovascular are similar although the rates do

vary slightly.

Let me point out here that in some of

these slides, these numbers will not necessarily

add up. That is for two reasons. One is an

individual patient may have more than one event,

and they would therefore be listed in more than one

category, and, secondly, for the sake of clarity

and brevity, I left out in some instances all the

events.

This is the Kaplan-Meier estimate of time

to event for the placebo comparison. Note that

this is only 3 months in duration. There are very

little differences between the two groups.

Let me move on then to the

etoricoxib/non-naproxen comparisons. Here is the

rate, 0.79 and 0.80, and I will show you that in

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next slide. Here are the rates again, 0.79 and

0.80. These are composed of 12 patients in the

etoricoxib group versus 4 in the combined, and by

that I mean combined exposure to diclofenac and

ibuprofen. You can see, however, exposure to

ibuprofen is rather small and there were no events,

so all of the events come from the diclofenac

exposure.

If we examine the breakdown of these 12

events, you can see there were 11 cardiac events in

the etoricoxib group for the rate shown here versus

2 in the combined for this rate, and that is

further broken down to 3 MIs versus zero, 2 and 1

of fatal MIs, and then the rest you can see here.

There are 2 and 2 events in the cerebrovascular

system.

You have seen this previously, but let me

make several points about this Kaplan-Meier

analysis for the non-naproxen and nonsteroidal

comparisons. First of all, you will note that the

length of exposure is out to 36 months when there

are relatively few patients still present in the

195

studies.

Secondly, there were 4 events in the

non-naproxen nonsteroidals, which is shown by the

solid line. Three of those events occurred at

greater than 36 months exposure. Two of those 3

events were the deaths that I described in the

earlier slide.

In contrast, there were 12 events in the

etoricoxib group, 11 out of those 12 events

occurred at approximately 26 months or earlier.

So, there is a difference in the time to event as

demonstrated by this Kaplan-Meier analysis.

Lastly, let me turn to the

etoricoxib/naproxen exposure. Here are the rates,

1.37 and 0.81. Again, here are the rates, 1.37 and

0.81. There were 34 patients in etoricoxib versus

14 in naproxen, and that is broken down into 21

cardiac versus 9 for the rate shown here, 10 MIs

versus 5, and you can see the remainder.

For peripheral, there was a slight

imbalance, 5 events in naproxen versus 2 in

peripheral, however, when we come back to the

196

cerebrovascular system, there were 12 versus 2,

which included 10 ischemic strokes versus zero.

Again, you have seen the Kaplan-Meier analysis,

which shows a separation of the two curves almost

throughout the entire exposure.

Let me turn now to the analysis of

cardiovascular events in the EDGE study, and start

by making a few points. There were 7,100 patients.

It was designed as a GI tolerability study in which

cardiovascular data was collected.

The sponsor defined a non-inferiority

margin to diclofenac for cardiovascular events as

the upper limit of the 95 percent confidence

interval for the hazard ratio of 1.3.

In addition, there were several concerns

that I would like to emphasize. First, it was

designed as a non-inferiority trial, there was no

placebo. Diclofenac was the only comparator, and

as we have heard here, and there is data in the

literature to support the relative COX-2

selectivity of diclofenac.

Next, there were only osteoarthritis

197

patients studied. There were no rheumatoid

arthritis patients in this study. We know that

rheumatoid arthritis itself confers cardiovascular

risk.

The next two bullets relate to maneuvers

that could potentially, in the context of a

non-inferiority trial, make it difficult to

identify differences between the two treatment

groups.

So, for example, there was 30 percent

aspirin use. If we believe that aspirin is

cardio-protective even in the context of COX-2

inhibitor, this could make it difficult to discern

any differences between the two groups.

In addition, previous COX-2 use was

allowed, and I have listed here what that was, and

this could potentially lead to depletion of

susceptible individuals to a cardiovascular event.

Lastly, although it is important to study

high-risk patients, if these high-risk patients are

on aspirin, that may be a problem in

differentiating the two groups. In addition, if

198

there are more events in these high-risk patients,

it could increase the background events, and again

in the context of a non-inferiority trial, may make

it difficult to differentiate the two treatment

groups.

So, you have seen this Kaplan-Meier

analysis. Again, the two groups separate slightly,

but the two curves do finally converge at

approximately 12 months.

This is a breakdown of the events in the

EDGE trial. There were 35 patients in the

etoricoxib group versus 30 in diclofenac for the

rates given here. If we look at a further

breakdown of the components, we see there were 27

cardiac-related events versus 19 for the rates

given here. For MI, there was 19 versus 11. For

cerebrovascular events, there was 7 and 7 with a

slight imbalance in ischemic strokes of 6 in

diclofenac versus 3 in etoricoxib.

I think it is important, I mentioned

earlier that aspirin use may be a problem. I broke

down the number of events by aspirin and

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non-aspirin users, and I have just provided the

number of events, the patient years of exposure are

fairly similar.

You can see that by aspirin users, there

is little differences between the groups, 12 versus

9 here for cardiac events, 7 and 5. However, when

you look at the non-aspirin users, the differences

are more pronounced. There were 15 cardiac events

in etoricoxib versus 10 in diclofenac, and 12 MIs

versus 6.

There was some concern about hypertension.

Some issues were raised about that yesterday. I

show some data for hypertension-related adverse

events in the EDGE trial. These types of adverse

events could include anything from a hypertensive

crisis, malignant hypertension to systolic blood

pressure increase among other events.

This is an analysis of patients with

serious hypertension-related adverse events. There

were 5 in etoricoxib versus 2 in diclofenac, and

then another category, hypertension-related AE

associated with systolic blood pressure greater

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than 180, or diastolic greater than 110, and there

were 69 cases here versus 30 in diclofenac.

Then, this is a cumulative incidence of

new use of anti-hypertensive medications. The

upper line is etoricoxib, the lower line is

diclofenac. You can see that the two curves

separate almost throughout the entire 12-month

period.

Lastly, a description of congestive heart

failure-related adverse events. This is the

incidence of CHF pulmonary edema-related or cardiac

failure adverse events. There were 14 versus 6.

In summary, in the NDA, etoricoxib trends

worse in terms of cardiovascular thromboembolic

events, particularly cardiac and MI. The one

common thread throughout all the comparators does

appear to be the cardiac system.

There are differences in the

cerebrovascular or peripheral system, but those are

inconsistent depending on the comparator.

Comparisons of etoricoxib to naproxen for

the cardiovascular events is similar to what you

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have seen for rofecoxib and the naproxen

comparisons.

I have outlined some trial design concerns

in the EDGE study, which I presented, and as you

have already heard, there are two ongoing trials of

similar design, which I believe have similar

concerns.

There are trends in the EDGE study for

cardiac events, worse for etoricoxib, and that is

seen mainly in the non-aspirin users.

Thank you.

DR. WOOD: Thanks very much.

Let\'s go straight on to the Novartis talk

and we recognize that will finish a little late,

but we will have a shorter lunch break.

Lumiracoxib

Lumiracoxib: Introduction

Novartis Pharmaceuticals Corporation

Sponsor Presentation

Mathias Hukkelhoven, Ph.D.

DR. HUKKELHOVEN: Thank you.

Dr. Wood, Dr. Gibofsky, Dr. Gross, members

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of the FDA Advisory Committees, FDA, and Guests:

Good morning. My name is Mathias Hukkelhoven and I

am responsible for Global Regulatory Affairs at

Novartis.

On behalf of Novartis, I would like to

thank you for the opportunity to review the

gastrointestinal and cardiovascular safety data

that we have gathered in our clinical development

program for lumiracoxib.

As a part of the program, we have also

gathered one of the largest databases of clinical

trial data with ibuprofen and naproxen.

Allow me to remind you of the reason that

the COX-2 selective NSAIDs were developed. In the

U.S. alone, there are approximately 100,000

hospitalizations, and as we heard yesterday, 16,000

deaths annually that are caused by GI adverse

events. Deaths due to NSAIDs are among the leading

causes of death in the U.S.

Our presentation will make the following

key points. Each non-selective NSAID and COX-2

selective inhibitor has a benefit-risk profile that

203

must be considered individually.

The Novartis development program provides

clinically informative safety data for lumiracoxib

as well as for ibuprofen and naproxen.

The GI and CV safety profile for

lumiracoxib differs from non-selective NSAIDs and

other COX-2 selective inhibitors.

We have investigated the use of

lumiracoxib for several indications, but our

presentation today will focus on the safety data

accumulated for chronic indications. We have

conducted 22 clinical trials of 1 week or longer in

which 34,000 patients were enrolled.

The largest of the clinical studies was

the TARGET outcome study. This is the largest

outcome study ever conducted for an NSAID or COX-2

selective inhibitor with 18,325 patients enrolled.

It is important to note that this study was

conducted at 400 mg daily dosing, which is 4 times

the dose for which approval will be sought.

This 1-year study compared lumiracoxib to

two different NSAIDs - naproxen and ibuprofen.

We will also present a meta-analysis of

cardiovascular safety of all 22 long-term

lumiracoxib studies.

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Our presentation will demonstrate that

there is a definitive GI benefit with lumiracoxib

in the non-aspirin population. In addition, the CV

meta-analysis of all lumiracoxib studies at no

point revealed a significant CV risk.

I would like to introduce today\'s

presenter Dr. Patrice Matchaba from our Clinical

Research Department. In addition, we have a few

advisers with us who will be able to answer

specific questions. These are Dr. Michael Farkouh,

a cardiologist from NYU; Dr. Raymond Hirschberg, a

nephrologist from UCLA; and Dr. Thomas Schnitzer, a

rheumatologist from Northwestern.

Drs. Farkouh and Schnitzer were the lead

authors on the TARGET CV and GI publications that

were published this past September in the Lancet.

I would now like to turn the podium to Dr.

Patrice Matchaba.

Gastrointestinal and Cardiovascular Safety

of Lumiracoxib, Ibuprofen, and Naproxen

Patrice Matchaba, M.D.

DR. MATCHABA: Thank you to the Chair,

thank you to the Committee, the FDA, and the public

for inviting us. Just to state that for this

purpose, we will be discussing the cardiovascular

205

and GI safety data from the TARGET study, but we

are certainly willing to answer any question

related to an end organ, and that we have published

the data in TARGET in the Lancet, two papers.

We have two of the key primary authors for

the GI and other adverse events of safety profile,

we have Dr. Schnitzer, and for the cardiovascular

paper we have Dr. Michael Farkouh.

Before we got into the TARGET data for

cardiovascular and CV, I think it is important

underlie that when the TARGET study was designed,

that the VIGOR study and the CLASS study had been

completed, and that the discussion for the TARGET

design occurred between health authorities

including advice sought from the Arthritis Advisory

Committee in September 2001, because there were

206

important public health questions that were asked

after the CLASS study and the VIGOR study.

Some of the key issues or principles that

then drove the design of the study, the first point

was that we should designing studies to detect a

difference in ulcer complications because that was

the COX-2 promise.

As a result, more patients were required

because this event, as Dr. Cryer had discussed

yesterday, is a fairly rare event, about 1 percent

of patients, that the patient numbers required

increased to about 18,000 patients in TARGET.

The second point was that in this

population of patients that we studied in terms of

osteoarthritis, that they do take low-dose aspirin,

so we stratified patients to low-dose aspirin, and

we managed to get a 24 percent stratification, and

obviously, because of the impact of low-dose

aspirin on GI outcomes, this necessitated an

increase in the size of the study.

The other point that had been made from

the previous two studies, that the median duration

207

was short. If you recall, the VIGOR study had a

median duration of about 9 months, and the data

that we saw for CLASS was 6 months, whereas, in

TARGET, we had a fixed term design of 12 months.

The other design principle that was

important, and we have heard this data discussed

extensively, was that not all NSAIDs are the same

in terms of COX-1 and COX-2 activity and that we

will see differential GI and CV effects because of

that.

So, we chose two NSAIDs that should have a

different impact on the GI and the CV, and

addressed that question as to what is the

difference between coxibs, and in this case,

lumiracoxib between naproxen and ibuprofen.

Finally, there was a need to prospectively

define an adjudicate all outcomes, so we had three

Adjudication Committees, one for the cardiovascular

outcome, the other one for the CV, and the other

one for the hepatic events.

In terms of the objective, it was to

compare lumiracoxib at 4 times the proposed OA

208

dose, 400 mg. to naproxen 500 mg bid, and the dose

is important here, because this is the dose and the

dosing frequency that people have discussed in

terms of a possible anti-thrombotic effect, and

ibuprofen at 800 mg 3 times a day.

Key inclusion criteria that I think are

important for the endpoints is that patients who

had a previous history of a cerebrovascular or

ischemic event in terms of cardiac events were

allowed into the study if the event occurred more

than 6 months before they entered the study and if

they had been on low-dose aspirin for 3 months in

order to stabilize the patients, and this is the

advice and the current thinking that was there in

terms of patient safety if you are going to conduct

a 1-year study.

From a GI perspective, a key exclusion

criteria was that any patients who had active GI

ulcerations 30 days previously were excluded, and

any patients who had a GI bleed in the previous

year were excluded because the thinking again was

that with the availability of PPIs and high-dose H2

209

antagonists, that enrolling these patients that

required long-term treatment would have been an

unethical thing to do.

So, the study design were 2 studies that

were identical, lumiracoxib compared to naproxen in

1 study, and compared to ibuprofen in the other

study. You will note that the 2 studies are of

similar size, about 9,000 patients in each study,

and that the studies went on to 52 weeks or 1 year

with a follow-up at 56 weeks or at 1 month.

The key thing to note also is that the

naproxen sub-study started recruitment 4 to 5

months before the ibuprofen sub-study, and that

different centers were used for the 2 studies. So,

you may see differences in the baseline risk for

the endpoints that we will be discussing.

For cardiovascular and for this particular

discussion, as I said, we had a pre-defined and

prospectively adjudicated CV endpoints that

included important coronary cerebrovascular and

also the peripheral events.

In terms of the patient demographics, the

210

majority were female an average age of 63. We

managed the 24 percent aspirin stratification. Of

importance is that within this cohort of 18,325

patients, about 12 percent of these patients had a

high CV risk as defined by a previous

cerebrovascular or cardiac history or by Framingham

risk equations.

The patients were fairly representative of

an OA population. We had hypertensive patients,

diabetics, and patients with dyslipidemia. Very

importantly, because it was fixed term design, 60

percent of the patients finished the 12 months, a

total of about 11,000 taking treatment for 12

months.

For the primary endpoint, which was ulcer

complications, or perforations, obstruction, and

bleeds in the non-aspirin population, it was a

relative risk of 0.21 or a 79 percent reduction if

you compared lumiracoxib to all NSAIDs.

If you made that comparison by sub-study,

it was an 83 percent reduction compared to

ibuprofen, and 76 percent reduction compared to

211

naproxen.

So, although we have 2 different NSAIDs

with different COX-1 and COX-2 activities, this the

first GI outcome study that looked at ulcer

complications as a primary endpoint and shows

definitively a reduction in ulcer complications for

lumiracoxib compared to the NSAID studied.

A lot of the discussion, because if you

recall, we have stratified patients to low-dose

aspirin in the 24 percent of patients, about 4,000,

and the question was, and is, what is the impact of

low-dose aspirin on this outcome, and we will also

discuss the CV outcome.

Now, if you look at the ulcer

complications in the low-dose aspirin population,

and I have tried to show you an analytic figure

here, is that for the upper GI ulcer complications,

there was a relative risk of 0.79 with wide

confidence intervals crossing the line of no

difference with a point estimate showing a 21

percent reduction.

What we have done, however, for this

212

discussion is to say when we consider more events,

ulcer complications and symptomatic ulcers, is the

point estimate still favoring lumiracoxib and does

the confidence interval tighten in terms of the

precision, and you can see that the reduction

increases to 27 percent, but the confidence

interval certainly still crosses one.

In this context, it is important to

remember that the TARGET study wasn\'t designed to

show a difference in the low-dose aspirin

population, but was designed to show a difference

in the non-aspirin population, and it cascaded to

the overall population if the first result was

positive.

But what is encouraging is the consistent

trend that we see in this population.

There was discussion yesterday about do

coxibs, in this case lumiracoxib, does it still

show benefit in patients who have a high GI risk,

and this was prespecified in the TARGET analysis,

and high GI risk, there were 5 categories of risk

defined, age greater than 65, low-dose aspirin use,

213

a history of ulcers or bleeds in H. pylori-positive

patients.

When we do the analysis, taking one risk

into consideration, you see that the magnitude of

about a 3-fold reduction in favor of lumiracoxib

for ulcer complications is maintained. If we have

time later on, we can also show you the data for

patients greater than 65, for patients who were H.

pylori-positive, but because of the exclusion

criteria that I outlined beforehand for patients

who had a previous bleed, the numbers become

smaller and smaller when we look at further

increasing risk for these patients.

So, in summary, for the GI data, the

TARGET study definitively shows benefit for

patients taking lumiracoxib compared to these 2

different NSAIDs, ulcer complications in the

non-aspirin population. We have seen the high risk

or high GI population as defined in TARGET, and we

see a consistent trend although it is not

significant because of the numbers in the patients

taking low-dose aspirin.

The cardiovascular endpoint that was

chosen at that time was the APTC endpoint.

Certainly, all the other cardiovascular events were

214

also adjudicated, peripheral events, pulmonary

embolism, deep vein thrombosis.

At the time we published the data, and as

prespecified in the protocol, the plan was to

compare lumiracoxib to all NSAIDs for the APTC

endpoint, but for the purpose of this discussion,

if we do that, we fail to disaggregate the relative

results for lumiracoxib compared to naproxen and

compared to ibuprofen.

So, we will discuss the separate studies,

but, first, you will see that when you compare

lumiracoxib and NSAIDs, that there is no difference

in the APTC endpoint throughout the 12-month

period, but there is greater data and more insight

to be mined when you look at the 2 studies

separately. That is the current debate.

Before we look at the data, look at the

baseline demographics. If you recall, these were 2

parallel studies, recruiting at different centers,

215

different time points, identical in design, but

what you can see is that for the endpoint that may

have an impact on the rate of cardiovascular events

in the 2 studies, that there seems to be

differences in the low-dose aspirin use, for the

naproxen sub-study, patients who were high CV risk

and patients with baseline hypertension.

For the high CV risk patients, in terms of

patient numbers, this translates to about 140

patients difference. Now, this may or may not be a

factor in terms of looking at the differences in

rates, and there are other factors certainly that

we may not have measured that could impact on the

differences in rates.

So, we will look at the ibuprofen

sub-study first and look at the APTC endpoints,

myocardial infarcts, look at stroke, look at the

cardiorenal complications, congestive heart

failure, and a combined endpoint, and just to state

that in terms of all-cause mortality, there were 29

patients who passed away in the lumiracoxib study

arm and 30 patients in the NSAIDs, and when you

216

split it up between the 2, there was essentially no

difference.

So, for the APTC endpoint, looking at

lumiracoxib versus ibuprofen, if you start off with

the overall result, in other words, all patients

including those who took low-dose aspirin, you can

see that the hazard ratio for all populations

studied are consistently less than 1.

The other point that I want you to see is

that in the non-aspirin population, the number of

events are the same with a hazard ratio of 0.94.

There is certainly a lot of discussion and this was

thought to be part of the value of looking at the

TARGET data to ask what happens in the low-dose

aspirin population where you have this possible

interaction with ibuprofen.

You see in this population that there were

6 events in lumiracoxib and 10 in ibuprofen. This

difference, however, was not significant, and you

will see when we look at myocardial infarct, that

the number of events in this population when you

look down to myocardial infarcts, are not enough to

217

definitively contribute to this debate about the

interaction of low-dose aspirin and ibuprofen, but

certainly all the data in this 8,600 patients

studied do not indicate that lumiracoxib is any

different from ibuprofen in terms of the APTC

endpoint or cardiovascular risk.

For myocardial infarcts, going through the

same analysis, the overall population, 5 versus 7,

again, you see the hazard ratio of consistently

less than 1. The number of events are low. In the

non-aspirin population, 4 versus 5, and as I

pointed out, in this aspirin population, 1 versus

2, so difficult to comment and to contribute to the

debate about myocardial infarct and ibuprofen

interaction.

For stroke, again the number of events

were low, 8 versus 9, no real difference, 6 versus

5, and 2 versus 4 in the aspirin population,

lumiracoxib 2 events, and ibuprofen 4 events. So,

again from this data, 8,600 patients treated for 1

year, no indication that lumiracoxib is any

different from ibuprofen in this robust data set.

I think it is important to recall that

this study, in terms of patient exposure and

patient numbers, is larger than the VIGOR or the

218

CLASS study in itself in terms of exposure.

The real differences we see in the TARGET

study is in hypertension, and there has been a lot

of debate yesterday about the possible impact of

hypertension as a risk factor in contributing to an

increase in strokes and myocardial infarct, and

cardiovascular morbidity.

If we look at the cumulative incidence of

new onset hypertension or de novo hypertension, you

can see that over the study period, 360 days, that

the patients taking ibuprofen have a significantly

higher incidence of new onset hypertension compared

to the patients taking lumiracoxib. This is

percentages, number of patients.

So, it is about 10 percent of patients

with new onset hypertension with about 6 percent of

patients.

For a similar analysis looking at

aggravated hypertension, if you recall in our

219

demographic analysis, about 45 percent of the

patients in the TARGET study were hypertensive. In

terms of aggravation or worsening of the

hypertension, you see exactly the same trend

between lumiracoxib and ibuprofen, which was

significant.

If we look at the mean difference over the

entire study period, again comparing lumiracoxib

and ibuprofen for blood pressure, we see a systolic

of 2.7 for patients taking ibuprofen compared to

0.7, and we see almost a 1 millimeter increase in

blood pressure for patients taking ibuprofen with a

zero mean increase for patients on lumiracoxib, and

these differences again are statistically

significant.

There was a lot of debate yesterday as to

the possible cardiorenal implications of this in

terms of edema, congestive heart failure, and

weight gain, and if you look at the data in TARGET

for this sub-study in terms of edema, no

significant differences between the comparators,

but for edema and congestive heart failure, you see

220

that there are more patients taking lumiracoxib

with edema, congestive heart failure, but no

difference for weight gain.

There was discussion previously about how

do we assess benefit-risk. There was discussion

also yesterday that any advantage that was shown in

terms of GI ulcer complication reduction with

rofecoxib in VIGOR was negated by an increase in CV

events.

We prespecified, and this is not a

validated way of analyzing benefit or risk, but at

least we prespecified this outcome to say if we

combine ulcer complications as defined by

perforation, obstruction, and bleeds, and combine

them with the primary cardiovascular endpoint, of

the APTC endpoint, what is the trend compared to

the lumiracoxib and ibuprofen, and this is the

endpoint that I am showing you for the non-aspirin

population, that patients taking ibuprofen are

significantly worse for this combination of the 2

endpoints of GI ulcer complications and APTC.

Certainly, this is the first time that

221

this has been done in an outcome study in

arthritis, but we hope that this will contribute to

the discussion in terms of getting an overall

assessment for benefit for the patients with

osteoarthritis.

If you look at the overall population,

this difference is still significant with a 50

percent reduction, but if you look at the aspirin

population alone, the significance disappears as

would be expected.

So, in summary, in this patient population

of more than 8,500 treated and randomized to

treatment for 1 year with these doses of

lumiracoxib and ibuprofen, if we look at the APTC

endpoints, myocardial infarcts, and stroke, the

hazard ratios are consistently less than 1.

We see significant differences in

hypertension, and obviously, hypertension in the

long term, as discussed yesterday and today, may be

an impact on CV adverse events for patients with

osteoarthritis.

We have also seen that there isn\'t an

222

increase compared to ibuprofen for congestive heart

failure and for edema, and as for the combined

safety endpoint, there is a significant benefit for

patients taking lumiracoxib.

So, we will now look at the naproxen

sub-study and go through the same analysis, APTC

endpoint, myocardial infarct, stroke, cardiorenal,

the combined endpoint.

What you see immediately is that for this

sub-study, that the number of events is much

greater than the ibuprofen sub-study. Also, what

you see is that the hazard ratios are now in favor

of naproxen, and there are more events with the

lumiracoxib compared to naproxen.

You will see when we look at the next

slide, and we look at myocardial infarcts, you will

see that this is driven by the differences in

myocardial infarcts particularly in the non-aspirin

population.

So, if we look at the non-aspirin

population, patients taking lumiracoxib, 10

myocardial infarcts, clinical and silent, compared

223

to 4 in the naproxen population, a hazard ratio of

2.37, but which is not significant over the

12-month treatment period.

But the robustness and I think the value

that TARGET adds to the debate is that because we

stratified 24 percent of the population to low-dose

aspirin, when you look at the aspirin population,

you see the numeric difference or the hazard ratio

decreases in this population.

Now, low-dose aspirin we all agree has

COX-1 activity, irreversibly binds to the platelet,

and it may contribute to 10 to 30 reduction in

myocardial infarcts.

The question then was asked when we look

at this data, and this is the data that we present

to you, is that if it\'s COX-1 activity of low-dose

aspirin that is negating the differences in terms

of myocardial infarct, the implication therefore

that naproxen at 500 mg dose taken twice daily in a

clinical trial situation to ensure compliance, and

there is certainly pharmacological data that shows

that this dose has got anti-thrombotic and platelet

224

aggregation activity, that naproxen must have

significant COX-1 activity.

There has been extensive debate this

morning about observational studies, the merits of

them, and looking at the naproxen and non-naproxen

data, but this paper published by June in Lancet

last year, looking at all the studies,

observational studies, and this is not the

rofecoxib analysis, but just the observation

studies looking at naproxen.

We can see that when you combine all the

data, that the diamond at the end here shows a 14

percent reduction in myocardial infarcts with a

confidence interval that doesn\'t cross the line of

no difference or 1.

The point I think was made by a member of

the panel that in observational studies, that the

dose that is taken could be less than the 500 mg

dose, and that the dosing interval would not be the

regular dosing interval that you see in clinical

trial situation.

I think Dr. Graham also made the point

225

that in that case, you would see the point

estimates moving closer to 1 in terms of the real

effect that you would see if it had anti-thrombotic

activity.

So, you go back to the sub-study of

naproxen and look at strokes, you see that in the

non-aspirin population, small numbers, and the same

thing in the aspirin population, so no significant

differences, and the confidence intervals are

crossing 1.

Now, again when we do the analysis for

blood pressure, we see that there is significant

difference in favor of lumiracoxib compared to

naproxen. Now, if you recall in the VIGOR study,

where they compared rofecoxib to naproxen, that the

differences in blood pressure were the reverse, and

that rofecoxib increased systolic and diastolic

blood pressures, systolic by about 3 to 4

millimeters of mercury, and diastolic for this same

comparator.

The caveats are there that these are

different patient populations. The RA population

226

is a high-risk population, this is an OA

population, but without the studies that compared

directly COX-2s, this is the only way that we can

make a cross-study comparison.

Again, hypertension may be significant as

discussed in terms of long-term morbidity and

mortality.

For the same analysis we did with the

ibuprofen sub-study for de novo hypertension, and

for new aggravated hypertension, no significant

difference between lumiracoxib and naproxen

although consistently, the lumiracoxib patients

have less events over the 12 months.

This is again a revealing analysis if we

look at the cardiorenal complications. For edema,

slightly more patients having edema, 4.5 versus 4.2

percent, but we think what is encouraging is the no

increase compared to naproxen for congestive heart

failure.

Again, we saw in VIGOR, or if you look at

the VIGOR data, that rofecoxib had more patients

with congestive heart failure or pulmonary edema

227

compared to the same comparator, and we have not

seen this is the naproxen sub-study, and weight

gain, 8.1 percent versus 9 in favor of lumiracoxib.

For the same analysis we did for ibuprofen

looking at this safety endpoint that we introduced

and prespecified in TARGET, for ulcer complications

and APTC in the non-aspirin population, again we

see over time that notwithstanding the reduction

that you get with myocardial infarcts with naproxen

or when you add the 2 combined, that over time for

patients with osteoarthritis, at the doses that we

tested, that there is a significant reduction and

benefit for patients taking lumiracoxib in the

yellow line there.

So, in summary, these two studies, huge

studies, 8- to 9,000 patients, randomized to 1

year, show interesting data, and the naproxen

sub-study shows no significant increase compared to

naproxen/lumiracoxib for the APTC endpoint, but we

see these differences in myocardial infarcts with

more events in lumiracoxib, but of key importance

that when you consider the low-dose aspirin

228

population and you add COX-1 activity, that the

numeric difference disappears.

From a public health perspective, still

significant differences in blood pressure, no

increase in cardiorenal or congestive heart failure

with lumiracoxib as we saw in the other study, and

the combined safety endpoint still significantly

favor lumiracoxib.

Now, because the study included a certain

number of high-risk CV patients, it allows us to

look at a high-risk cohort within the TARGET study

and follow them over the 12 months, and asked in

this sensitive high-risk cohort of patients, what

are the outcomes in terms of APTC and myocardial

infarct, and we will discuss only the myocardial

infarct for this high risk.

A total of over 2,200 patients, and these

are patients who had a history of either coronary

artery disease, a previous myocardial infarct, and

other vascular events, and we added these patients

to those who had a high Framingham, high risk, so

over 2,200 patients treated for 1 year.

We look at the myocardial infarct data

because we will probably glean more from looking at

this specific endpoint than looking at APTC, but if

229

you have questions, we will address those

questions.

But if you look at the overall population,

these 2,200 patients, including those who were not

taking aspirin and those who were taking aspirin,

the naproxen sub-study, there were 7 myocardial

infarcts in the lumiracoxib population compared to

5\. Obviously, the number of events low,

nonsignificant, and if you look at the ibuprofen

sub-study, 1 in the lumiracoxib and 2 in the

ibuprofen sub-study.

The question, and certainly there has been

debate that by adding low-dose aspirin, which I

think everybody thought it was a good idea in the

year 2001 in terms of answering some of these

biological questions on the impact of low-dose

aspirin\--

DR. WOOD: Hang on. You are getting well

over time, so you can try and speed it up a bit.

230

Thanks.

DR. MATCHABA: Thank you.

But this population is an important

population because these 646 patients have a high

CV risk, but are not taking low-dose aspirin and

are treated over 1 year. So, high CV risk and not

on low-dose aspirin, and what you see is that in

the naproxen sub-study, 2 versus zero, and 1 versus

1\.

The last cohort are patients who had a

previous myocardial infarct, randomized to

treatment for 1 year, and there were 288 patients

who had a previous myocardial infarct, and if you

look at the repeat APTC events, for the naproxen

patients, 6 events occurred versus 3 for the

lumiracoxib, and certainly this is chance, because

the number of events are low and the patient

population is small.

But what we can comment is that we are not

seeing an outstanding signal even in this high-risk

population with all the limitations of the size of

the analysis. So, that is the TARGET data.

Finally, we performed obviously a

meta-analysis of all studies completed on the 30th

of December last year. Math has already described

231

there were 22 of those studies. You can see from

the analysis that 34,000 patients plus, 18,000

patient year exposure, that patients who were

randomized to 1-year studies accounted for almost

90 percent analysis, so it\'s a fairly robust

analysis.

If you look at the APTC endpoint, and

notwithstanding all the discussion and comment that

has come forth including from Dr. FitzGerald, that

combining all comparisons is probably not the right

thing to do, we did a comparison against all

comparators.

Now, this is a cumulative meta-analysis

and I will just quickly run through it. These are

the studies that we have done from 2001 to 2004.

These are the cumulative patients you can

see as we have added a trial, over 34,000. These

are the events as events have occurred for APTC,

156, and we have added the events to try and get an

232

estimate as they have occurred, and you can see

that the relative risk of 1.2 with a confidence

interval crossing 1. This is against all

comparators for the APTC.

We do the same analysis and we subtract

naproxen, and when you do the same analysis without

naproxen, you see the relative risk changes to

0.94, over 24,000 patients with cumulative event of

0.88. What you also see is that at no time in our

development program have we seen a significant

increase in risk.

If we look at myocardial infarct, same

analysis against all controls, a relative risk of

1.28 crossing the line of no difference. A similar

analysis minus naproxen again, and you see the

relative risk goes to 1, 24,000 patients and 34

events.

For strokes, all controls comparison, a

relative risk of 1.02, 62 events, and when we

remove naproxen for the analysis, a relative risk

of 0.84.

Now, this reduction that we are seeing in

233

the more robust data set with the meta-analysis is

certainly within the bounds of the 10 to 30 percent

benefit that you would expect from aspirin in the

idea situation.

A specific question and the comparison has

been made for the 2 studies, the naproxen sub-study

versus the VIGOR, but just to point out, and we can

have discussion if time permits, that the

half-lives are different of this compound and the

structure. Lumiracoxib has got a short half-life,

and if the hypothesis that continuous prostacyclin

inhibitor is important, this may be an important

factor.

A median 9-month versus 12 months, seeing

a significant difference with the caveats of the

different populations, but not seeing it in a

similar population not taking low-dose aspirin, and

we have commented about the differences in the

congestive heart failure and the hypertension,

which we think plays a significant role with time.

The final slide I think has been discussed

before in terms of prostacyclin, and if the Chair

234

and the committee decides we can discuss that more

in detail, but the fact that the other NSAIDs also

show a prostacyclin inhibition compared to the

COX-2s.

So, in summary, we have seen that the

meta-analysis is supportive of the data that we are

seeing in TARGET. It\'s a robust meta-analysis,

34,000 patient. We are seeing that each time you

removed naproxen from the comparison, you are

getting your 10 to 30 percent difference and that

at no time point during our development program

have we seen a significant increase for the APTC

endpoint.

Importantly, we are seeing no increase

with lumiracoxib with congestive heart failure and

hypertension.

The question was asked, and this obviously

is the subject to further debate as to what do we

think as a company going forward.

Thank you, Mr. Chair, and thank you,

committee.

DR. WOOD: Great. Thanks very much.

We are going to break for lunch and I have

to remind the members to turn in their dinner

reservation form I guess to Kimberly, and we have a

235

table reserved for the committee members in the

restaurant. We will be back here and start at 1

o\'clock, so you had better grab it and eat.

(Lunch recess.)

236

A F T E R N O O N P R O C E E D I N G S

(1:04 p.m.)

Open Public Hearing

DR. WOOD: Let me begin by reading the

conflict of interest statement.

Both the Food and Drug Administration and

the public believe in a transparent process for

information gathering and decisionmaking. To

ensure such transparency at the open public hearing

session of the Advisory Committee meeting, FDA

believes that it is important to understand the

context of an individual\'s presentation.

For this reason, the FDA encourages you,

the open public hearing speaker, at the beginning

of your written or oral statement to advise the

committee of any financial relationship that you

may have with the sponsors of any products in the

pharmaceutical category under discussion at today\'s

meeting.

For example, this financial information

may include the sponsor\'s payment of your travel,

lodging, or other expenses in connection with your

237

attendance at the meeting.

Likewise, the FDA encourages you at the

beginning of your statement to advise the committee

if you do not have any such financial

relationships. If you choose not to address this

issue of financial relationships at the beginning

of your statement, it will not preclude you from

speaking.

We are ready to go and let me give you the

ground rules before we start, so that everybody

understands. You get two minutes to talk. We have

a light there that will go on. At 1.5 minutes it

will be green, and then yellow, and then at zero,

the microphone will go dead and only your lips will

keep moving.

So, it is important at that point to sit

down because the next guy is coming up to take that

microphone.

Let\'s get started. I will be impolite

enough to call you by number rather than by name

because that is what I have here. If there are

people who have registered to speak and have not

238

yet checked in, they need to go to the check-in

desk outside and check in rapidly or someone else

will get their spot.

Let\'s begin with Speaker No. 1.

MS. JOAN JOHNSON: Hello. I am Joan

Brierton Johnson and this is my 7-year-old daughter

Sabrina. She writes:

\"Dear FDA:

When I was 6 years old, I had fun visiting

my friends, playing computer games, and drawing

lots of pictures. All of that ended when I came

home from the first grade, not feeling very well.

My parents gave me Children\'s Motrin, but

instead of getting better, I got Stevens-Johnson

Syndrome.

Taking Children\'s Motrin is why I am blind

today.

Now I wear a hat that covers my entire

face - even indoors - because the light hurts my

eyes. When I go outside, I get teased because of

my hat. People say mean things to me about it and

that really hurts my feelings.

I liked going to school, but my immune

system is now so weak because of SJS that it is not

safe for me to go anymore. I miss my friends.

239

Millions of kids all over the world are

given Children\'s Motrin when they get sick. But it

doesn\'t have a warning label on it about SJS.

I would like to ask the FDA to require a

warning label about SJS on Children\'s Motrin and on

any other drugs that can cause this horrible

disease.

Thank you for considering my request.

Sabrina Brierton Johnson, age 7, Topanga,

California.\"

Now, Sabrina would like to say a few

words.

MS. SABRINA JOHNSON: Please do something

so other children don\'t get hurt by Stevens-Johnson

Syndrome like me. People really need to know about

it. Thank you.

MS. JOAN JOHNSON: Thank you.

DR. WOOD: Thank you very much.

No. 2.

(No response.)

DR. WOOD: No No. 2. All right. Let\'s

move on to No. 3, I know he will be here.

DR. WOLFE: Before the clock starts, I

have no conflict of interest.

Four years ago, I testified before this

240

committee that FDA should require a black box

warning on Vioxx and Celebrex because of

significant evidence from the VIGOR study and

trends in CLASS of increased cardiovascular risk.

What the FDA, the Advisory Committee, nor

I knew then was that in the year 2000 Pfizer had

finished a study, a placebo-controlled trial using

Celebrex to prevent Alzheimer\'s disease progression

and that the study had found increased

cardiovascular risks for the drug.

What I did not know several weeks ago,

when I made the results of this yet unpublished

study public, was that the FDA had been provided

the results of this study in June of 2001, even

though they held back, Pfizer held back the study

so that it wasn\'t discussed at the Advisory

241

Committee meeting four years ago, which would have

presented a class effect for Vioxx and this drug.

FDA was concerned enough about this study

that it presented it internally at a meeting in

2001, but never revealed the results to the public

until yesterday in Dr. Witter\'s presentation, which

acknowledged that in almost every type of adverse

cardiovascular outcome, the cases occurred mainly

in those using Celebrex, 3 cardiovascular deaths,

non-fatal heart attacks, strokes, heart failure or

angina out of 140 in the placebo group, 20 out of

285 in the Celebrex group.

Because of much prevarication, to put it

mildly, by Pfizer yesterday, Pfizer testified under

oath they might have been found to have committed

perjury. I recommended today that Pfizer be

criminally prosecuted for fraud to the U.S.

Attorney\'s Office if they aren\'t already conducting

such an investigation, and it appears that Senator

Grassley\'s office will take up the investigation as

to why FDA withheld this information for so long.

I sent this testimony to them.

Given that Celebrex and Bextra are making

an important contribution of the estimated 100,000

deaths and 2 million serious injuries a year from

242

adverse drug reactions, I hope you will recommend a

ban of these drugs, not a don\'t use for more than

10 days.

DR. WOOD: Thank you.

No. 4.

MS. SUYDAM: Thank you for the opportunity

to present an over-the-counter or OTC perspective

on the safety of nonsteroidal anti-inflammatory

drugs. The Consumer Healthcare Products

Association is a national trade association

representing manufacturers and distributors of OTC

medicines and has a long history of working with

FDA on important safety issues.

In considering the safety of NSAIDs, I ask

the Advisory Committee to consider three important

points.

First, the use of OTC NSAIDs clearly

should be distinguished from long-term or chronic

prescription use. OTC NSAIDs have a different

243

overall benefit-to-risk equation and a wider margin

of safety because they are used at lower doses and

are not intended to be used on a chronic basis

unless directed by a physician and are used for

mild, self-limiting conditions.

Second, OTC medicines differ from

prescription drugs because the OTC label contains

all of the information that consumers need to

decide if the medicine is right for them, how to

take the product, and when to see their doctor if

needed.

OTC NSAIDs are not intended to be used for

long durations unless directed by a physician, and

this is clearly stated on the label.

Third, OTC NSAIDs are safe for consumer

use when used according to label conditions. Every

OTC NSAID has been extensively reviewed by FDA and

FDA Advisory Committees. This review has confirmed

that OTC NSAIDs are safe and effective and that the

benefits of OTC use outweigh the risks.

In closing, it is important to clearly

distinguish the benefit-to-risk equation for

244

prescription NSAIDs from that of OTC NSAIDs. The

millions of consumers who rely on OTC NSAIDs for

temporary pain relief should continue to feel

confident that these medicines are safe and

effective when used according to the label.

DR. WOOD: Thank you.

Jennifer Lo.

DR. LO: To facilitate the benefit and

risk assessment of COX-2 inhibitor in each

individual, we propose to the Committee a new test

under development, iHAD test, used to assess the

cardiovascular disease risk in patients taking

COX-2 inhibitors.

Our test reveals the pathobiological

effect of inflammatory mediators/inflammation

related agents (IRAs) on each individual\'s vascular

system ex vivo. Individuals found to be at high

risk because they are likely to suffer the same

pathobiological effect of IRSs if present under

desirable conditions in vivo.

The ex vivo pathobiological effect may be

quantified in the form of cytotoxicity which can be

245

revealed in 2 general categories: cytolysis and

cyto-aggregation. The severity of cytotoxicity is

used to determine the level of CVD risk of

asymptomatic individuals. Individuals tested with

a high risk may choose not to use COX-2 inhibitors.

Others tested with a low risk may benefit from the

use of COX-2 inhibitors with periodic retesting.

This picture depicts the cytolysis of

cultured fibroblast induced by the basic nature of

a protein like many inflammatory mediators.

The next picture depicts the

cyto-aggregation of human blood cells induced by

multiple IRAs. Phospholipase A2 is one of the many

significant inflammatory mediators used in our

assessment test.

This simplified proposed mechanism for

Acute Coronary Syndromes (ACS) forms the basis of

our new iHAD test, including the involvement of

COX-2 inhibitors. Inflammation produces many IRAs

and some of them are prothrombotic. PLA2 and other

IRAs act on blood components to cause cell damage

in the form of cytotoxicity.

Cytolosis may be responsible for rupturing

atherosclerotic plaques, leading to

thromboembolism, predisposing ACS.

246

Cyto-aggregation may lead to thrombosis,

predisposing ACS.

COX-2 inhibitors prevent the synthesis of

Prostaglandin (PGE2) that is responsible for

triggering the pain, but they have no inhibitory

effect on arachidonic acid (AA) a byproduct of

phospholipase A2, which is also prothrombotic.

Our new iHAD test is intended to evaluate

the response of individual blood cells to IRAs in

assessing the baseline CVD risk based on the

severity of cytotoxicity.

We urge all individuals taking the COX-2

inhibitors or considering taking the drug to take

the iHAD test.

DR. WOOD: Thanks.

No. 6, Jim Tozzi.

MR. TOZZI: Thank you, Mr. Chairman,

Distinguished members of the Committee. Having

been a resident of New Orleans, I cannot speak that

247

fast, and I have burned up 10 minutes or 10 seconds

I am Jim Tozzi. I am the member of the

Board of Advisors of the Center for Regulatory

Effectiveness. The Center receives no funding from

the pharmaceutical industry although a number of

years ago we did receive grants from the industry.

The Center is a regulatory watchdog. To

this end, we have a particular interest in the FDA

compliance with the requirements of the recently

passed Data Quality Act. When the agency makes

determinations regarding the benefits and risks

associated with the use of non-steroidal

anti-inflationary drugs\--sorry, I am an

economist\--anti-inflammatory drugs. They may be

anti-inflationary, too.

The Data Quality Act required OMB and FDA

to issue guidelines which would maximize the

quality, the objectivity, the integrity, and the

information FDA disseminates to the public.

So, you may be asking why am I here.

Well, the guidelines require certain analytical

results to be reproductive and

248

unbiased\--reproducible and unbiased. The Data

Quality Act places no requirements on the

distinguished members of this committee, however,

the FDA cannot rely upon the information it

receives from the advisory committee unless the

advisory committee information meets the

requirements of the Data Quality Act.

Furthermore, any third party, such as CRA,

can petition under this act for FDA not to use the

results if they do not comply with the Data Quality

Act, and I thank FDA for allowing\--.

DR. WOOD: No. 7. Dianna Zuckerman.

MS. ZUCKERMAN: The National Research

Center for Women and Families is an independent

nonprofit organization with no conflicts of

interest on this issue.

We focus on research, but we know that

when Americans take medication, they don\'t expect

to have to read the studies that have been

conducted on the product, and their physicians

don\'t expect to have to read them either, and the

patients don\'t expect to have to carefully

249

scrutinize the fine print and personally weigh the

risks and benefits.

They expect that medications that are

FDA-approved are safe and effective for almost

everyone and therefore safe for them.

So, please, when you vote tomorrow, please

treat your votes as if they are the most important

ones you will ever make, because there are a lot of

people depending on you.

There is plenty to be concerned about

regarding the medications that you are considering,

but unfortunately, we don\'t have access to all the

data that you have access to, so I am going to

focus on the broader issue, which is the failure of

the FDA to scrutinize long-term safety data.

This is a systemic problem and it will not

be fixed by wishful thinking or by advisory panel

instructions.

Unfortunately, drugs that are studied on a

few hundred or even a few thousand people, for a

few weeks or months, are then taken, as you know,

by millions of people for many years. The FDA

250

really doesn\'t always know what the long-term risks

are especially if the companies involved don\'t

reveal all the information that they have.

The FDA should be requiring and carefully

monitoring long-term studies of medical products

that patients will rely on for a long time. Our

Government needs to strengthen the FDA and other

security checkpoints designed to protect us from

those very real dangers.

In the meantime, please don\'t assume that

the companies can be trusted to carefully conduct

postmarket studies or that the FDA will enforce

requirements to conduct such studies and act on

their results in a\--.

DR. WOOD: Thank you very much.

The next speaker is No. 8, Elizabeth

Tindall.

DR. TINDALL: Good afternoon. I am Dr.

Elizabeth Tindall and I am speaking today as a

practicing rheumatologist from Portland, Oregon,

and as President of the American College of

Rheumatology. I have no consulting or financial

251

relationships with the companies or products being

discussed at this meeting.

The ACR represents more than 6,000

physicians, scientists, and health care

professionals who care for people with arthritis

and other musculoskeletal diseases. Our members are

actively involved in treating the estimated 70

million Americans who are affected by

osteoarthritis, rheumatoid arthritis, and other

musculoskeletal diseases for which traditional

NSAIDs and COX-2 selective NSAIDs are used.

Limited and emerging data about the

cardiovascular toxicity of COX-2 and non-selective

NSAIDs, which has received widespread media

coverage, has caused anxiety among the patients and

the physicians who treat them. We are concerned

that this controversy has damaged public confidence

and trust in drug safety, and we believe the

following points are central to the continued

discussion of this issue.

First, the FDA should lead the effort to

ensure that patients and the public are made much

252

more aware of the most common and serious

toxicities of all medications including those of

the traditional and COX-2 selective NSAIDs.

This information should be given to the

public with information about what groups of

patients may be at greatest risks including age and

underlying comorbidities. That allows physicians

and patients to make the best decision about their

health care.

The American College of Rheumatology

supports the FDA\'s efforts to ensure clarification

of the most important drug toxicities in all

direct-to-consumer advertising in print and

broadcast media, and we also applaud the full

disclosure of any advertising presented to the

public as promotional educational material.

We also support the full disclosure of the

test results of all industry-related trials for

drugs that are FDA approved, so that public and

scientific scrutiny may occur. We applaud the FDA

in forming a new independent drug safety oversight

board this week. This board must ensure that all\--.

DR. WOOD: Thank you very much.

The next speaker is No. 9. Dimitra

Poulos.

253

MS. POULOS: Good afternoon and I am here

at my own expense.

Every time you take a drug, there is a

risk factor to be considered. I believe it\'s

important for the government to keep us informed on

all drug findings and potential risks, so we are

able to make informed decisions.

Cigarettes come with a warning label,

there is no prescription needed for alcohol, yet

taken by the wrong person, we are all at risk.

Liver is damaged from Lamasil and Lipitor,

Coumadin is a risk of bleeding to death.

When I was diagnosed with rheumatoid

arthritis in 1998, my life changed dramatically.

Professionally, it had an impact on the quality of

my work. Socially, I could no longer sit in a

movie theater, take a walk, car trips to visit

out-of-town family members was out of the question.

Personally, arthritis attacked my husband,

254

too. He had to assume most of my responsibilities

for running the house. As daily functions became

impossible for me, I needed his help to get

dressed. On day he found me in the bathroom, on

the commode, crying, unable to get off of it.

But that was before Vioxx. I have taken

Vioxx for over 5 years with absolutely no side

effects. Vioxx gave me my life back. We have no

idea of the risks involved with any of the new

drugs, but a known risk can be dealt with.

As I speak, I have 40 Vioxx left. I have

40 days before my life and my abilities will be

severely altered.

I will assume all responsibility and sign

any waiver. Please give me that option and thank

you for allowing me this time.

DR. WOOD: Thank you very much.

The next speaker is No. 10, John Pippin.

DR. PIPPIN: Before the clock starts, may

I mention my affiliations? I am here representing

myself and the Physician\'s Committee for

Responsible Medicine, a nonprofit. I have no

255

commercial affiliations.

While the primary focus of these meetings

concerns whether the COX-2 inhibitors should be

withdrawn from clinical use, we also must address

the more fundamental problem regarding drugs

developed and approved in the U.S., and that

problem is how to identify safe and effective drugs

before they are approved for human use.

The greatest obstacle to accomplish this

goal is the continued use of animal testing to

evaluate drug safety and efficacy. For reasons

which are genetically based and immutable, drug

testing in rodents, rabbits, dogs, and monkeys

produces widely different results, none of which

correlates with human results.

For example, 9 of 11 studies of vascular

disease in mice and rats showed that COX-2

inhibitors, the very drugs we are talking about

today, were beneficial for heart disease, and, in

fact, some of the investigators suggested they

would be useful drugs for heart disease. We know

from the clinical trials that all three COX-2

256

inhibitors are dangerous for heart disease.

What I have just told you is no secret.

Everyone involved, the pharmaceutical companies,

their researchers, the FDA, we all know that animal

testing is unreliable. However, we have been

unreasonably slow to replace animal testing with

newer and better tests for drug safety and

efficacy.

First of all, we must eliminate animal

testing from this process since this flawed method

costs billions of dollars and tens of thousands of

human lives annually in the U.S. In-vitro testing

using human cells and tissues, computer-based

modeling, microdosing studies in humans, stem cell

technology to allow testing of human cells and

tissues, and the burgeoning field of

pharmacogenomics, which allows us to compare DNA

and predict toxicity and efficacy of the drugs.

They are all superior to animal testing.

We should be promoting these methods. As a group,

these methods are light years ahead of our crude

animal tests, they are safe, accurate, and cost

257

effective, and we must move toward these methods if

we are to have safe and effective medicines in

America.

DR. WOOD: Thank you.

No. 11. Major Grubb.

DR. GRUBB: I am Christopher Grubb, M.D.

I am in the Army Medical Corps at Fort Bragg, North

Carolina. I am supported by the Department of

Defense and I have no financial interests. As a

military physician, I have no other interests at

heart but the health and safety of our men and

women in uniform.

As a pain specialist, my mission is to

conserve the fighting strength by treating acute

and chronic pain in our active duty soldiers and

returning them to the battlefield.

However, we don\'t like to send soldiers

into harm\'s way on non-selective NSAIDs due to

their anticoagulant effects and the potential for

worsening bleeding after battlefield trauma.

Instead, they go to war with COX-2 selective

inhibitors or coxibs.

Consequently, the 82nd Airborne

Paratroopers are required to carry a coxib drug to

be taken in the event of a battlefield injury, one

258

of three drugs in what is called the soldier\'s pill

pack.

Many soldiers are fearful of the bleeding

risk with NSAIDs, so they ask specifically for

coxibs. Since service members are young and very

physically fit, the armed forces constitutes one of

the lowest cardiovascular risk populations in our

society, so the recent COX-2 risk data was of very

little concern to the military.

So, in this meeting, we warn against using

a broad brush when painting the portrait of risk.

Military personnel suffer frequent injuries and

have a higher incidence of chronic pain than

civilians, further increasing our need for coxibs.

Coxibs have allowed the worldwide

deployment of many previously disabled soldiers.

Many are now in Iraq on daily regimens of coxibs.

Without these products, we can\'t keep as many

soldiers functional on the battlefield.

The study of coxibs for chronic pain is in

its infancy. Although efficacy data for coxibs may

be equivocal for arthritic conditions versus

NSAIDs, the same can\'t be assumed for other types

of pain. Indeed, most military personnel use

coxibs for non-arthritic pain, such as low back

259

pain. We have found coxibs to be superior to

NSAIDs for spine pain, so we are planning

controlled trials of our own to compare these drugs

head to head.

In summary, our bravest Americans are

reaping benefits from coxibs without drug adverse

events. This large population should not be

disenfranchised here. Consider our military in

this particular drug decision. Coxibs are

essential in the global war on terrorism.

Thank you.

DR. WOOD: Thank you.

Dr. Arrowsmith Lowe, No. 12. Not here?

Okay, we will go on to No. 13, Mark Einstein.

DR. EINSTEIN: My name is Dr. Mark

Einstein and I am an Assistant Professor of

260

Gynecologic Oncology at the Albert Einstein College

of Medicine, Montefiore Medical Center at Bronx,

New York.

My academic department has supported my

expenses to attend this meeting. I have not been

asked to speak to you by any pharmaceutical

company, however, one of my clinical trials is

partially supported by an unrestricted grant from

Pfizer.

As a gynecologic oncologist, I am

committed to finding new therapies to prevent and

treat women\'s cancers. Recent trend data suggest

cancer is overtaking cardiovascular disease as the

leading cause of death in the U.S.

COX-2 inhibitors are one of the promising

class of agents used in cancer therapy, however,

many current and planned cancer clinical trials

using COX-2 inhibitors are on hold pending the

results of these hearings.

Expression of COX-2 has been identified in

many human cancers including gynecologic cancers.

One of the COX-2-expressing cancers is endometrial

261

cancer, which is the second most common gynecologic

malignancy in the U.S. after another

COX-2-expressing cancer, breast cancer.

The number of deaths from endometrial

cancer has risen 128 percent since 1987. Responses

to toxic chemotherapy in women with recurrent

endometrial cancer are dismal. These generally

elderly women have comorbidities that also limit

their tolerability of chemotherapy.

We identified high rates of COX-2

expression in the most chemo-refractory endometrial

cancers. These data led us to begin a pilot trial

using Celebrex in women with endometrial cancer

that is grant supported by the American College of

Ob-Gyn. This trial has been suspended.

Cervical cancer, the number 1 cancer

killer of women in many countries also strongly

expresses COX-2. Currently, two cooperative group

trials that were designed to observe the effects of

Celebrex in pre-invasive cervical cancer have also

been suspended.

COX-2 inhibitors are one of the targeted

262

agents that are being used for prophylaxis in women

at risk for ovarian cancer where survival using

toxic chemotherapy regimens has not changed in over

15 years.

In summary, gynecologic cancers remain a

critical issue in women\'s health and standard

therapy are not very effective at limiting the

death rate and are not well tolerated. The thought

of using target agents, such as COX-2 inhibitors

that have less toxicities than most chemotherapies

have many\--

DR. WOOD: We found No. 12.

DR. LOWE: My name is Janet Arrowsmith

Lowe. I am a physician and epidemiologist and the

president of a small consulting firm in a tiny town

in New Mexico. I do want to state that some of my

clients, my pharmaceutical clients include Bayer,

Glaxo-Smith-Kline, Merck, Pfizer, and Wyeth, but

today I am just representing myself and my firm.

It has been refreshing to hear discussion

of risk and benefit, because I think too often in

the press, concerning safety of marketed drugs only

263

risk is discussed, and I think as we all know, that

when a product is approved, FDA weighs risk and

benefit before approval.

Now, the calculus may change over time as

new drugs or new information is available, but in

my several years of experience at FDA, and since

leaving, I am assured that the agency is still

functioning, and I don\'t believe that FDA is

broken.

It is not perfect. Is there a perfect

institution? But it probably can be improved, but

I think the proposals for a separate agency for the

review of safety are not rational. I think that

the premarket review really provides appropriate

balance in deciding whether a product should stay

on the market.

Now, I would like to see greater access to

some drug development data including more

user-friendly public access to the safety databases

at FDA modeled along the lines of the MOD database

in the Center for Devices.

So, in my opinion, the public health is

264

best served by a careful study of risks and

benefits, and FDA, with the proper funding balance

and authority, an engaged industry, and an educated

public.

Thank you very much.

DR. WOOD: Thank you.

Next, we will go to No. 14, who is Dr.

Abramson.

DR. ABRAMSON: Thank you for having me

here. I do serve as an expert on cases involving

Vioxx and Celebrex. I want to say that in order to

get to the bottom of what went wrong with Vioxx, I

think it is important to address first what went

right.

At the February 2001 Advisory Committee

meeting, the reports of the FDA reviewer showed

conclusively that Vioxx caused significantly more

cardiovascular complications in people with and

without cardiovascular history, and overall, the

people who took Vioxx developed 21 percent more

serious complications.

So, the question before us is why do

265

American physicians prescribe \$7 billion worth of

Vioxx after Merck and the FDA knew that Vioxx was

significantly more dangerous, no more effective,

and far more expensive than naproxen.

In order to answer that question, we need

to look at the sources of information that

physicians trust most. That data was reported in

the New England Journal of Medicine in 2000. The

article acknowledged that there was a

cardiovascular risk in theory and measured

cardiovascular events, but the article did not

report those cardiovascular events, nor did the

article report serious adverse events overall.

It did report heart attacks. The heart

attacks were reported as not statistically

significant in people without a cardiac history,

and therefore, the issue was not brought to

physicians\' attention. All 13 authors had

financial ties to Merck.

We look at the clinical practice

guidelines from the American College of

Rheumatology. We see that first is Tylenol, and

266

next recommended is Vioxx and Celebrex. All four

authors have financial ties to the manufacturers of

both drugs.

The problem here is that the information

that docs are getting is so heavily filtered

through commercial sources that no matter what the

FDA does with drug safety, unless the integrity or

doctors\' information is not improved and doctors

and patients don\'t take good information into the

exam rooms, this exercise is going to be for

naught, and the quality of American medicine will

not improve.

DR. WOOD: Thank you.

We will go to No. 15, Dr. Baraf.

DR. BARAF: I have consulted to and

performed clinical trials for many of the companies

whose drugs are being discussed today.

As a busy practicing rheumatologist, I

have asked to be here to speak for my patients with

arthritis. For four and a half months, their needs

have been ignored in virtually every news report

and medical journal editorial discussing NSAID

267

therapy.

Indeed, we have all learned that we must

be more mindful of each patient\'s risk factors for

cardiovascular disease in selecting COX-2s or other

NSAID treatment, but data regarding this risk for

COX-2 inhibitors is incomplete, sometimes

contradictory, and begs further investigation.

The risk for cardiovascular disease with

non-selective NSAIDs is unknown and untested. I

urge this panel to give careful thought to the

considerable benefits COX-2 inhibitors offer

patients with arthritis especially those with GI

risks.

For large numbers of my patients, COX-2

inhibitor diminish the threat of serious

drug-induced gastrointestinal injury, thereby

eliminating a major barrier to their treatment.

How are we to balance the competing risks of

cardiovascular and GI toxicity against real

therapeutic need for patients with debilitating

pain?

We must heed the advice that we give to

268

our patients. There are no completely safe drugs

in any treatment category. It is my responsibility

to weigh and risks and benefits of drugs with my

patients, to make individualized decisions.

Sensationalizing and highlighting only the

risks of these drugs based on scanty and incomplete

information, as many of our colleagues have chosen

to do, have created an atmosphere in which an

informed discussion with patients is difficult, if

not impossible.

For many patients with arthritis, these

drugs are not superfluous as some have suggested,

but greatly impact their quality of life. To

withdraw one drug might put us on a slippery slope,

leading to withdrawal of all NSAIDs. My patients

must not be denied access to the widest variety of

therapeutic options.

Thank you.

DR. WOOD: Thank you.

No. 16. Dr. Hamburger.

DR. HAMBURGER: I am a practicing

rheumatologist and the President of the New York

269

State Rheumatology Society. I have been a speaker

for several of pharmaceutical companies mentioned

today.

I polled New York rheumatologists, State

rheumatology society leaders, and I spoke to my

patients, and we have remarkably consistent views.

Events have reminded everyone of what

rheumatologists and our patients already know.

NSAIDs are important because of their role in the

treatment of the pain of arthritis and because of

the numbers of people who suffer from this pain.

We have seen recently far too many

patients who have experienced the recurrence of

their pain and their suffering because they stopped

their medications out of fear or because of changes

in managed care formularies.

None of us can emphasize enough the

importance to these patients of reducing their pain

and preserving their mobility. So, our consensus

opinions are, number one, that access to

anti-inflammatories needs to be preserved.

Physicians and patients need to be provided with

270

the important information about these medications

in a more rational and timely fashion, and the

process for disseminating this information should

be improved.

The coxibs, we have learned today, and we

have known, have less GI toxicity, but their own

side effects. Everyone wants an NSAID free of

toxicity, but no one can say today to any patient

that this NSAID has been tested and found to have

no CV, GI, or renal toxicity.

So, we need to maintain access while

deciding the best next research.

Patients act on what they read and hear,

and they believe the information that appears in

the media. The evidence on NSAIDs presented to the

public has focused on only a small number of

published studies, and the public is making its

judgments without knowing all the information.

Juries in this country do not deliberate

and reach a verdict based on the last three pieces

of evidence.

DR. WOOD: Thank you.

The next speaker will be Dr. Qureshi, No.

17\.

DR. QURESHI: Good afternoon. Before I

271

start I should let you know that I am being paid by

Given Imaging to be here, but not enough to

influence my results.

I am going to talk about NSAIDs and the

small intestine injury they cause. The occasional

findings of intestinal blood loss or anemia in the

setting of normal upper and lower endoscopy led to

the realization that NSAIDs cause significant

disease in the small intestine.

We performed the first controlled study to

look at NSAIDs using new technology that is a

camera pill that takes a video wirelessly of the

small bowel. We looked at 41 patients, half of

them on NSAIDs for at least three months and half

that took Tylenol or nothing.

This is a camera that you swallow.

Much to our surprise, we found small

ulcers in the small bowel, large ulcers, and

bleeding in the small intestine.

We found that 71 percent of NSAIDs takers

had some form of injury in their small intestine,

20 percent had severe injury compared to none in

the controls.

So, symptoms and signs of ill health among

chronic NSAIDs users is often attributed to the

272

underlying disease, but we think that dyspepsia and

not responding to acid suppression, vague abdominal

symptoms, iron deficiency anemia, or

hypoalbuminemia may result from small intestinal

injury.

We have a new technology now that enables

us to look at the small intestine. Video capsule

endoscopy is very useful for diagnosing and for

comparing the damage that different NSAIDs might

cause on the small bowel, and in a subset of

patients where we suspect small bowel injury, this

technology is useful and shows promise.

Thank you.

DR. WOOD: Thank you.

We will go on to No. 18, Mr. Matthews.

MR. MATTHEWS: Thank you. My name is

273

David Matthews. I am a lawyer and I represent

individuals who have been harmed by the drugs being

discussed here today.

The fact that these hearings have become

necessary to address the safety of COX-2 drugs is

yet another tragic example of the continuing

failure of the pharmaceutical industry to disclose

the truth, the whole truth, and nothing but the

truth to the FDA, prescribing physicians, and the

citizens of this country.

Why is the whole truth not forthcoming?

Simple. Billions and billions of profit dollars and

absolutely zero individual accountability by

company officers who submit drug safety data both

before and after a drug is approved.

With the coxibs, the FDA has had to

negotiate with the drug sponsors to change labels,

conduct patient and physician education, limit

advertising, modify approved indications, and to

even complete studies.

The time for these negotiations should

end. In response to a rash of corporate scandals

274

involving the likes of Tyco, WorldComm, Enron, and

others, Congress passed the Sarbanes-Oxley Act of

2002\. It provides criminal penalties of up to \$5

million and 20 years in prison for knowingly

submitting false finance information to the SEC.

These penalties are for lying about a

company\'s financial status, not for causing injury

or death to an individual. Because everyone

deserves nothing less than the whole truth from

pharmaceutical companies and complete disclosure

about clinical trial data, there must be personal

accountability for any individual who fails to do

so.

I urge Congress, and I hope these hearings

can be a springboard, to enact legislation which

follows the Sarbanes-Oxley Act, but with more

severe penalties for any drug company, officer, or

employee who submits false, misleading, or

deceptively modified drug safety data to the FDA, a

physician, or to the public.

If someone who submits false financial

information to the SEC can be filed \$5 million and

275

sentenced to 20 years in prison, there is no

compelling reason that the penalties for submitting

false, misleading, or deceptively modified data to

the FDA.

DR. WOOD: Next speaker will be No. 19,

Dr. Wilson, and as you start, Dr. Wilson\--we are

not counting your time yet\--try and step back a

little bit from the microphone. Apparently, there

is a lot of distortion from people being too close

to the microphone, and that goes to the other

speakers, as well. Thanks.

DR. WILSON: First of all, I have no

sponsorship, I am here on my own recognizance. I

am a practicing rheumatologist in Atlanta, Georgia,

and my life is dedicated to alleviating the pain of

arthritis.

Almost 2 million Georgians suffer from

arthritis. In fact, the latest figures from the

CDC are that 1 in every 4 Georgians has a chronic

joint symptom, and arthritis is the number one

cause of disability in America.

Pain matters. It may not kill you, but

276

you may wish that you were dead.

My patients are not concerned about living

forever, they want to live well without arthritis

pain. It is not surprise that the more experience

we gain using medications, the more we learn when

to use it and when not to use it. Patients do not

take medications if they don\'t work, and millions

of patients taking COX-2 selective medications

evidence that they are effective. Indeed, this has

been my experience.

I am concerned about safety. We should

try to figure out what is unique about the 1 to 2

percent of patients with very serious side effects

rather than depriving the 98 to 99 percent of

patients with significant relief from their

arthritis pain who have not experienced a serious

side effect.

In a perfect world, I would have endless

choices because all patients are not created equal.

I believe that the choice to choose COX-2 selective

medications is too important to answer for the

patient. To limit choices based on evolving

277

knowledge is unfair to tens of millions of

Americans with arthritis pain.

On average, 29 people a week die in a car

in Georgia. I suspect that all of us came in a

motor vehicle today and accepted a risk.

We must consider both sides of the

equation when we decide how to treat patients and

what to treat them with. Ideally, it should be a

patient\'s decision to decide based on the

information provided by their personal physician.

Most of my patients would take some

significant risk for a better quality of life with

relief from arthritis pain. Please thoughtfully

consider our patients\' pain when you make your

decision.

Thank you for your time.

DR. WOOD: Thank you.

The next speaker is No. 20. Dr. Williams.

DR. WILLIAMS: I am Dr. Gary Williams. I

am here on my own time and at my own expense.

It is generally accepted that COX-2

inhibitors are a safer alternative to patients with

278

arthritis. Cost containment has been a competing

force. Those among us who feel these drugs are

expensive or overused may be pleased with the

recent changes in the market share of COX-2

specific drugs.

This shift has been caused largely by

prolonged concerns regarding Vioxx, culminating in

the decision by its manufacturer to withdraw the

drug from the market.

Our current attention is directed to

possible cardiovascular risks for two currently

marketed drugs, celecoxib and valdecoxib. The data

that concerns us is to date in non-arthritis trials

designed to explore possible additional uses of

these drugs beyond their current indications.

The largest effort to date to assess the

impact of these drugs on cardiovascular risk in

patients using them for their current indications

is the FDA-sponsored Kaiser trial. This trial

reinforces the cardiovascular risk for users of

Vioxx and raises additional concerns for possible

increases in cardiovascular risk in users of

279

nonsteroidal anti-inflammatory drugs including

Naprosyn.

In this trial, Celebrex was not associated

with increased risk compared to any other treatment

option or even when compared to non-users or remote

users of any of the treatment options.

On this background, we should be cautious

in recommending that thousands, or even millions,

of current users of COX-2 specific inhibitors move

to other, older non-selective NSAID options.

We should be realistic and assume that

they will continue to use anti-inflammatory drugs

obtained either over the counter or by

prescription. Since they would be moving away from

the GI safety advantage demonstrated with the COX-2

selective drugs toward the options included in the

Kaiser trial, they would be moving toward

increasing GI risk.

Unfortunately, as it relates to the

decisions facing this Advisory Committee, the same

FDA Kaiser data suggests that the recommended

movement\--

DR. WOOD: Thank you.

The next speaker is Rebecca Burkholder,

No. 21.

280

MS. BURKHOLDER: I am Rebecca Burkholder

from the National Consumers League. In the

interest of full disclosure, NCL occasionally

receives unrestricted financial support from

pharmaceutical companies for consumer education and

research projects. The research cited below is one

of those projects. My expenses for this meeting

were not paid by an external organization and my

statement reflects the interests of those NCL

represents, consumers.

NCL urges the FDA to carefully weigh the

risk and benefits of COX-2 inhibitors as it decides

how best to protect the public. Whatever action

this committee takes, NCL believes it is important

to anticipate consumer response in the wake of the

publicity surrounding COX-2 drugs.

Although COX-2 drugs were originally

intended for use by those patients who had GI side

effects with traditional NSAIDs, a much broader

281

population actually took the medications. Given

recent events, some patients taking COX-2 drugs for

arthritis for other pain will now likely turn back

to traditional over-the-counter NSAIDs for relief,

but consumers likely do not understand how to

safely use these OTC NSAIDs.

A 2003 survey of over 4,000 adults

commissioned by NCL on consumer use and attitudes

towards OTC pain relievers found that 47 percent of

those who take OTC NSAIDs take more than the

recommended dose. Nearly half would not consult a

doctor when taking for more than 10 days. Nearly

half thought it was more important to control pain

regardless of risk, and the survey revealed the

following about arthritis sufferers - 85 percent

take OTC for pain relief with 60 percent choosing

OTC NSAIDs, 30 percent take pain relievers on a

daily basis, and 70 percent do not discuss the

risks.

Based on these findings, we believe

consumers must be educated about the relative risks

and benefits of all medications, OTC or

282

prescription. We call upon the FDA to engage with

relevant partners in a broad-based educational

campaign that would cover relative risks and

benefits of various pain medications, appropriate

pain management strategies, the importance of

talking with a health care professional, and the

role\--.

DR. WOOD: Thank you. The next speaker is

No. 22. Amye Leong.

MS. LEONG: My name is Amy Leong. Before

I begin, I would like to say that while my funding

here was as a result of the Foundation for Better

Health Care, a nonprofit health education firm, I

have had a role as a motivational speaker in

previous years with several of the pharmaceutical

companies mentioned today. However, my presence

here today is as a concerned patient and a citizen.

As President and CEO of Healthy

Motivation, a consulting firm in health education,

and as spokesperson of the United Nation\'s endorsed

Bone and Joint Decade, I am very concerned about

the issues that you all are addressing today. I am

283

very pleased that you are addressing them, but I

think that we need to look at the benefit-risk that

you are all so diligently doing today.

I am that patient that you are addressing.

I have got rheumatoid arthritis, I have had it for

over 25 years. Within 8 years of diagnosis I ended

up in a wheelchair, unable to feed myself. As a

teenager, not being able to walk or feed herself,

it is one of those frightening scenarios that we

know should not ever happen.

Because of arthritis medications that did

not work in my years, I ended up going through 16

surgeries, 12 of those were joint replacements. I

have been hospitalized for over 312 days, and have

indeed taken over 35 arthritis medications

including every single nonsteroidal

anti-inflammatory and the celecoxibs.

So, I am here today to just tell you and

to share with you that while we look at risk, we

really do have to consider the benefit. I am a

standing benefit in front of you. It is my choice

to work with my physician to determine what is at

284

higher risk for me and what is not.

Every single arthritis medication I have

taken has come with some serious adverse effect -

abdominal pain, fluid retention, gastric ulcers,

upset stomach, nausea, vomiting, heartburn,

indigestion, ringing in the ears, reduction in

kidney function, increasing liver enzymes, rash,

weakness, unusual tiredness, sleeplessness,

sleepiness, respiratory infections, infections,

sepsis, and it goes on and on.

This is what I deal with.

DR. WOOD: Thank you.

No. 23. Donna Fox-Keidel.

MS. ZUCKERMAN: My name is Diane

Zuckerman. I am here on my own to read for Donna.

She was unable to attend because her son is a

juvenile RA patient, and he had a serious flare.

She writes:

\"I am 39 years old and have lived with

scleroderma and juvenile rheumatoid arthritis for

35 of those years. I began taking Celebrex in 2001

as part of my treatment plan. Prior to 2001, I had

285

been on almost every medication known to treat

juvenile arthritis. I had endured many corrective

and replacement surgeries. I have suffered

setbacks and side effects too many to mention.

When my doctor spoke of this new

medication called Celebrex, I was indeed skeptical,

what would the side effects of this new medication

bring to me, headaches, fatigue, and the dreaded

gastrointestinal problems I had learned to despise,

would it alter organ function, or, better yet,

would it really even work, because so many

medications I had experience had not shown any

benefit, and my drug cocktails were never less than

two medications and that is not counting the

injections I received.

With my skepticism aside, I tried the new

drug and within weeks saw a remarkable difference.

I was able to attend school full time versus part

time, I was able to manage my home better, and,

most importantly, I was able to be a mom I wanted

to be.

I was able to spend quality time with my

286

boys, maintain my home, and continue my work with a

volunteer group I started for children with

arthritis. My life was full for once and I was

able to enjoy every moment of it.

For once, taking medication didn\'t mean

chasing the pills with a bottle antacid. I could

eat without fear of feeling nauseated. My then

90-pound frame was able to gain 15 pounds. For a

brief period of time, I was taken off Celebrex due

to insurance issues. I was borderline depressed

because I was afraid my new-found life would

disappear. Fortunately, this did not happen

because my rheumatologist and I fought for my\--.\"

DR. WOOD: Thank you.

The next speaker, Erika Umberger, is she

here? No? All right.

Let\'s go to No. 25, Theresa Ray.

MS. SARAFIN: Hi. I am Judy Sarafin. I

am here on my own and speaking for Theresa, who was

unable to attend due to a last-minute emergency and

she asked me to read her story.

\"I am 35 with a history of osteoarthritis

287

starting in college. After the birth of my second

child, my arthritis worsened. Advil wasn\'t

working, my GP gave me Celebrex, which worked for

about four months. When that was no longer

sufficient, he sent me to Dr. Fleishman. Together,

we worked through Mobic and Bextra before settling

on Vioxx.

With the combination of Vioxx,

multivitamins, glucosamine, and avoidance of

caffeine, I became stable. For the first time in

about five years, I could honestly say that I had

periods of time where something didn\'t hurt. I

could always feel pain somewhere prior to this

point.

I reached stability with the Vioxx

combination in August of 2004. When the FDA pulled

Vioxx, I had no choice but to go back to the Bextra

at least temporarily. Once again, Bextra failed to

give me a sufficient quality of life. I hurt so

badly I could feel it in my toes.

We are now trying to find something that

will return me to my Vioxx quality of life. My

288

family has no history of heart disease or stroke,

my blood pressure is perfect, and my cholesterol is

ideal. I understand and do not wish to dispute

that Vioxx can cause some serious complications in

a certain portion of the population, however, what

about someone with my medical history?

I completely agree that all new

information, whether good or bad, should be

disseminated to patients and physicians, but I

believe the withdrawal of Vioxx was premature.

Each patient and physician should be allowed to

perform the risk-benefit assessment and further

studies should be performed to fully understand the

interaction before removing this drug from the

marketplace.\"

DR. WOOD: Thank you.

The next speaker is No. 26, Judith

Whitmire.

MS. WHITMIRE: Pfizer has paid my travel

expenses. I came from Reno, Nevada. I contacted

Pfizer, though, because I wanted to try to keep my

drug of choice, Celebrex, on the market, so that is

289

why I am here today.

When I was a young teenager, I helped my

grandfather in his home printing business. It was

difficult for him to set type since his hands were

even worse than mine are now. Certainly, I never

did think that my hands would resemble his one day.

Now I face a similar challenge. When I

retired at the end of 2002 from a 40-year career in

public health microbiology, which was a problem

with my hands, my husband introduced me to the

wonderful world of woodturning. It seems I have a

natural talent and my wooden bowls are in much

demand if I can only keep my osteoarthritis under

control, and this is what I do and love.

I will be 65 years old next week.

Subsequent to a severe whiplash when I was 16, I

developed osteoarthritis in my neck at the age of

30\. It was then that I embarked on the search for

an effective anti-inflammatory.

I started with Cliniril and have spent the

next 30 years trying all of the new drugs as they

became available. They either provided limited

290

relief or caused me gastritis, or both. I had a

three-day run on Naprosyn before my stomach said

no.

My new rheumatologist prescribed Celebrex

last fall for the osteoarthritis in my hands, neck,

and right knee. It gives me far better relief than

all of the other anti-inflammatories, and no

gastritis.

I do not have any risk factors for

cardiovascular disease. Interestingly enough, most

of my family has died of cancer. My rheumatologist

is comfortable with my low dose regime of 200 mg

per day. I urge you to keep this drug available

for the clinicians to judge if it is appropriate

for their patients like me.

Thank you.

DR. WOOD: Thank you.

The next is No. 27, Judy Fogel.

MS. FOGEL: My name is Judy Fogel. I

drove myself here from my home in Ithaca, New York,

to talk to you today. I found out about this

hearing from inputting in Google the word Celebrex,

291

a drug I have been taking with great success for

three years.

I feel like Celebrex was created for me.

My OA started when I was in my early 20s. It

started with pain and stiffness in my fingers. The

symptoms continued to worsen. In the early \'70s, a

rheumatologist had me take increasing doses of

aspirin, which led to gastric upset and ringing in

my ears. Since there was no other drug available,

I would sometimes take an aspirin and just pay the

consequences.

We raised three children and being a

soccer, football, and ice hockey mom, cold weather

environments was especially difficult. In the \'80s

and early \'90s, I tried about 10 of the NSAID

drugs. As each new one came on the market saying

it was better than the preceding one, I would take

one pill and have gastric upset, bruising, and

ringing in my ears.

Three years ago I went to my

rheumatologist with an inflamed right arm and hand.

He prescribed a new drug that would be easier on my

292

stomach, he said. It was called Celebrex. He gave

me samples and a prescription form.

After taking the samples with no adverse

aftereffects, I had the prescription filled and

have taken 200 mg of Celebrex each day ever since.

It took several months to have the pain

and swelling in my right hand and arm subside, so I

could use them again, and gradually, the morning

stiffness and pain in the rest of my body was

remarkably better.

Most days I feel better than I did 30

years ago. I downhill ski, play golf, shuffle cards

at bridge, sit through days of lectures and take

notes, dig and clip in my gardens. I have regained

the manual dexterity\--.

DR. WOOD: Thank you very much.

The next one is Dr. Preston Mason, No. 28.

DR. MASON: Thank you. I would also like

to acknowledge the contribution of my colleague,

Professor Corey, Nobel laureate in Chemistry.

Both the studies I will discuss were

conducted without interference from the

293

pharmaceutical industry. We both purchased the

drugs used in our studies. I have received

unrestricted grants from the manufacturers of these

drugs.

Dr. John Vane, also a Nobel laureate,

suggested as early as 2002 that differences in CV

risk observed among COX-2 inhibitors may be

attributed to their physico-chemical properties.

Confirmation of this hypothesis was

provided by Professor Corey. He reported that

rofecoxib readily formed potentially cardiotoxic

metabolites under physiologic conditions. One of

these metabolites would promote LDL oxidation, a

well-known contributor to inflammation. Such toxic

metabolites were not observed in the other agents

he tested.

The findings of Professor Corey

corroborate our own findings submitted before Vioxx

was removed from the market. We showed that this

drug dramatically damaged LDL and membrane lipids

through oxidative modification. We saw this at

pharmacologic levels.

In this figure, we also show an increase

in isoprostanes, a mediator of inflammation, and we

again report that this change in LDL oxidation was

294

not seen among other agents tested.

In the next slide, we contrast the

pro-oxidant effects of Vioxx against a potent

antioxidant. Remarkably, the combination only

partially attenuated the effects of the rofecoxib.

We also saw that rofecoxib reduced the

capacity of human plasma to defend against free

radicals. We have seen, and others have reported,

similar changes in patients with diabetes and a

recent MI.

The next slide is a further explanation

for the cardiotoxicity. We evaluated its molecular

effects on lipid structure. Vioxx indeed altered

lipid structure in a manner that we have seen

consistent with increasing rates of oxidative

damage.

We also saw adverse effects on lipid

structure and oxidative damage with etoricoxib,

another sulfone-type agent.

So, in summary, the last slide, we have

seen increased reactive oxygen species with

rofecoxib that contribute to mechanisms that lead

to cardiotoxicity.

Thank you.

DR. WOOD: Thank you.

295

Is No. 29, Dr. Ross, here? No. All

right. Let\'s move on to No. 30, Dr. Singh.

DR. SINGH: I am Gurkiepal Singh and I am

here on my own. This morning you heard data from

the collaborative study that David Graham and I

did. I am also the lead author of the Estimate of

NSAID GI Bleeds in the Country that Dr. Cryer

referred to, and as a handout, I provided you our

latest study on the hospitalizations because of

complicated gastric and duodenal ulcers in the

United States from 1988 to 2001 that I presented in

a plenary session last year.

In the next 30 seconds, reviewing it very,

very quickly, if you go on to page 3, the top slide

on the right side shows you what we found, that

there were a total of 493 million hospitalizations

296

in the U.S. and 3.6 billion patient years, and over

the years, there has been a decline in the amount

of gastric and duodenal ulcer complication

hospitalizations in the country with two periods of

remarkable decline, the first one \'94 to \'95,

perhaps coinciding with the introduction of H.

pylori guidelines by the NIH, and the second one in

1999, coinciding with, not necessarily caused by,

the introduction of COX-2 inhibitors.

The last slide also shows you the same

rate expressed for 100,000 NSAID prescriptions, and

you would see that the 1999 decline was of 22

percent. We do not know what causes it, but here

are the numbers.

One last point I would like to make on our

Medi-Cal study, is that we did look at the recent

exposures and current exposures and remote

exposures. I know that issue came up, and the

study was internally consistent and that the

current exposure was always the highest followed by

the recent exposure and then the remote exposure.

So, internally, we were consistent in defining that

297

exposure.

Thank you very much, ladies and gentlemen,

and I will be here to answer any questions that you

want.

DR. WOOD: Thank you very much.

The next speaker is No. 39, Dr. Allan

Fields.

DR. FIELDS: Good afternoon. My name is

Dr. Allan Fields. I have been a physician

practicing general and pelvic surgery and sports

medicine for over 30 years. Presently, I am also

the medical spokesperson for Swiss Medica, the

maker of 024, Essential Oil Pain Neutralizer.

This is a potent, safe, and effective

topical analgesic. It contains only natural

ingredients that have been clinically studied and

tested in the U.S. and around the world including

double-blind studies. It carries a U.S. process

patent.

As physicians, we have taken an oath to

provide the most effective care while not knowingly

harming the patient. To that end, I would like to

298

share some of my experiences with you.

I personally am asked on a daily basis

what can patients do or take to control pain for a

variety of medical conditions. I have been

advising my patients to minimize the use of oral

prescription OTC medications and instead to use the

024, which due to its purity, does no harm to the

human body.

We also recommend that 024 be applied with

massage therapies. This has provided pain relief

that has often lasted 6 to 8 hours. These results

have been very exciting. The patients have been

using less of the aforementioned drugs and saving

money in the process.

No serious adverse effects, such as GI

bleed, hypertension, or cardiovascular problems

have ever been reported. There is no interference

with other medications that are necessary to

maintain the patient\'s health because 024 is all

natural.

It contains no binders, preservatives, or

additives. Diet, exercise and work control are

299

also stressed, but in the future, we must strive to

enhance our body\'s natural responses to pain and

healing by safe and effective methods.

I am also a patient with diabetic

neuropathy. I use it on a twice daily basis. I

have had no pain since.

Thank you very much.

DR. WOOD: Thank you.

The next speaker is No. 32, Grant Johnson.

MR. JOHNSON: Thank you. I would like to

start off by saying there is a little bit of a

logistical mistake. The presentation packages will

be circulated at the end of the public

presentations.

My name is Grant Johnson. I am the

present Chief Operations Officer at Swiss Medica,

the manufacturer of 024. It\'s a topical pain relief

medication that competes against the NSAIDs and the

COX-2 inhibitor class of drugs.

We are all very aware of the huge

potential negative side effects when certain

high-risk patients take NSAIDs and COX-2 medicine

300

for any length of time. At Swiss Medica, we have

compiled scientific evidence that powerful topical

pain relievers, such as the 024, are as effective

as many oral medications, but without the side

effects, such as the bleeding ulcers, high blood

pressure, or increased risks to the heart.

These claims are supported by three

European medical studies, one American-based open

trial, and a recently completed Canadian

randomized, double-blind clinical study over an

extended period of time.

Every one of these studies demonstrates

that there was a 60 percent or greater quantifiable

reduction in pain for those who suffer from chronic

pain conditions.

The first study was conducted five years

ago, the latest was concluded last month. In your

presentation packet folders I have included the

appropriate summaries and the five pages of

professional endorsements, and you will also find

anecdotal feedback from pain sufferers who switched

to the 024 after failing to find relief from a wide

301

variety of pain medicine and magic solutions,

particularly the NSAIDs and COX-2 inhibitors.

Consumers need to be better advised by the

FDA, healthier eating choices, regular exercise.

These are things that have worked for centuries on

this planet. Does it make sense to allow

multibillion dollar companies to spend tens of

millions of dollars to persuade consumers to pop a

pill instead of making a healthy lifestyle

decision?

I propose the FDA consider a moratorium on

all direct-to-consumer advertising until these

drugs have been properly studied, and as of today,

no one has a straight and honest answer to the

question how many have really died from using these

pain pills.

Thank you.

DR. WOOD: Thank you.

The next speaker is No. 33, Necole Kelly.

MS. KELLY: Hi. I am here speaking for

the American Chronic Pain Association. We want to

make sure that everyone here understands that

302

chronic pain also destroys lives.

People who have chronic pain fight to get

their pain validated, to keep their jobs, to keep

their health insurance, to maintain their homes and

their families.

For 25 years, the ACPA has offered support

and taught pain management skills to people with

pain, to help them live more normal lives. Yet, in

spite of their best efforts, many of these people

still need medications including COX-2 inhibitors

that come with both benefits and risks.

Imagine learning that one of the tools you

need to live a normal life is not longer available.

In recent weeks, we have received hundreds of

letters and e-mails from people who have told us

they have stopped taking their medications because

they are afraid of heart attacks.

Others also have told us that they would

rather live 10 years with manageable pain than live

20 in agony. Some people are getting their

medications from Canada because they can\'t function

without it.

The ACPA is not a research facility. We

can\'t speak to the science behind these studies.

We can speak for people with pain. What these

303

people want and need is to share with their doctors

the medical decisions that affect their lives.

They need to know the risks of taking any

medications and weigh them against the benefits, to

make intelligent personal treatment decisions.

They need to retain the right to make these

decisions for themselves.

People with pain need the FDA to continue

helping the public to get the accurate

science-based information they need to make good

decisions, but we ask you to look beyond the

science and see the human face of pain.

Imagine just one person who woke up today,

as every day, with intractable pain, unable to

function, and ask yourself what is best for that

individual. We hope your decision will make a

positive difference for that person.

DR. WOOD: Thank you.

The next speaker is No. 34, Karen Kaiser.

304

Is she here? No.

All right. Then, let\'s go on to No. 35,

Robert Thibadeau.

DR. THIBADEAU: I am an experimental

research scientist in a nonmedical field with no

financial interests in the medical industry

whatsoever.

I have had rheumatoid arthritis and

ankylosing spondylitis since 1973, diagnosed by

blood tests in 1983. Vioxx saved my life. It acts

in an hour with no high or other perceptual side

effects. It is like aspirin for headaches, it just

makes the arthritis pain and stiffness go away.

I am here solely to reinforce the

probability of an experimental confounding and ask

for public analysis and full disclosure.

The confounding. You don\'t exercise for

25 years and now you have no pain and stiffness.

You run upstairs because you are amazed you can.

Risk of heart attack or stroke goes through the

roof, not for bad reasons, but for good reasons.

Control. Since these are brief,

305

unpredictable episodes, electronic monitor all

waking hours to see if patients show brief,

spontaneous increases in aerobic physical activity

over placebo controls. I have not seen this done

or even mentioned for control by any study

available to be read by the public.

I predict mentally incompetent people,

Alzheimer\'s, much more likely to show this exertion

side effect. People physically debilitated by

joint damage should show less effect due to

physically restricted mobility. Other predictions

are in my longer paper.

I ask the advisory group to review for

this confounding and ask the FDA to report the

findings and justifications out publicly.

Thank you.

DR. WOOD: Thank you.

The next speaker will be Lois Humphrey,

No. 53. No? Not here.

I beg your pardon, Glenn Eisen, No. 36,

was 52.

MR. EISEN: Close enough. I would like in

306

the interests of full disclosure to acknowledge

that I have done research and consulted with

Pfizer, AstraZeneca, and Given, and like Dr.

Qureshi, they are barely covering my expenses

today.

Next slide, please.

I would like to discuss the fact that

there has been accumulating data over the last

decade as far as gastrointestinal toxicity that has

gone beyond the ligament of trique (ph) to both the

small and large bowel.

This is an autopsy study from the New

England Journal approximately 10 years ago, which

showed a greater than 10-fold incidence of

nonspecific ulcers in an autopsy study.

Next slide.

A case-control study of hospitalized

patients who presented with upper and lower GI

bleeding found that patients within a week of

admission had equal use of NSAIDs whether it was an

upper GI bleed or a lower GI bleed, and this was

twice of the control population.

Next.

As a secondary analysis in the VIGOR

trial, you can see from these bars that there was

307

twice the risk of lower gastrointestinal bleeding

for naproxen as compared to rofecoxib.

Next slide.

In another analysis from the CLASS study,

showed that in an FDA-mandated outcome, having a

greater than 10 percent drop or a drop in

hemoglobin of greater than 2 grams per deciliter,

there was double the risk of dropping the blood

count in both diclofenac and ibuprofen as compared

to celecoxib.

If we remove patients who have had overt

bleeding, the trend continues.

Next slide.

So, because of this, we developed a study

to show proof of principle for small bowel damage,

and the combination of a nonspecific NSAID with a

proton pump inhibitor should be associated with a

rate of small bowel mucosal break that is

significantly higher than the rate for placebo or

308

COX-2 selective agent.

Next slide, please.

We have already shown this.

Next slide. Dr. Qureshi showed some nice

pictures.

Next slide.

This was a double-blind, randomized trial

where healthy volunteers had a two-week run-in

period, were randomized after a baseline capsule,

which was normal, and then were given 1 of 3

treatment arms.

Next slide.

The primary endpoint was the mean number

of small bowel mucosal breaks, and as you can see,

naproxen with a PPI had 10 times the number of

mucosal breaks as compared to celecoxib.

Next slide.

The secondary endpoint showed that there

was 55 percent incidence of small bowel mucosal

breaks for combination therapy as compared to 16

percent for celecoxib.

Next slide.

So, in conclusion, as in the upper GI

tract, inhibition of COX-1 by naproxen, and not

celecoxib, translated into significantly different

309

rates of mucosal injury in the small bowel, and

these findings extend the original COX-1-sparing

hypothesis beyond the upper GI tract and into the

small bowel.

Next slide.

You can read it because I am out of time.

Thank you.

DR. WOOD: Thanks.

The next speaker is Susan Winckler. Is

she here? Yes, No. 37.

MS. WINCKLER: I am here representing the

American Pharmacist Association, and we did not

receive funding to participate in today\'s meeting.

The views I am presenting are solely those of the

Association and its membership.

We are here because the safety profile of

COX-2 selective NSAIDs has recently come into

question. Some have suggested that these drugs are

too risky to be marketed, but a consideration often

310

lost in comments and debates, such as this, is the

reality that no drug has zero risk.

Every medication has benefits and risks,

and those risks increase exponentially when the

products are used inappropriately.

Unfortunately, patients have lost access

to several medications because the health care

system failed to appropriately manage risk.

Patients should not lose access to these products

because of the health care system\'s failure to

reduce risk.

If the agency determines that the

benefit-risk profile is insufficient for these

products to remain on the market, that assessment

must consider the responsibility of health care

professionals and patients in making medications

work.

By collaborating, pharmacists, physicians,

and patients can mitigate some level of risk if we

focus on identifying potential risks and

determining systematically how best to manage those

risks.

There are a few things that can help us

with that risk management. First, is to increase

the reporting of adverse events by pharmacists and

311

other health care professionals and to continue to

encourage that reporting.

Providing pharmacists with complete

information about the patients would also improve

our ability to manage potential risks.

When products are identified as having a

risk or requiring more attention, access to a more

complete medical history would allow pharmacists to

help assure that at-risk patients do not take

medications that could exacerbate such a condition.

If the agency determines that there is a

need for special oversight of COX-2 inhibitors or

other NSAIDs, we urge the FDA and product sponsors

to involve pharmacists in both the development and

implementation of any risk management program.

Please avoid the misperception that only

these products present a risk to patients when, in

reality, every medication has benefits and risks.

Thank you.

DR. WOOD: Thank you.

The next speaker is No. 38, Virginia Ladd.

MS. LADD: My association is paying for my

travel.

Good afternoon. My name is Virginia Ladd.

I am President of the American Autoimmune Related

312

Diseases Association. We are a nonprofit health

organization representing patients living with

autoimmune diseases, which include rheumatoid

arthritis, lupus, scleroderma, and over 80 other

disorders sharing similar complications as the

result of the body\'s attack on itself.

Autoimmune disorders are serious chronic

and disabling conditions that often present with

constitutional symptoms of joint and muscle pain,

widespread inflammation, and fatigue.

We ask that the agency and its advisory

committee respectfully consider the critical role

of patient and physician dialogue in conducting

risk-benefit analysis of any therapy at the level

where it belongs - with the individual patient

rather than a diverse clinical population as a

313

whole.

We believe that patients should have

access to as broad an array of essentially safe and

effective therapies as possible, with informed

labeling, providing the means by which the provider

and the patient can consider treatment options.

For many patients, the remote and even

more common risk of a serious acute adverse event

is, and would be, overweighed by the benefit of

maintaining or regaining freedom from pain,

mobility, and independence.

Since there has not been a new drug

approved specifically for the use of most

autoimmune disorders in the last 40 years, it is

necessary that clinical reliance on off-label use

of existing anti-inflammatories and

immune-modulating drugs.

In particular, the COX-2 inhibitors have

contributed to the improved life quality of many

autoimmune patients to which I have personally

spoken. Without COX-2 inhibitors, many autoimmune

patients with sensitivities to other NSAIDs would

314

be relegated to the use of low-dose corticosteroids

with therapy for the treatment of their

debilitating symptoms, and as you are aware, such

therapies carry\--.

DR. WOOD: Thank you very much.

The next speaker is No. 39, Paola

Patrignani.

MS. PATRIGNANI: I am Paola Patrignani,

University of (inaudible) Italy. I am Professor of

Pharmacology. I am in the field for 20 years.

This slide compares the therapeutic plasma

concentrations of cyclooxygenase inhibitors,

reported in pink, with the concentrations of the

different drugs inhibiting by 80 percent the

activity of platelet COX-1, a biomarker of

gastrointestinal toxicity, shown in panel A, and

monocyte COX-2, a biomarker of efficacy, shown in

panel B, as determined in the whole blood assay

that I developed. This is in vitro, reported in

blue.

It should be pointed out that 80 percent

inhibition of COX-2 is associated with clinical

315

efficacy.

Ibuprofen and naproxen therapeutic

concentrations are proper to inhibit more than 80

percent platelet COX-1 and monocyte COX-2. Thus,

these two drugs have similar pharmacodynamic traits

and they should be placed in the same box.

Differently, therapeutic concentrations of

COX-2 inhibitors are from 4 to 200-fold lower than

those inhibiting platelet COX-1 by 80 percent, thus

demonstrating a variable impact on COX-1 depending

on the dose and selectivity.

The impact of COX-2 inhibitors on monocyte

COX-2 is shown in panel B.

The therapeutic plasma concentrations of

nemesulide, rofecoxib and etoricoxib are proper to

inhibit more than 80 percent COX-2.

Diclofenac and lumiracoxib plasma

concentrations are several fold higher than those

inhibiting by 80 percent COX-2 while celecoxib and

valdecoxib plasma concentrations are 2- to 4-fold

lower.

In summary, ibuprofen and naproxen have

316

similar pharmacodynamic features towards COX

isoforms, so they have to be in the same class.

Diclofenac and celecoxib have

superimposable pharmacodynamic traits, but they are

given at not comparable doses.

Lumiracoxib 440 mg is an overshooting

dose.

Next slide, please.

This slide is very interesting because I

compared, I gave different drugs, lumiracoxib,

rofecoxib, celecoxib, ibuprofen, naproxen to

healthy subjects or patients, and I compared the

inhibitory effect on COX-1 and COX-2 and the

synthesis of prostacyclin.

The most interesting part of the slide is

that all the other coxibs gave a similar inhibitory

effect of prostacyclin. Also, the other

important\--.

DR. WOOD: Thank you very much.

The next speaker will be No. 40, Betsy

Chaney.

MS. CHANEY: Good afternoon. I am Betsy

317

Chaney. I am a Celebrex user. I took Vioxx

before.

I am here to say would you all pick up

your elbow and whack your funny bone and feel that

pain that stops you in your tracks from doing what

you are doing. All you want to do is say a bad

word.

Well, I have cracked vertebras in my neck,

and without Celebrex, I start to lose the feeling

in my hand, and I can\'t grasp a paper, I can\'t hold

onto something, I can\'t do things around my house.

I am concerned that you all will take my

ability away to make a decision with my physician,

my family, and my friends, to make an advised

decision to take COX-2 inhibitors.

There is a lot of people here for profit,

for many things, whether it be the drug companies

or the lawyers, or whoever, but my issue is please

don\'t take this medication that works so well for

me.

I can\'t take other medication because I am

taking two Nexium and a Xantac today. That is

318

maxed out on the stomach medication. They looked

inside and said it looks like Barrett\'s esophagus.

I have GERD and you all know I have NSAID, NSAID,

NSAID. I could name 100 of them, but those names

don\'t matter.

What matters is that I retain the right to

make a decision, with my doctors and my family, to

continue taking this medication even if there are

risks.

I am willing for my quality of life to

take those risks, and I thank you all very much for

watching over us.

Thank you.

DR. WOOD: Thank you very much.

The next speaker is No. 41, David

Peterson. Is he here? No.

Then, the let\'s go on to No. 42, Jack

Klippel.

DR. KLIPPEL: Thank you, Mr. Chairman.

The Arthritis Foundation represents and is

the voice of millions of Americans with arthritis.

Our constituency is keenly interested and is a

319

major stakeholder in the discussions being held

today.

They seek clear answers from us, you,

their doctors, industry leaders, and regulatory

authorities about the role of COX-2 inhibitors and

other NSAIDs in the treatment of their arthritis.

The Arthritis Foundation believes there

are two main factors that must be considered in

these discussions of these drugs and similar

discussions about other medications in the future.

First, there must be a more balanced

discussion about the benefits, as well as the risks

for these medications. Recent attention of COX-2

inhibitors and NSAIDs have focused almost

exclusively on one particular risk, cardiovascular

disease, with little mention of other risks

associated with these drugs, or more importantly,

the benefits of this class of drugs.

Numerous studies have documented that

COX-2 inhibitors and other NSAIDs relieve pain and

inflammation which has benefited millions of people

with arthritis. Many have found COX-2 inhibitors

320

to provide greater pain relief than other

medications. For some, COX-2 inhibitors have

controlled pain when nothing else has worked.

They would ask you the question, whether

their public health was made better or worse by the

decision to withdraw Vioxx. Their greatest concern

and risk is not about side effects of drugs, but

that they live with arthritis.

Second, is the central role of informed

patient choice in allowing patients with arthritis

to make their own decisions about treatment. We

believe that patients should be able to choose for

themselves whether or not the benefits of a

particular medication or treatment outweigh the

risks.

Full disclosure of these benefits, side

effects, and risks, and discussion with the

patient\'s doctor\--

DR. WOOD: Thank you.

The next speaker is labeled as No. 43.

Kathy Pinkert. Is she here? No.

Then, No. 44, Carol Spitz.

MS. SPITZ: Hi. My name is Carol Spitz

and my travel expenses have been paid for.

I have severe osteoarthritis. I have had

321

a knee replacement, shoulder replacement, and three

back surgeries.

Bextra has allowed me to be able to

function, some of the normal things that people

take for granted like walking and dressing. I

couldn\'t even do that before.

I am unable to take Motrin and Naprosyn

and aspirin due to anaphylactic reactions. Other

NSAIDs have given me adverse reaction of my

stomach, and that\'s it.

Thank you.

DR. WOOD: Thank you.

The next speaker is No. 45, Eileen

Lacijan.

MS. LACIJAN: Good afternoon. My name is

Eileen Lacijan. I am grateful for the opportunity

to be here today to speak to you about my

experience with COX-2 inhibitors.

I would like to advise the committee that

322

I do not have any financial relationship with the

sponsor, product, or competitors. I am here today

representing myself on the advice of my

cardiologist.

I am 57 years old and reside in Arnold,

Maryland. I am a registered nurse and the

Executive Director of a Hospice Program in

Maryland.

I have osteoarthritis of the basal thumb

joints of my hands. I was first prescribed Vioxx

in March of 2000. My rheumatologist changed my

prescription to Celebrex in June of the same year.

I then took Celebrex for the next four years until

July of 2004. Following a flare-up, the Celebrex

was no longer effective and I was prescribed Bextra

in July of 2004.

I have never smoked. I don\'t drink

alcohol. I don\'t have diabetes or any family

history of heart disease. I have never had high

blood pressure. I exercise regularly. I am not

overweight, and I have always maintained a health

diet.

On the evening of August 12, 2004, I

survived a myocardial infarction. A cardiac

catheterization, which was performed the following

323

day at GW Hospital, revealed no blockages. My

heart attack was thought to be caused by a coronary

vasospasm, which affected the left anterior

descending coronary artery and initially resulted

in a moderately large amount of heart damage.

I received excellent cardiac care and was

able to return to work full time a month after my

heart attack. I continue to work out at cardiac

rehab several mornings a week before work. I thank

God every day that I am alive and have the love and

support of my family and friends. However, I still

have many unanswered questions about the cause of

my heart attack as does my cardiologist.

DR. WOOD: Thank you very much.

The next speaker is No. 46, Gloria

Barthelnes.

MS. BARTHELNES: I am Gloria Barthelnes

and I am from South Grafton, Massachusetts.

When I was in my 30s, I was having

324

problems with my legs and my neck, didn\'t figure

what it was. I figured it would go away. Finally,

in 1984, I was living on a second floor apartment

and I was carrying my grandson who was 10 months

old up the stairs, got halfway up the stairs and

couldn\'t finish, I had to sit down the pain was so

bad.

I had contacted the doctor and had me go

through several tests. Finally, he recommended a

rheumatologist. They tried several medications on

me, it didn\'t work. Then, finally, he had given me

Vioxx. It was such a relief that I was able to go

to work without any pain, without any problems.

To go to work, I had to travel like 37

miles one way, and sometimes there was a lot of

traffic, and just to sit in the traffic was the

hardest thing to do.

I have the arthritis in my neck, lower

back, and in my legs. When they took the Vioxx

away, I panicked and I tried using just the

over-the-counter medication. It didn\'t work. So,

finally, I had called the rheumatologist and I

325

said, \"Can you help me?\"

So, he put me on Bextra. I am hoping that

you people can help me, and not take these

medications away.

Thank you for your time.

DR. WOOD: Thank you very much.

The next scheduled speaker is No. 47,

Rebecca Dachman. Is she here?

DR. DACHMAN: Hello. My name is Dr.

Rebecca Dachman. I am an occupational medical

physician, and I also have significant experience

in clinical trial design.

There were a number of thoughts that came

to my mind as I read in the papers about what was

going on with the COX-2 inhibitors. One of them,

as an occupational medicine physician, there are

many people who only respond to COX-2 inhibitors,

and that makes a difference between working and not

working for them, which has significant effects

both on disability and ultimately on their health,

because nonworking, sedentary people are a setup

for cardiovascular disease, as well.

As a clinical trialist, looking at the

data, I know I was surprised that I didn\'t get more

subgroup analysis of those who ended up having the

326

cardiovascular events, whether there were more

diabetics in that group or whether there were any

other ancillary factors that one could tell that

would identify them, and I think that is important.

I also think that vis-a-vis drugs, we have

to put it all in context, all drugs do have ADRs.

Birth control pills are as extensively used as

nonsteroidals and anti-arthritic drugs, and they

all do cause increase in thrombotic events, yet, we

haven\'t taken them off the market either.

I think we have to remind ourselves of

that and what it means is not that they won\'t have

events, but knowing about them and knowing how to

subgroup the people in who those events occur.

I think from the FDA stance, they have to

develop registries post licensure, so that for the

first two years, you get all the adverse events

that occur, and that is what is being done in

Britain.

DR. WOOD: Thank you very much.

The next speaker is No. 48, Barrett

Collins. Not here.

No. 49, Cynthia Lee. Not here.

No. 50, Robert Humphrey.

No. 51, Michael Paranzino.

327

MR. PARANZINO: I am Mike Paranzino. I am

here on behalf of Psoriasis Cure Now, a patient

advocacy group. We have no financial conflict. We

receive no pharmaceutical industry funding or

funding from their trial lawyer opponents.

I am here to represent the 6 1/2 million

Americans with psoriasis, more than a million of

those who have psoriatic arthritis, and many of

those psoriatic arthritis patients take NSAIDs

and/or the COX-2s.

Our written statement is on the FDA

website. It is available at psoriasiscurenow.org,

and there are some copies in the press room. Our

central point there was that absent a scientific

consensus against these drugs, that they continue

to be available so that patients can decide, with

328

their physicians, if in their own particular set of

circumstances, the benefits outweigh the possible

risks.

But in the remaining time, I want to make

a different point and I am amazed that in the last

50 people no one has made, and that is, that in

some of the rhetoric surrounding some of the

critics of FDA, some of the critics of the

pharmaceutical industry, we are hearing even some

buzz in Congress, that somehow the drug approval

process is broken, and we think that is false.

Patients need expeditious approval of

medications, and there are many still in clinical

trials that need to get approved, and we are

concerned that the FDA may become timid or gun-shy

and flinch about approving those drugs that are

coming down the pipeline that millions of Americans

with disease desperately need.

Where it does appear\--and I am just a lay

guy, I am lay person, liberal arts guy\--but where

it does appear we need work is in postmarketing

monitoring, post-FDA approval, that is where we

329

need long-term monitoring.

We can\'t wait 20 years to get long-term

studies before drugs are approved, but when that

data does become available, it does appear that the

ball is being dropped on a lot of sides in adding

that information to the mix.

So, please, keep approving the drugs. We

need new treatment options, and I thank you.

DR. WOOD: Thank you.

The next speaker is Dr. Lawrence Goldkind.

DR. GOLDKIND: I would ask that I go over

20 or 30 seconds, I could use some of the time that

some others didn\'t use.

DR. WOOD: No, you get two minutes. Good

try.

DR. GOLDKIND: That\'s the Chair\'s

prerogative, I understand.

DR. WOOD: Good try.

DR. GOLDKIND: From 2001 to 2003, I was

the Deputy Division Director of the

Anti-Inflammatory and Analgesic Drug Products

Section at the FDA.

Over the past decade, there has been an

evolution of what is considered feasible in the

realm of clinical trials. Drugs, such as the

330

statins, beta blockers, ACE inhibitors have been

developed to reduce mortality from cardiovascular

disease. Demonstration of these benefits requires

large and multi-year study.

Risk-benefit analyses are not so hard when

there is superiority in an outcome of death, and

placebo control, which is really add-on to standard

care, is ethical and feasible.

What is unique about the COX-2 story is

that the indication is pain relief, chronic in the

case of arthritis, but the perceived value was a

safety advantage compared to NSAIDs, which were

known to have substantial risks that were reflected

in the labeling.

In fact, everybody here knows that NSAIDs

have been the poster child for problem drugs for

over a decade. So, it seemed obvious that large

outcome studies would adequately test the

hypothesis of superiority of safety.

The concept of a large simple trial sounds

simple, but, in fact, is not. We are now learning

the limits of outcome studies. At the time that

VIGOR and CLASS were done, they were the longest

and largest trials by an order of magnitude of

NSAIDs.

331

We can now say they were imperfect and

lessons can be learned. One, therapeutic,

super-therapeutic doses are not the best choice.

They promote off-label usage, and you cannot

extrapolate well back to the therapeutic dose

levels.

Single comparator trials, when there are

many standards of care available, likewise is hard

to interpret and put into a context of therapies.

Allowing the duration and size to be

driven by a single prespecified safety endpoint

does not provide robust evidence necessarily of

overall superiority, and yet it is impossible to

power a study for unexpected or as yet

uncharacterized safety problems.

Even today, the term \"cardiovascular

332

outcome study\" is bantered about as if it were

cookbook simple. Well-known cardiologists have

stated that the obvious population for study is the

high risk patient\--

DR. WOOD: Thank you very much.

The next speaker is Louis Humphrey, No.

53\. Is she here? No.

Then, we will go through the ones that

didn\'t respond to our call earlier.

Rakesh Wahi, No. 2. Erika Umberger, No.

24\. Gilbert Ross, No. 29. David Peterson, No. 41.

Barrett Collins, No. 48. Cynthia Lee, No. 49.

Robert Humphrey, No. 50. Lois Humphrey, No. 53.

In the absence of them, we will take

somebody off the wait list, who is Yvonne Shira.

Is she here? Yes.

DR. SHIRA: Hi. My name is Yvonne Shira.

I am a practicing rheumatologist, and while I have

worked with all of the companies mentioned here,

and many others, doing clinical trials and as a

consultant, I am here today representing myself. I

paid for this trip myself.

I am representing my patients and I hope

most of the rheumatologists who are seeing patients

day by day.

333

I ask the committee to consider that

quality of life issues are as important as length

of issues to many of our patients. When Vioxx was

removed from the market, a number of my patients

refused to discontinue the drug despite its risk,

because they deemed the quality of life benefit to

be greater than the risk.

One patient said to me regarding its

removal, \"Dr. Shira, they just don\'t understand how

much we suffer.\"

So, I ask that you do not take away

choices unless there is compelling evidence that

the coxibs are substantially less safe than the

available alternative NSAIDs.

The data you have presented so far does

not suggest this, but that rather the traditional

NSAIDs have not been sufficiently scrutinized in

long-term trials.

Remember that real life data is more

334

consequential than theories no matter how good they

sound. Rheumatologists have always been aware of

the cardiovascular effects of all NSAIDs. That is

why most of us monitor patients at high risk by

having them come back within a week or so for blood

pressure monitoring.

The problem has been that we have accepted

blood pressure increases that we thought were

insufficient, that in light of new cardiovascular

information, may actually have hit long-term

consequences.

It is likely, I believe, that all NSAIDs

have cardiovascular risk, but they have not all

been studied equally.

Please don\'t away our patients\' choices

without compelling evidence that the alternatives

are truly safer.

Thank you.

DR. WOOD: Thanks very much. That was the

last speaker in the public hearing. I am grateful

to all of you for sharing your views with us. I am

sure they will be helpful to the committee.

We are going to go straight back to the

program, and Dr. Villalba.

MS. MALONE: Excuse me, Dr. Wood.

335

DR. WOOD: Sure, yes.

MS. MALONE: I am Leona Malone. I am the

patient representative on the program. I just

wanted to tell the people who did give testimony

that\--and this is not facetious at all\--that I

literally do feel your pain, and I think that

everyone here is here because we are aware of the

pain and the situation that you are in, and no one

here is taking it lightly.

I know how much trouble especially for the

patients it was to get here, to sit here, to

listen, and to get up to speak, and I applaud you

for that. I just want you to be assured and to be

confident that all of us here will take it

seriously and give a voice to everything that you

have said.

Thank you.

DR. WOOD: Thank you, Leona. That was

helpful.

Are we ready, Dr. Villalba?

DR. VILLALBA: I am ready.

DR. WOOD: Okay, let\'s go.

Lumiracoxib

FDA Presentation

Lourdes Villalba, M.D.

336

DR. VILLALBA: I am going to talk about

the cardiovascular safety of lumiracoxib. I want

to make some points before I am going to show the

data, and this is that my talk is restricted to

cardiovascular safety.

I will start again. I am going to talk

about cardiovascular safety only in TARGET. So,

this is a very focused presentation, and I am not

going to discuss any other aspects of safety, such

as hepatotoxicity, I am not going to discuss

efficacy, so I would urge you not to jump into

conclusions regarding the risk-benefits of

lumiracoxib without having all the data on hand.

I am going to TARGET. I hope you remember

everything that was presented before lunch, because

I don\'t want to repeat everything. We know TARGET

337

was a large study, 52 weeks, 18,000 patients with

osteoarthritis, that had two sub-studies, one

comparing lumiracoxib and naproxen, the other,

lumiracoxib and ibuprofen.

About 25 percent of patients were on

low-dose aspirin, and they were two identically

designed studies although there was a little less

exposure in the second study, in the lumiracoxib

and ibuprofen study, and there was some imbalance,

slight imbalance in the cardiovascular risk factors

between these two studies.

I want to point out that the dose of

lumiracoxib that was used was 400 mg daily and that

this dose has been mentioned before, that it is 4

times the recommended dose, however, that the

effectiveness of this dose has not been

demonstrated to the FDA\'s satisfaction yet.

So, we don\'t know exactly what this dose

means. Initially, it was thought to be twice the

recommended dose, now the sponsor is pursuing the

100 mg dose. So, again, this is hard to draw

conclusion from this dose into what is going to be

338

in the final dose.

Regarding the cardiovascular safety, I

want to point out that the primary endpoint here

was confirmed and probable APTC endpoint. For

example, Merck used only confirmed events. So, you

cannot really cross-compare the numbers here to the

other trials at Merck.

So, it includes cardiovascular and unknown

cause of death, myocardial infarction, clinical or

silent, and stroke, hemorrhagic or ischemic.

Again, this specifically includes silent myocardial

infarction, which was not particularly specified in

the Merck definition. And then there were other

variables, they were looking at everything.

So, here we have the same disposition of

the slides that I showed yesterday. Here, you have

the name of the study, the drugs used lumiracoxib,

naproxen, ibuprofen, the number of patients

randomized in this row. Before, I didn\'t have it

up here, but now I have the patient years of

exposure. As you see, there is a little less

exposure of this study, but not that different.

Here we go to the APTC events. We have 40

events with lumiracoxib and 27 on naproxen as

compared to 19 on lumiracoxib and 23 on ibuprofen.

339

So, the first thing that I think stands out is that

there is a different number in the total number of

events, and particularly the number of events on

lumiracoxib is half in the study 2332 than in study

0117\.

If you go through the different rows, the

difference is driven by the non-fatal MI here in

the lumiracoxib as compared to naproxen. This

number, as I mentioned, includes silent MI.

Here, we have in this column the number of

events and the rate expressed in 100 years of

exposure, 100 patient years of exposure. This is a

different way of presenting the data than the

sponsor presented.

Here, in this column, we have the relative

risk, which is the overall risk of lumiracoxib

versus naproxen, and I did not include the

confidence intervals here basically because it

would make the slide so busy, but also there were

340

not statistically significant difference in any way

you looked here.

So, again, if you look at the relative

risk here of all the events to be increased. For

lumiracoxib, it is increased, lumiracoxib compared

to naproxen particularly driven by the number of

non-fatal myocardial infarctions.

This is the Kaplan-Meier plot with the

time to events information, with the percentage of

patients with events, and here time and date. As

you see, there is a separation between lumiracoxib

and naproxen, that it starts early, before day 50,

and seems to have a constant overall risk here.

However, if you remember, for example, in

VIGOR we have the separation after a month, but if

you think about APPROVe, the separation wasn\'t

until after 18 months. So, this is only a year, so

we didn\'t get into what we saw with APPROVe yet

here.

These are the numbers for 2332, the number

of confirmed and probable APTC events, and here you

see that the numbers look pretty much the same.

341

The relative risks are all around 1 or below 1 for

all categories.

Here, we have the Kaplan-Meier plot and

they look pretty close here. This is lumiracoxib

in red and this is ibuprofen.

Now, if we put the two lines together, we

see that lumiracoxib in study 0117 was up here, and

lumiracoxib in study 2332 was down here with

ibuprofen and naproxen in the middle.

So, I think that is very difficult to

interpret anything from this study, because

lumiracoxib look like two different products in two

sub-studies within the same study.

This slide shows the difference in the

number of events by aspirin use. I am not going to

give the relative rates, et cetera, but it is just

to show you the numbers, how if you look in the

lumiracoxib/naproxen sub-study, again, the number

we said was driven by the number of non-fatal MIs,

the non-fatal MIs among the non-aspirin users,

because if you look at the number of aspirin users,

the number is the same, 6 and 6.

This has to do with the size, because only

25 percent of the patients were on low-dose

aspirin, so this may have something to do with

342

power, but again I think it is unclear what the

role of aspirin is here, may be protecting, that is

possible, but what I am concerned about is that the

use of aspirin, if you have a substantial number of

patients on aspirin in a trial that is evaluating

cardiovascular safety, actually, that may blur a

little bit the results.

Here, in 2332, we see that in the

non-aspirin users, there is no difference, and if

you look at the aspirin users, actually, there is a

trend that goes, that the situation was on

ibuprofen users who also use aspirin, and this

trend is consistent with that hypothesis that

actually ibuprofen depleted the anti-platelet

effects of aspirin.

This is just to show the number of

non-fatal myocardial infarctions in the first

study, the lumiracoxib/naproxen. Here, we have all

patients. The number was 18 versus 10. In the

343

non-aspirin population 10 versus 4, in the low-dose

aspirin population 8 versus 6, and here you have

the relative risks.

This is taken from the paper in the Lancet

by Farkouh, et al.

Again, we see a signal here of lumiracoxib

and naproxen, but this signal seems to start

earlier than what we have seen before.

So, in conclusion, we cannot draw

definitive conclusions regarding the COX-2

selective class effect. If anything, I think that

this is consistent with what we have been

discussing during the last two days, and that this

seems to be a class effect.

We don\'t know that selectivity is a

continuous variable, so different NSAIDs have

different degrees of selectivity, and they are

associated with different cardiovascular risks, and

the same with the different so-called coxibs, but I

never like that name, because to me they always

were NSAIDs.

But anyway, I think that this adds some

344

information to the puzzle that we need to put

together and decide what to do with this class of

agents. I know that this was only one year. Now,

we are expecting to see longer studies than one

year now, this is up to a year, which at that time

seemed to be a long time, but now that we look at

it, we think, okay, we would like to see what

happened in the next two years.

These included patients, some of the

patients had increased cardiovascular risk as they

were using low-dose aspirin, however, this was a

study only in patients with osteoarthritis, it did

not include patients with rheumatoid arthritis, and

we know that rheumatoid arthritis is associated

with higher cardiovascular risk than

osteoarthritis.

So, that may have something to do with the

findings, although we did see the findings really

in the naproxen sub-study.

Again, I am not clear as to the role of

aspirin here. Regarding blood pressure, for

rofecoxib I think that blood pressure is an

345

important factor. I am not saying it\'s the whole

explanation, but I think that is an important role.

However, here, I am not showing any data,

but if you remember the data presented by the

sponsor, ibuprofen affected blood pressure more

than what lumiracoxib did. Actually, ibuprofen

affected blood pressure more than what naproxen

did. It was like a 2.7 change in mean blood

pressure for ibuprofen. It was a 1.4 change in

mean blood pressure for naproxen.

So, here, we see the association. There

is not a big increase in blood pressure, but we are

still seeing the signal. Again, we didn\'t have

placebo here, so we don\'t know how these were

compared to placebo.

Another thing that I want to mention is

that lumiracoxib is structurally related to

diclofenac, and we don\'t know how diclofenac would

compare to lumiracoxib in this case.

This is it.

DR. WOOD: No back-up slides, good.

We are going to take a break and we are

346

going to be back here and start at five past 3:00,

and then we will start with the discussion of the

presentations of the two previous drugs, and then

we will go to the general questions after we have

dealt with that.

So, we will come back at five past 3:00

and start with the discussion of the Merck

presentation and go on to this one second.

(Recess.)

Committee Questions to the Speakers

DR. WOOD: We have three tasks that we

need to get through this afternoon, so pace

yourselves as you think about that, colleagues.

We have got to deal with the questions and

the issues that came up from the last two sets of

presentations. We need to have Dr. Furberg address

the Pfizer issues that he raised yesterday and give

Pfizer the chance to respond to that, and we will

come back to that in a second.

The third we need to do is start to

address the questions that the FDA prepared for us.

So, there are three tasks we need to get through.

347

It is just after five past 3:00, and we need to get

started on that.

Let\'s begin with the questions for the

speakers on etoricoxib.

Oh, Dr. Hennekens first.

DR. HENNEKENS: In the 1970s, I was in

Oxford with Richard Peto. I had the privilege to

help him put together the APT Collaboration. We

prespecified non-fatal MI, non-fatal stroke, and

all vascular deaths as the combined endpoint. We

specifically excluded silent MIs in the first cycle

in \'88 and the second with Rory Collins leading in

\'93, and the third with Colin Baigent, now called

the ATT.

So, Merck, in my view, has used the

correct APT now ATT definition. It is Novartis and

the FDA that are at variance with what the APT

definition.

I had a question for the FDA presenter.

One of the things Peto told me is if you torture

the data enough, they certainly will confess, but

with that as a background, the lumiracoxib

348

comparison versus ibuprofen is 0.76, against

naproxen it\'s 1.46, and the conclusion is that the

drug is behaving differently in the two studies.

Well, the alternative hypothesis based on

the evidence we have seen so far is that there may

be a protective effect of naproxen and perhaps some

harm of the shorter acting NSAIDs, a hypothesis

supported by the basic science showing some

deleterious actions of all the NSAIDs, but this

potential beneficial effect on platelets of the

longer acting NSAIDs.

So, I think it may not be necessarily true

that we need to conclude that this drug is behaving

differently in two studies with two very different

comparators.

DR. VILLALBA: My conclusion was that I

really don\'t know what to make of it, and that is

why I need the opinion of other people here.

The conclusion really was that this

probably a class effect, this is a very

heterogeneous class, and you have all the degrees

of selectivity there. So, that is what we need to

349

determine.

DR. WOOD: We have got Dr. Stephanie

Crawford.

DR. CRAWFORD: Thank you. I would like to

ask Dr. Sean Curtis to please come to the

microphone if you are in the room.

Dr. Curtis, this morning you stated that

in global markets, Merck is currently revising its

labeling for etoricoxib to address new safety

information relative to the safety of selective

COX-2 inhibitors, so I am intrigued. In what

manner, specifically, what is the sponsor stating

in its revised labeling worldwide on the safety of

this product?

DR. CURTIS: We participated in the

European referral. It has been basically a

referral process for all the COX-2 inhibitors, and

that is actually just wrapping up, as you know. I,

of course, have been here, but I am aware of now

that there has now been wording for the label that

talks\--and this is basically class labeling in

terms of contraindications\--but I think really what

350

it boils down to, you know, we have been informed

from the CHMP that there will now be a classwide

contraindication for all coxibs related to

congestive heart failure.

It was previously classed as 3 and 4, it

has been extended to Classes 2 through 4. In

addition, there will be contraindications in

patients with established ischemic heart disease

and/or cerebrovascular disease, so that will be

class contraindication, class labeling.

In addition, for Arcoxia or etoricoxib,

there will be contraindication in patients with

hypertension whose blood pressure has not been

adequately controlled.

So, that is obviously new information as

of today, and that is, in essence, what I mean by

working with the regulators, based on new and

evolving information, to come up with product

labeling that accurately and adequately reflects

current knowledge.

DR. WOOD: I think she was asking

you\--which I suspect is going to be the committee\'s

351

focus the rest of the afternoon for both the

sponsors, for the committee at least to decide what

the committee would need to see before they approve

new drugs like this\--I think what Dr. Crawford was

asking was what were the studies you were proposing

to do to do that. Is that right, Dr. Crawford?

DR. CURTIS: Could you restate the

question? I couldn\'t hear you.

DR. WOOD: I think the question was what

studies were you proposing to do, that you thought

would help get this drug approved in the future.

DR. CURTIS: As I reviewed through my

presentation, we feel the underlying safety

information that is most relevant to ensure that we

are all comfortable with the safe and effective use

of the drug, is to proceed with the studies that I

outlined this morning, namely, EDGE II and MEDAL,

which are, as I reviewed, opportunity to assess the

long-term safety of the compound in contrast to

traditional care, namely, diclofenac.

I reviewed the reasons why we chose

diclofenac. There is pluses and minuses of the

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comparators, but that is our primary method to

further assess the compound at this point in time.

DR. WOOD: Put on slide 31 again, would

you. That was the slide that showed the relative

potency on the COX-1 and COX-2.

Basically, I think Dr. FitzGerald said

earlier that he saw this as rofecoxib lite or

something. So, given that you presumably wouldn\'t

have expected to see a difference between your new

drug and rofecoxib, it seems like you picked the

next best thing to do as your comparator.

Naproxen is up there higher up, and you

picked the one that was closest to rofecoxib to

make your comparator, so the chances of seeing a

difference seemed to me extraordinarily small, and

I am not sure what that will teach us.

DR. CURTIS: Could we go to slide 1115,

please. The slide that I just showed as part of the

core presentation was the weighted mean average. I

did also want to point out that diclofenac here,

what is plotted here is again at steady state and a

percent inhibition from baseline again of a COX-1

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assay looking at platelet, thromboxane, B2.

This is a plot of inhibition both at peak

and at trough of the exposure in the blood. You

see diclofenac at trough has about 60 percent

inhibition of thromboxane, but at peak, achieves

levels that are close to 90 percent, so there is

some variability in the degree of thromboxane

inhibition throughout the dosing interval.

I went through the reasons why. I showed

some clinical data, too, that did suggest that at

least from a GI tract perspective, which, of

course, is ultimately one of the key safety

endpoints, that there is a way to differentiate

diclofenac from other NSAIDs\--excuse me\--from what

we consider COX-2 selective inhibitors.

I showed you data with valdecoxib and

rofecoxib. In thinking about other comparator

choices, there are limitations to the use of the

other NSAIDs that I reviewed, and I think

fundamentally one needs to keep in mind that

diclofenac at this point is, in essence, probably

the NSAID used most worldwide currently.

So, you know, in acknowledgment of the

limitations of choosing any single individual

comparator, and in acknowledging some of the

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limitations that were reviewed perhaps in the

TARGET study even, where if you do start to do

sub-studies, you do run the risk of showing

different estimates even with one comparator, even

with the same compound.

We felt that doing a large study of the

magnitude that I described for MEDAL against one

comparator, and I reviewed the reasons why we chose

diclofenac, was as reasonable a choice given all

the alternatives.

DR. WOOD: Garret, are you still here?

Maybe the question to him is supposing that study

turns out with no difference, are you going to hear

from him that he doesn\'t believe that tells you

anything because it is just another COX-2 selective

drug, is that what we are going to hear, Garret?

DR. FITZGERALD: I would take a slight

different tack. We have heard the words

\"continuous variables\" used quite a lot, and I

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think it is a continuum from as one extreme, very

selective, very long-lived drugs, going through

shorter lived, less selective drugs through to very

non-selective drugs.

I would guess that the ease of detection

and the size of signal would move across that

spectrum from being very large to being very small

or undetectable.

So, I won\'t reiterate the reasons why. I

think diclofenac resembles remarkably Celebrex with

respect to selectivity, and I would view this trial

as actually a very useful trial, beginning to

address for us information that we need to know. I

would cast it as a within COX-2 selective trial in

that respect.

It is like we have a surrogate for

Celebrex. We saw a lot of little trials with many

flaws in the blood pressure arena yesterday,

setting up Celebrex against rofecoxib with

arguments about timing of dosing, and so on.

Well, here the rubber meets the road. We

actually addressed the question of whether a

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commonly used, relatively selective drug,

diclofenac, stacks up in a way that segregates from

a longer lived, much more selective drug,

etoricoxib, so I think it does provide useful

information in that regard, although I might cast

the reasons for why I think it is useful in a

slightly different way.

DR. WOOD: Any other questions? Dr.

D\'Agostino.

DR. D\'AGOSTINO: This is both for Joel and

Sean.

You raised the question, Sean, about doing

a non-inferiority study, and I am wondering\--that

certainly will be a discussion that we will

have\--and I am wondering if you realized the

implications of that.

When you look at, for example, slide 44,

in your presentation, and you look at the EDGE

study, was the EDGE study a non-inferiority trial?

DR. CURTIS: I actually wanted to clarify

something that Dr. Schiffenbauer mentioned. So,

the answer is no. The non-inferiority criteria

357

that I identified in the presentation is based on

cardiovascular safety data accrued from three

studies: EDGE, EDGE II, and MEDAL. So, the

cardiovascular non-inferiority criteria is to be

applied to the minimum 635 confirmed thrombotic

events that will accrue from three studies.

DR. D\'AGOSTINO: From the three studies,

not one at a time.

DR. CURTIS: That\'s correct, but I am

providing you data that is coming available, and

EDGE had finished, and it is an important piece of

information.

DR. D\'AGOSTINO: That is comforting in

terms of what is possible, but just to point out

that on that result, that would not be very

positive for you if you did the 1.3. You would

actually, in that case, say that the comparator

could be better. I mean that would be a conclusion

in that study.

I don\'t want to go into the details of

that, but one has to be very careful when they go

the non-inferiority route, and we will talk about

358

that more. This slide frightened me a bit.

The other is if you do go the

non-inferiority route, what about the inclusion of

the aspirin individuals, it probably won\'t be a

constant hazard in the sub-groups, but what will

happen then with your non-inferiority. This was

raised by Joel, and I would like an answer. I

would love to hear what your answer is.

DR. CURTIS: Aspirin, of course, it is

hard to win with that, and I will tell you why. On

the one hand, you want to include patients with a

range of baseline risk, and certainly one criticism

of some of the studies is that patients with

cardiovascular risk have not been included in these

studies.

Both us and the FDA felt it was important,

as the data provided to included patients with

baseline cardiovascular risk, but, of course, those

patients should be on aspirin.

So, we, of course, allow patients to be on

aspirin as per clinical guidelines. As I

mentioned, we expect about 30 percent of the total

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patient cohort in the cardiovascular analysis will

be on aspirin.

But I want to be clear, the primary

analysis will be based on all patients whether they

are on aspirin or not.

DR. D\'AGOSTINO: But are you going to be

assuming in the 1.3 that the hazard ratio will be

the same within that sub-group, but just that it

will be a different level of absolute risk? We

will talk about those things, but those are serious

implications.

I would have to have a study design where

the very first thing you do is say, well, gee, I

couldn\'t do what I set out to do, I have to look at

subsets, namely, I have to get rid of the aspirin

users because they are confounding things.

Was that the concern that the FDA is

having?

DR. SCHIFFENBAUER: Yes, as I expressed,

in the non-inferiority design where we don\'t have

the placebo background, this would be a maneuver to

make the two groups look more similar. I mean if

360

you extrapolate it to 60 percent or 80 percent

aspirin use, I think the two groups would look

almost identical, so you would end up having to

look at subsets, that is true.

DR. WOOD: Dr. Abramson.

DR. ABRAMSON: Yes, I have a question for

Dr. Villalba

DR. WOOD: Can we just deal with the first

presentation first.

DR. ABRAMSON: I am sorry. Then, I will

wait.

DR. WOOD: Dr. Gibofsky.

DR. GIBOFSKY: Dr. Curtis, I have a

concern about the selective emphasis of data being

presented in seeming replicate trials. If we go to

slide 10, for example, and again in slide 46, you

commented that etoricoxib was superior to naproxen

in one of two pivotal studies, but similar in the

other study, and based on that one study, you have

used the term \"superiority\" at least twice in your

presentation.

I guess I am kind of wondering, if you did

361

a back of the envelope calculation, like Dr.

Fleming did yesterday afternoon when we were

discussing two polyp trials, one of which we gave

more focus to I think than the other, would you

still be able to make this claim of superiority

based on the meta-analysis with both trials?

DR. CURTIS: My point in highlighting the

efficacy data was, of course, not to talk about a

claim of superiority. The purpose was to provide

data that provides you and all of us an opportunity

to look at both the risks and the benefits of the

compounds, and the data in RA were compelling, and

I fully disclosed results from both studies.

Furthermore, the data, these really were

the first studies that we are aware of that showed

a statistically significant difference. So, my

point was again in the context of an overall

risk-benefit assessment, to claim\--to not claim,

but to show the data for this compound at the doses

that were studied provide a level of efficacy that

certainly should be part of the consideration.

I certainly would not be claiming any sort

362

of label claim or anything like that, because we

are not here to talk about such things.

DR. GIBOFSKY: I take your point, but

specifically, if you combine the second study with

the first, would you use the word \"superior\" to

naproxen, or would you use the word \"equivalent\" to

naproxen?

DR. CURTIS: I can only talk about a

clinical study within the context of that clinical

study where patients were randomized evenly between

treatment arms. I think it would be speculative to

talk about combining the results.

DR. WOOD: Dr. Shafer.

DR. SHAFER: If you can go to slide 19,

and we see here that once again the confidence

bounds around the three groups do not really

justify the breaking out of naproxen, it would

appear to me, as a separate group.

Now, go to slide 44. Once again you have

broken out naproxen as a separate group although it

is not clear that the confidence bounds would

support that either.

So, we have a pattern where you are

constantly seeing a worse outcome compared to

naproxen, and similar to rofecoxib, where the same

363

signal came up, you asked, I think, or you mean to

imply to us that naproxen is intrinsically

different, but we have heard multiple experts over

the course of the last day and a half tell us that

they don\'t believe that naproxen is intrinsically

different.

We have seen observational trials in which

there may be a modest effect of naproxen, but

certainly nothing of the magnitude to explain a

1.5, 1.7 risk relative to naproxen that you have

seen in your data, and even the sponsors

themselves, Roche and Bayer, in their

presentations, felt that naproxen did not have the

cardio-protective effects that you have attributed

to it.

So, first, I am disturbed that your

primary analysis isn\'t versus NSAID comparisons,

all NSAIDs, and then as a subgroup, you compare

naproxen out. Instead, you pull naproxen out and

364

ask us, I mean the implication almost is that we

should dismiss it, because it\'s naproxen, and then

look at everything else. It concerns me that we

aren\'t primarily looking at all NSAIDs as the

comparison group.

Secondly, at this point in time, do you

truly believe that naproxen and the postulated

cardio-protective benefits of naproxen truly

explain the difference that you are seeing, and

that we are not actually seeing a very solid signal

for intrinsic increased cardiovascular toxicity

with the COX-2 antagonists?

DR. WOOD: And while you are answering

that question, tell us why the right study wouldn\'t

be to do a naproxen with omeprazole versus your

drug. I mean you obviously believe naproxen beats

the drug, right? And the only advantage of the

drug over naproxen is a GI benefit.

Supposing omeprazole gave you the GI

benefit and you still had the cardiovascular

benefit, wouldn\'t that be the optimal therapy? And

why, given your data here, did you choose to go

365

with the drug that has less benefit than naproxen?

I still don\'t understand that.

DR. CURTIS: I am going to answer your

second question first. Naproxen clearly is a very

effective drug, however, as we heard repeatedly

today, patients have different responses to

therapies. Again, the reason people with arthritis

take drugs is so they can have some relief. Not

everybody responds to naproxen.

So, I think naproxen clearly is a very

logical choice for many patients, but there are

going to be patients who do not respond to

naproxen, and when you factor in GI risk, adding a

PPI certainly would appear to likely to mitigate

some of the risk, but you are still going to be

left with patients who don\'t respond to naproxen,

who still are going to have a residual GI risk, and

we have seen data that suggests even when you add a

coxib or a PPI to an NSAID, there is still room to

improve from a GI safety perspective.

So, I think that as a therapeutic option,

selective COX-2 inhibitors, including etoricoxib,

366

still have a role. As to why we chose not to use

naproxen as the comparator in our outcome study, I

reviewed the reasons. We have now seen qualitative

differences in cardiovascular outcomes against

naproxen with three different COX-2 selective

inhibitors: rofecoxib, etoricoxib, and

lumiracoxib.

We felt that doing an outcome study

against naproxen, we would likely replicate that

observation again. We felt it was important to

accrue additional data against another traditional

NSAID that was used widely around the world to get

a more firm estimate of what the cardiovascular

risk looked like against another NSAID.

DR. WOOD: You looked at that data. You

saw that naproxen beats your drug. So, you decided

to pick one that didn\'t look like it would\--because

it is as selective as your drug is\--and you are

going to come back with that data and say wow, it

doesn\'t produce any cardiovascular signal because

it\'s the same as diclofenac. That doesn\'t make any

sense.

DR. CURTIS: Again, I think it is

important to remember that the qualitative

differences that were observed against naproxen

367

were being seen at the same time that no

differences were being observed with non-naproxen

NSAIDs, and in a time frame like a year for which a

difference from placebo with COX-2 inhibitors has

not been appreciated.

So, I think all that data, to me,

continues to say that there is something different

about naproxen. I can\'t quantify that, I don\'t

think the data allow that, but there clearly

appears to be something different about comparisons

to naproxen to the other NSAIDs.

DR. WOOD: I understand that, but the

issue that has changed since hour initial studies

with naproxen is that we now have three randomized

trials against placebo in which placebo beat the

drug. So, using an active comparator that you have

chosen to match in terms of cardiovascular adverse

events, etoricoxib, isn\'t acceptable in terms of

showing that the drug doesn\'t have an effect on

368

cardiovascular mortality or morbidity.

It might have been acceptable in the days

when you believed that naproxen was beneficial and

that that was the total explanation, but by your

own admission, you don\'t believe that anymore.

DR. CURTIS: So, if I understand the

question, you are asking why we are not doing a

large outcome study against naproxen?

DR. WOOD: I guess I am asking you what

you are going to learn from the diclofenac study.

You are certainly not going to be able to say that

this drug does not produce cardiovascular problems

given that you have deliberately chosen a drug that

looks as similar to etoricoxib as you can get, and

from your earlier studies, namely, this one, you

have seen that it does produce a difference with

naproxen, and it doesn\'t appear to produce a

difference with this, and it has got a very similar

pharmacology.

So, if you can imagine an imputed placebo

arm here, and given what we know about placebo, you

would predict that this drug would do worse than

369

placebo, and you won\'t be able to exclude that from

the study you are designing.

DR. CURTIS: The data that are emerging,

that we have all seen the APPROVe data, we have all

seen the difference against celecoxib in the APC

study, to us, that suggests a class effect. I have

showed you our placebo-controlled data for

etoricoxib, it\'s very limited.

With that being said, the class effect

related to COX-2 inhibition, we would presume

extends to etoricoxib, and, to us, the real

clinical question is in patients who require

chronic treatment, what is the cardiovascular

safety against a standard of care, and for the

reasons I reviewed, we chose diclofenac.

DR. WOOD: So, let me be sure I

understand. So, we are going into this study

saying that we know and believe that the drug will

produce a cardiovascular signal, we are just trying

to work out if it\'s better or worse than

diclofenac.

DR. CURTIS: No, I think what we are

370

asking is\--

DR. WOOD: Well, that is what you just

said, isn\'t it?

DR. CURTIS: If I could rephrase what I

said, I think what we are saying is we are

suggesting there is a class effect, and we are not

sure how big the class is, and we feel that the

MEDAL study will help provide information to

address that specific question, whether

cardiovascular safety for selective COX-2 inhibitor

is the same or different than that of a traditional

NSAID, one that is the most widely used NSAID

around the world currently.

DR. WOOD: Okay. Dr. Bathon.

DR. BATHON: I was going to say much the

same thing. I have the same concerns about this

especially since naproxen is the most widely

prescribed NSAID in the U.S. and the most relevant

to our practice, whereas, diclofenac has much more

hepatotoxicity especially in RA patients where

methotrexate is co-administered.

So, I think it would have added a lot more

371

to our clinical practice management to see another

big trial against naproxen rather than diclofenac,

plus you could have added these results to your

prior trials and had more power to assess the

effect of naproxen versus etoricoxib with all of

your trials combined, but now, since you are using

diclofenac, you don\'t have that extra power.

DR. WOOD: Dr. Reicin.

DR. REICIN: Let me just make one comment,

and as all you start to talk about designing

clinical trials, I think you will see, as many of

you know, it is quite difficult and you cannot

answer every question in every study.

MEDAL was started over two years ago, and

at that time there was no placebo-controlled data

to suggest that COX-2 inhibitor was different than

placebo. Obviously, that has changed. The studies

are fully enrolled and ongoing.

I can\'t disagree with you that the idea of

doing a naproxen plus PPI study versus a COX-2

inhibitor isn\'t a good idea and isn\'t an important

question. Unfortunately, we didn\'t design that

372

study, we designed this one, and I think, as Garret

said, it will provide information about how big the

class is.

While some of you may not be using

diclofenac, it is the most widely used NSAID in the

world, and therefore, I think it will provide

beneficial safety data to see what a selective

COX-2 inhibitor looks like versus a non-selective

inhibitor albeit not as non-selective as naproxen.

DR. WOOD: Thanks.

Dr. Dworkin.

DR. DWORKIN: Yes, a simple question. You

said that the CPMP had come up with class labeling,

but you neglected to tell us CPMP defined the

class. Is it all NSAIDs, is it COX-2 inhibitors,

and if the latter, what drugs were included in that

subclass?

DR. CURTIS: I am going to give my

understanding as a clinician who has been here for

the last 48 hours, but my understanding it is

specific to what we consider the selective COX-2

inhibitors - celecoxib and etoricoxib, and that

373

that is how the class is being defined currently.

DR. DWORKIN: So, those two drugs, but

not, for example, Meloxicam.

DR. CURTIS: Dr. Erb, would you like to

comment on any additional agents?

DR. ERB: Yes, Dennis Erb from Regulatory

Affairs.

The CHMP is included in the class, what we

have been referring to today as the coxibs,

lumiracoxib, celecoxib, and etoricoxib, and

valdecoxib.

DR. WOOD: Dr. Platt.

DR. PLATT: More on the history of the

choice of comparators. Dr. Schiffenbauer, could

you tell us more about the conversations between

the agency and the sponsor around the choice of

comparators?

Your comments and the materials you

presented to us suggested that you had reservations

about that choice.

DR. SCHIFFENBAUER: Yes, we had extensive

discussions with the sponsor. At the time we

374

appreciated the difficulties doing a

placebo-controlled trial, but we had requested\--and

I can\'t quote you whether it was additional

comparators or comparator\--but we had recommended

strongly that additional agents be studied to get a

better handle on the true cardiovascular risk.

DR. PLATT: Was there discussion about

naproxen as a comparator?

DR. SCHIFFENBAUER: Not specifically other

than to mention that we recommended additional

comparators.

DR. WOOD: Dr. Farrar.

DR. FARRAR: One of the things that

strikes me about all of the studies that we have

been looking at, and perhaps most in the comparison

of studies that we are still waiting for some data

on, namely, APC and CPAC, is the difference in the

underlying risks between some of these different

comparisons.

I noticed that in your particular study,

the cardiovascular risk, you felt that 38

percent\--I think that was the number\--that in your

375

slide you had 38 percent at an increased risk of

cardiovascular disease with 24 percent on aspirin

and 10 percent of them as being diabetic.

I just wondered if you could comment on

what the mix of the MEDAL study is likely to be or

is. I mean you certainly would have the data at

this point.

DR. CURTIS: Yes. 1103, please. The

MEDAL study population is, as I mentioned, both OA

and RA patients, so approximately 75 percent of the

patients have OA and about a quarter have RA. What

is represented here are the risk factors for the

cohort, the entire cohort, and it is not dissimilar

to what I highlighted for the EDGE study.

These are basically baseline medical

diagnoses at the time of entry into the study, so

about half have hypertension, which is a little

higher than the EDGE study, which was about 40

percent, as you see here, the individual cardiac

risk factors, and this 12 percent of history, that

is documented atherosclerotic cardiovascular

disease. The 38 percent that I quoted for the EDGE

376

study was patients with this or to primary risk

factors.

So, that percentage, if I were to

calculate that percentage for this study, it would

probably be a little higher than EDGE, probably

about 40, 42 percent. So, these are the patients

in MEDAL.

DR. FARRAR: If I could just follow up and

ask actually Garret FitzGerald, whether he has any

comments on the relative risk of patients who have

either high or low cardiovascular risk factors.

I mean we know from the study, the CABG

study, that patients with very high risk clearly

have a marked increased response to these drugs,

and whether people who have cardiac risk factors

are also in that category, or whether it really is

restricted to sort of the release of active agents

from the surgical procedure.

DR. FITZGERALD: Well, obviously, the

actual information we have relevant to your very

important question is conjecture. What we know

mechanistically is that what we would expect would

377

be the response to thrombogenic stimuli would be

enhanced, as would the predisposition to the other

cardiovascular adverse manifestations of this

mechanism, namely, hypertension and atherogenesis.

So, for example, if a population was

enriched in patients with secondary

hyperaldosteronism, they would be more prone, on

average, to exhibit hypertension in response to an

NSAID or particularly a selective COX-2 inhibitor.

Similarly, if they were at advanced risk

of hemostatic activation, they would be prone to

the thrombogenic complications, and I think with

the CABG patients, we had an extreme phenotype of

excessive hemostatic activation.

Now, as we move away from that extreme

through what we call \"heightened\" cardiovascular

risk, there is probably a continuum of

predisposition that is a mix of predisposition to

the various types of manifestation of this

mechanism that could occur.

So, we have only crude indicators

obviously, and to some extent, as I talked about

378

yesterday, it\'s in the eye of the beholder as to

what defines heightened cardiovascular risk, but on

average, the group defined as having higher

cardiovascular risk, for example, RA compared to

OA, on average would be expected to show a signal

easier than in a group with low cardiovascular

risk.

I mean I would think with this type of

study, we may have had a premonition of the outcome

from the EDGE result. For example, if we think of

these two drugs as defining the limits of a class,

just for fun, one could say like in the EDGE

results, you wouldn\'t see a distinction in the hard

GI endpoints or the hard cardiovascular endpoints,

but what you might see a distinction in is their

fringe surrogates, which might be easier to pick

up, such as discontinuations because of

hypertension or discontinuations because of GI side

effects, and that is actually what was seen at the

two ends of the spectrum in the EDGE result.

DR. WOOD: But we do know from the APPROVe

study that the point estimate, even in the people

379

with no history of cardiovascular disease, which

would be the only clinical measure we could

reasonably use to distinguish that, it is still

substantially greater than 1.

DR. FITZGERALD: Yes, I mean I did try to

raise the issue yesterday that how we define

underlying clinical substrate is an inexact

science, on the one hand, and on the other, that

many other factors that we discussed yesterday

could play into the likelihood of manifestation of

risk at the individual level.

DR. WOOD: Steve.

DR. NISSEN: I want to maybe bring us back

to earth a minute and talk about the time horizon

for such a trial. I feel compelled to point out

that we have got a lot of history in cardiovascular

medicine of studying drugs for atheroprotective

effects.

Those trials are typically not one year or

two years or even three years, they are typically

five-year studies, and in many of them, let\'s take

a blockbuster class of drugs like the statins.

Look at the CARE trial. The CARE trial,

the Kaplan-Meier curves didn\'t diverge at all for

two years, and so now we have got a drug here that

380

may be promoting atherogenesis, and so we are going

to say, well, we are going to have a 20-month mean

exposure, and if it doesn\'t produce a problem,

then, there must not be a problem, and I am not

sure that\'s right.

The problem we have is that what has been

done here is the sample size has been increased to

a large sample size in order to shorten the

duration, but that may not be the same as studying

a more modest size group of patient for three or

four years.

It is assuming that the hazard is constant

over time, and I am not so sure that it is here.

If, in fact, Garret is right, and he has been right

about a lot of things, that these drugs are

potentially atherogenic, then, an atherogenic

intervention may not produce an effect for several

years.

So, how can you reassure us here that a

381

20-month mean exposure is enough to allow us to

move forward with a drug like this?

DR. CURTIS: I think what you are touching

on is\--I am not going to disagree\--what I am going

to point out is the fact that I think running an

arthritis study is perhaps different, and I have

not designed outcome studies, cardiovascular, other

than this\--but to keep arthritis patients in

studies is difficult, and that has to do with the

treatment of the disease.

As the rheumatologists here can speak to,

a traditional trial has 40 percent of the patients

discontinuing after one year, and another 10 to 20

percent dropout rate every year subsequent, so

there are significant practical limitations to

keeping patients on study therapy into the time

frame that you proposed, Dr. Nissen.

So, that is a practical limitation to

running arthritis studies.

DR. NISSEN: I just would also point,

however, that the patients that we studied

initially with these atheroprotective drugs were

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very high risk secondary prevention patients.

These were not low risk people.

So, you are going to take a lower risk

population and you are going to look for a signal

at a 20-month mean duration, and that signal may

actually take longer to show up in a lower risk

population.

So, I am troubled by how long we have to

look for with a drug like this before we really can

say there isn\'t a problem. People may take these

drugs for a decade. We heard that from people at

the microphone here.

So, these are some of the things that

trouble me about the whole question.

DR. WOOD: I have got a whole list of

questions here, but I want to keep us moving here.

So, are there any people who have burning

questions that they want to torture Dr. Curtis with

before we let him off? It has to be specific. We

will take Tom, we have not heard from you yet.

DR. FLEMING: Burning?

DR. WOOD: Burning.

DR. FLEMING: There are two or three

issues I want to quickly review. You didn\'t

mention in EDGE the new ischemic heart disease or

383

the heart failure, pulmonary edema, cardiac

failure. I think the FDA indicated in their

review, there was a 25-19, and a 14-6, so basically

about a 30 percent relative increase and a doubling

in those two, is that your understanding?

DR. CURTIS: The numbers, yes, Dr.

Schiffenbauer quoted, those are the correct

results, and that information was in your

background package.

DR. FLEMING: And then very quickly, your

slide 19 and then your slide 25. On your slide 19,

do you have the analogous slide for the APTC

results? If you don\'t, my understanding is the

relative risks are less favorable than this or more

unfavorable, depending on your perspective.

They are 1.8, 0.87, and 2.72?

DR. CURTIS: That is correct, yes.

DR. FLEMING: So, essentially, we are

looking at with roughly a 3 to 2 randomization in

384

the aggregate, and the aggregation of these events

here, we are looking at 43 versus 12, so a pretty

substantial excess in the critical APTC measures.

DR. CURTIS: Well, again, as you know, the

APT events in total are smaller than these numbers,

so your confidence intervals around those point

estimates are, in fact, much broader.

DR. FLEMING: But at 43 to 12, they are

certainly well outside of unity.

The last thing is slide 25. You give the

mortality results, but it is difficult to really

see in this scale, but it appears that the relative

risks are roughly in the range of 1.6 against

placebo, also 1.6 against naproxen, and 1.2, and

then in addition to that, it is also 1.33 in the

EDGE trial.

So, it looks as though when you look in

terms of relative risks, that you are looking at

about a 1.5 relative risk on mortality across the

aggregate of these data.

DR. CURTIS: Yes, this slide shows the

rate with the confidence interval. I don\'t have

385

the relative risk.

DR. FLEMING: But those aren\'t relative

rates is my point.

DR. CURTIS: That\'s correct, these are

absolute rates here.

DR. WOOD: So, you are saying this stuff

doesn\'t look it\'s good for you. Anyone else who

has a burning question? Go ahead.

MS. MALONE: It\'s burning. I would like a

simple answer. How much different\--now, I heard

him call this like Vioxx lite, I believe I heard

him say that\--how different is this from Vioxx, you

know, chemically, and do you see it as a substitute

for people who are perhaps taking Vioxx?

DR. WOOD: I think we are talking about

diclofenac. It was the comparison to diclofenac

which had been referred to.

MS. MALONE: He also did a presentation on

etoricoxib. So, can he answer that?

DR. WOOD: You are asking me?

MS. MALONE: No, him. Okay, I am sorry, I

thought you had said that about etoricoxib.

DR. CURTIS: Can you clarify the question,

please?

MS. MALONE: I am just wondering how the

386

compound in etoricoxib compares to Vioxx.

DR. WOOD: You mean chemically?

MS. MALONE: Yes, but in simple terms.

DR. CURTIS: The human whole blood assay,

if that is your specific question, the human whole

blood, which is sort of the gold standard, that

shows a degree of COX-2 selectivity that is greater

for this drug, but in the clinical dose range,

etoricoxib, just like rofecoxib, just celecoxib,

just valdecoxib, are selective for the COX-2 enzyme

in the clinical dose range, so in that regard, they

are similar.

Does that answer your specific question?

MS. MALONE: I am just wondering, you

know, I have heard people say that Celebrex or

Vioxx was much more selective than Celebrex and

Bextra, and where does this fit in, in that scheme?

DR. CURTIS: Again using the human whole

blood biochemical assay, this drug would be

387

considered more selective, but I think the key

concept, at least for me as a clinician, is that in

the dose range that these drugs are used, they all

selectively inhibit the COX-2 enzyme and do not

inhibit COX-1.

DR. WOOD: Let\'s move on to the next set

of presenters and let Dr. Curtis off the hook.

Thank you very much.

Are there questions for the Novartis

presenters from the committee? Some of the people

who are still waiting for the questions, we will

begin with them if they want to start with the

other ones. Dr. Abramson had one, I know, and we

punted.

DR. ABRAMSON: That was the TARGET

presentation by Dr. Villalba. I would like to just

throw slide 9 up, if we could, and follow up on a

point that Dr. Hennekens made when we started this

session.

In that slide, you combined the two

component studies of TARGET and again said that

lumiracoxib behaved differently in the two studies,

388

but I think that is probably incorrect to put up a

slide like that. It is like putting up a CLASS and

a VIGOR slide together, because these were, as I

understand it, separate studies and separate

populations.

That is the comment, but the other

interpretation, as we heard, is that lumiracoxib

performed less well than naproxen, maybe because it

has a risk and maybe the naproxen has some

protective effect, but was comparable ibuprofen,

which again raises a question whether ibuprofen has

some risk attached to it.

But my question is that you then said that

you attributed these findings to a class effect,

and since definitions are going to become very

important for us going forward, I was wondering if

you could tell us what you meant by a class effect

and what you were referring to, is it the class of

NSAIDs?

DR. VILLALBA: Yes, yes. First of all,

this slide was made by the sponsor, we didn\'t make

the Kaplan-Meier curve, so this was just a

389

different way of presenting the data. I don\'t

think it was in the background package for you, and

I thought it was an interesting way of looking at

it, raising the issue that precisely you cannot

just combine the two studies, because the sponsor

also has presented the data of the two studies

combined, lumiracoxib with NSAID, and you cannot

just combine these two studies, because they are

different studies.

I agree with you, you cannot cross-compare

even within the same study that had two

sub-studies, so we cannot compare to other studies

that were done with different designs and different

entry criteria, different endpoints, so that was

the point of the slide.

Regarding the class effect I mentioned, I

referred to the NSAID class effect. I think that

if there is an effect, it is for the entire class,

and that is a very heterogeneous class with

different degrees of selectivity within the NSAID

class. That is what I meant.

Actually, let me clarify. We also thought

390

that naproxen could be protective. I was seeing

these data at the same time that I was reviewing

all the other rofecoxib studies, so I guess you can

understand what our position was at this time.

DR. WOOD: Dr. Furberg? No? All right.

Dr. Bathon?

DR. BATHON: This was a question for Dr.

Matchaba.

I think there is an interesting

observation about the TARGET trial. Before we even

consider comparing lumiracoxib to the NSAID

comparators, but just looking at the baseline APTC

events in the two sub-studies of TARGET, there is

an event rate of 0.43 percent in one trial and 0.84

percent in the other trial, in the

lumiracoxib-treated individuals.

That is a 2-fold difference although the

numbers are small. I am wondering if that could

have been contributing also to the ultimate

difference between lumiracoxib and the comparator

drugs.

Even though you used the same inclusion

391

and exclusion criteria, could you tease out any

differences in the two study populations that were

enrolled into the studies that could have explained

the baseline difference in events in the

lumiracoxib groups? I don\'t mean baseline, I mean

the accumulated events.

DR. MATCHABA: Thank you very much for the

question. If I could have No. 8 and then could I

have CV No. 67.

As we discussed, the TARGET study was a

combination of two studies. The only thing

identical about the studies is the design of the

studies, but as I mentioned in the discussion

today, that this study against naproxen started

about 4 to 5 months before this study against

ibuprofen, and that the centers that were used for

this study were different centers even within the

same country, and the staggering of the recruitment

was to ensure that centers were not recruiting for

the same study.

In some cases, countries that participated

in one study did not participate in another study.

Can I see the CV67, please.

We have also asked this question to say

why are we seeing differences in the rates of

392

cardiovascular events for the 1-1 study versus the

ibuprofen sub-study. What we have done here is to

look is it a center effect, and there is obviously

a lot of reasons, we don\'t have all the answers or

explanations, but if you see for the major

recruiting countries, Argentina, Germany, and the

U.S., that the naproxen sub-study, in terms of

rates of APTC events, were always higher than for

the ibuprofen sub-study even in the same country.

So, if you look at the demographic data

that we also presented to you today, where 25

percent of the patients in this study were taking

low-dose aspirin, where we had a difference of 14

percent versus 10 percent in high CV risk, that

these populations are different in terms of

baseline risk, and certainly that might be an

explanation, it could be chance because the

confidence intervals cross, but we don\'t have all

the answers, but we think we have different study

393

populations.

I might ask Dr. Michael Farkouh to

elaborate on that because he was involved in the

design of the study and he was the primary author

for the TARGET cardiovascular paper.

DR. WOOD: Have we got the question

answered? I think we have. Let\'s move on. Dr.

Abramson, did we answer your question already?

Okay. Dr. Cryer.

DR. CRYER: Thank you. I have been trying

to understand the differences in the results

between the TARGET trial and previous outcome

studies of COX-2 specific inhibitors. One very

clear difference is in how the definitions were

rendered.

One thing that concerns me is that in the

lumiracoxib experience, both your CV and GI events

are defined to include people that not only had

definite MIs and definite GI events, but also

included those people who had probable events.

Typically, I am more used to seeing trials

in which we are looking at fully adjudicated

394

definite events. When I looked here, for example,

at your CV events, and eliminate what you call

silent MIs and look at just what would be

considered clinical MIs, there is an apparent

3-fold increase with lumiracoxib for clinical MIs

compared to NSAIDs, which dramatically differs from

your other conclusion.

With respect to the GI events, I think

that you actually studied a low GI risk population.

We know that the relative risk of COX-2 specific

inhibitors to have a GI benefit is greater in a

population that has low GI risk.

Specifically, you didn\'t include anyone

who had had a previous history of a GI bleed in the

last year, and greater than 50 percent of your

patients were less than 64 years of ago.

So, my question to you then is, have you

re-evaluated your data using more conventionally

accepted criteria, for example, fully adjudicated

clinical events rather than include their probable

events?

DR. MATCHABA: All the cardiovascular

395

endpoints, APTC, including silent MI, peripheral

events, deep vein thrombosis, pulmonary embolism,

TIAs were all predefined and prospectively

adjudicated blindly by an adjudication committee

before the study started.

This includes the GI or ulcer

complications and PUBs with the different

definitions that have been used, including

clinically evident bleeds, were also predefined by

a gastrointestinal committee.

DR. CRYER: I understand it may be

predefined, but I am asking do you have data if you

excluded the probable?

DR. MATCHABA: Yes. Perhaps Dr. Farkouh

would like to comment.

DR. FARKOUH: Michael Farkouh from New

York University. Our blinded adjudication

committee, the definitions of probable or definite

were purely on the basis of if we had all-source

documentation versus our clinical judgment of the

committee, which is many years of experience. I

happen to be the most junior member. A probable

396

cardiovascular event really, in our mind, was a

definite, that we just may not have had all the

source documentation we needed, so it really was

adjudicated as\--probable was an element or a degree

of definite is how I would put it.

DR. CRYER: With all due respect, I will

ask the question a third time. Do you have data

eliminating the subset of people who were

classified as probable, and looking only

specifically at those who you felt were definite

events?

DR. FARKOUH: From our clinical

cardiovascular committee, we did not feel there was

any distinction between the two of them, so we did

not mandate that. To be a probable event, I think

any cardiologist that would be on this committee or

anywhere else would have documented this as an

event. So, it is a degree of definitiveness. We

did not mandate that.

DR. MATCHABA: If I can just add to that,

the answer is yes, and if you just look at

confirmed cardiovascular events, the analysis is

397

the same, and just to add, that for silent MIs

besides what Dr. Farkouh has added in terms of

prospective definition, there was a total of 32

clinical MIs in TARGET, and there were 8 silent

MIs.

Of those 8 silent MIs, 5 of them were in

NSAIDs and 3 on the lumiracoxib. When we look at

silent clinical MIs, we still see the same trends

whether you compare the naproxen versus lumiracoxib

with ibuprofen versus lumiracoxib.

DR. FARKOUH: There is a moving target

here. The definition of MI has changed over the

last five to six years. We have a much more

enzymatic definition of MI which we have adopted,

and also the definition of silent MI has been

adopted into this modified anti-platelet trial.

I agree with Dr. Hennekens that it is not

part of the sharp definition, but rather we were

encouraged due to the signal of MI that has been

seen in this class of drugs that we document silent

MIs, and this was adjudicated through a blinded ECG

core laboratory run at the University of

398

Pennsylvania.

DR. WOOD: Dr. Fleming.

DR. FLEMING: Could we go to slide 33.

There, I think what you have tried to do is capture

the aggregation of the favorable effects on

reducing upper GI ulcer complication and the

unfavorable effects on the APTC.

I guess my first thought is that since you

didn\'t present the global data, I would assume the

global data is your primary analysis, and by my

crude calculation, the relative risk reduction is

probably more towards 25 percent or so rather than

the 41 percent that you are showing.

But I guess more to the point, is it not

apples and oranges here as you are trying to look

at the aggregation of evidence?

The ulcerative complication rate has been

reduced from 1 percent to 0.4 percent, so we can

think of it in terms of per 1,000 people, there are

about 7 cases that are prevented, and the APTC is

increased from 0.57 percent to 0.84 percent, so for

1,000 people, there are 3 of those cases.

Isn\'t it a little fairer to think of it in

that context? We have got per 1,000 people, 7 of

these ulcerative complications prevented, and while

399

those are substantial events, is it not true that

predominantly patients recover and don\'t have

long-term sequelae, while you are inducing 3 APTC

events that are CV-strokes or MIs that have much

more long-term effects?

So, isn\'t that a fairer question, and

while this picture makes it look like it is a clear

positive, I would have thought the answer is much

less clear, if not clearly negative.

DR. MATCHABA: Thank you. It\'s a fair

question. If we look at this combination of safety

data for the overall lumiracoxib compared to

NSAIDs, the reduction in the overall population is

35 percent. It was 25 percent in the naproxen

population overall, and it was not significant.

DR. FLEMING: I am focusing on just the

slide you are giving, which is the slide against

naproxen, so just to keep it simple in the

comparison against naproxen.

DR. MATCHABA: Yes. I think the first

comment we will make is that the comment was made

in the VIGOR study that any events that do occur in

terms of ulcer reduction and complications are

negated just quantitatively by the increase in

cardiovascular events.

400

I also made the comment that this is

certainly not validated, but it is an attempt on

our part that using this unvalidated method for the

first time and prespecifying it and stacking up the

primary endpoints, what does the picture look like

relative to comparators in the same study.

DR. WOOD: What Dr. Fleming is asking you,

that there is a qualitative difference\--

DR. FLEMING: Apples and oranges, yes.

DR. WOOD: And a GI bleed is not the same

necessarily as a stroke. They don\'t compensate for

one another. That is not a criticism, it is just a

fact.

DR. MATCHABA: Yes, that is a valid point.

DR. WOOD: And I think that is what he is

saying, am I right?

DR. FLEMING: Correct.

DR. WOOD: Any other questions for the

sponsors? Before anyone thinks of any, let\'s move

along.

DR. MATCHABA: Thank you very much.

DR. WOOD: One of the things that we left

undone from yesterday was that Dr. Furberg raised

some issues that he was unclear of some differences

that he thought he saw in the Pfizer briefing book

401

and from his calculations.

I charged him with meeting with Pfizer and

trying to resolve these. Dr. Furberg, did that get

resolved?

DR. FURBERG: We met and I got some

clarification, but I continue to be troubled.

DR. WOOD: So, the answer is no I guess.

Why don\'t we do this then.

DR. FURBERG: I think there are five

issues.

DR. WOOD: Why don\'t you tell us about the

issues and let\'s give Pfizer an opportunity to

respond.

Curt, why don\'t you go through the issues

as you see these.

DR. FURBERG: The first one related to the

number of trials included in the integrated safety

analysis for the acute pain studies. There was in

one place mentioned that there were 18 trials, in

another place there were 20, and the explanation

that was given was that the 18 trial analyses

excluded 2 trials, the one using the highest dose

of the drug, 60 mg\--more than 60 mg a day.

That doesn\'t satisfy me. If you are

looking at safety, the trials with the highest dose

402

are the ones that I am primarily interested in. I

think the company did the proper thing, they

included information about that, but they should

have included that in the pooled analyses, as well,

and that would have changed the message that you

take away from that summary table. So, that was

one issue.

DR. WOOD: Let me ask Pfizer, do you want

to respond to each one in turn, is that the easiest

way?

DR. HARRIGAN: That would be fine with me.

DR. WOOD: Let\'s do that, then, we can see

what the issues are.

DR. HARRIGAN: Just one slide, slide D114,

please. Ed Harrigan from Regulatory Affairs,

Pfizer.

What we have done with this slide is

basically pulled the two paragraphs from the

briefing document that Dr. Furberg was describing.

In Section 3.3, anybody who has the briefing

document and who downloaded it from the web would

be able to find these on pages 55 and 76.

In Section 3.3, as Dr. Furberg points out,

we integrated safety data from acute pain studies,

18 of these studies, and as it says in the

403

paragraph, they represented 4,087 patients treated

at a dose range of 20 to 60 mg total daily dose.

Later, in Section 3.6, we described 20

completed studies representing a larger number of

patients treated with valdecoxib at a dose range

greater than 20 mg total daily dose.

Now, the difference between these two

404

paragraphs is largely due to the CABG Study 035,

which is described in great detail, in fact, six

pages devoted to the CABG studies in the briefing

document.

It is a matter of opinion as to whether

one should have pooled this data. If one had

pooled all the 80 mg data, then, one might have

been accused of diluting the 80 mg treatment effect

that was seen in the CABG 035 study. On the other

hand, the 035 study was presented by itself with

full representation of the safety issues in that

study, which have been discussed in great detail

here in the committee, appropriately so.

I think that is probably the end of

response to that point.

DR. FURBERG: The second issue is to the

mean consistency in the reported event data.

Again, we are back to the same integrated safety

analysis of the 18 studies, and Tables 19 and 20

indicate that there was a total of 4 to 6 MIs

depending on how you define them, whether you

include sudden death in the report.

Well, separately, there were data

presented on two of the trials that were included

among the 18, and I just added up the number of MIs

405

and I come up with the number 8 to 10 when I define

it as non-fatal MI and fatal CHD. So, you already

have a negative balance. What happened in the

remaining 16 trials?

The explanation that was given was that in

the second CABG trial that got involved in the

analyses, they subtracted the number of events when

the patient was on the I.V. formulation parecoxib.

I looked it up and it turned out to be one case.

So, that doesn\'t explain the discrepancy, so the

explanation that was given was not satisfactory.

DR. HARRIGAN: Could I have slide D116,

please.

This is Table 20 in the briefing document,

I can\'t give you the page number. So, as Dr.

Furberg points out, this is a table that shows

placebo 2,468 and the 4,087 patients from the

valdecoxib studies at doses of 20 to 60 mg. Three

myocardial infarctions in the valdecoxib treatment

406

group.

Now, Table 22 is an illustration, it is a

table titled from one of the tables, there are

Tables 22 through 27 in the briefing document,

which report on the adverse events in the rest of

the studies described in that portion of the

briefing document.

As Dr. Furberg points out, we reported to

him earlier today that the myocardial infarctions

that he saw in the general surgery study and in the

two CABG studies, if they occurred to parecoxib,

they were assigned to parecoxib. These are trials

in which treatment with parecoxib took place for a

certain number of days, and then patients were

switched to valdecoxib.

If you assigned an event to both

treatments, then, of course, you are going through

tables until midnight, because they won\'t add up.

You have to assign the event to one treatment or

the other, they were appropriately assigned to

parecoxib, and so they are not accounted for in the

valdecoxib column.

A second reason for a difference is that

the adverse events in the tables that Dr. Furberg

was drawing them from are adjudicated adverse

407

events. So, these are events that were determined

according to prespecified criteria in both of the

CABG trials and in the general surgery trial.

So, aside from the parecoxib confound, you

wouldn\'t expect those adverse events to add up to

adverse events reported in a different way. This

is frequently an issue in safety summary documents.

There are a number of different ways to record

adverse events.

You have serious adverse events, you have

spontaneous adverse events reported to marketed

drugs, you have adverse events recorded in case

report forms in clinical trials. By presenting

them several different ways, you are sure that you

are giving the entire picture, because you don\'t

want to select one picture and be accused of not

showing the other two, but you can be guaranteed

the columns will not sum up.

DR. WOOD: But parecoxib is the pro-drug

408

for valdecoxib.

DR. HARRIGAN: It is.

DR. WOOD: So, as far as my body knows

when it gets parecoxib, it has got valdecoxib.

DR. HARRIGAN: Two points. One is that

the events are described in the briefing document

as you see, but they are assigned to parecoxib. I

don\'t know if you are suggesting that all treatment

groups that receive parecoxib, all patients that

receive parecoxib be transformed to valdecoxib.

DR. WOOD: I guess the body transforms it

to valdecoxib.

DR. HARRIGAN: It would obscure the data

from the effects of parecoxib, which is given by

different formulation. Some people consider that

significant, so I think to describe it under

parecoxib is appropriate. To not put it under

valdecoxib is appropriate. The data is in the

briefing document, it is not hidden, it is not

suppressed, it is clearly available in the briefing

document. The columns do not add up. We think

there are good reasons why they do not add up.

409

There are alternative ways to present safety data.

We are happy to, and frequently do, re-run safety

data and safety tables with different algorithms

and different rules.

DR. FURBERG: The numbers just don\'t add

up.

DR. WOOD: Have you another point, as

well?

DR. FURBERG: No.

DR. WOOD: I suggest that we are not going

to resolve this this afternoon, so why don\'t we

defer this to Dr. Temple and his staff to resolve.

Is that fair, Bob?

DR. TEMPLE: Yes. Curt agreed earlier

that he would write down exactly what the concerns

are, and we, not me, will follow them up and pin

down what is going on.

DR. HARRIGAN: It is important to us that

members of this committee and the FDA, and other

health agencies worldwide understand that we do not

suppress safety data. We report safety data, we

report it in a number of different ways, we do not

410

suppress safety data.

DR. FURBERG: But it would be much better

if you explained why you did it differently and

present the data in one way in one table, another

way in another table, the numbers should add up if

you have information from two trials and you have

more events than you have in the pooled analysis of

18, that has to be explained.

I think there are some numbers that will

be hard to explain away.

DR. WOOD: I think we have got it that

there is still a bone of contention here. Let\'s

move on to the three questions that we were charged

with discussing this afternoon.

Dr. Gross, I think wanted to make some

comments before we get to the first question.

Committee Discussion

DR. GROSS: On the first question, I would

like to propose a construct to deal with the issue

is the increase in cardiovascular risk a class

effect. My proposal is to say yes, it is, but the

degree of difference and the time of difference

411

varies and is different enough that one or more of

the drugs that we have discussed should be

marketable with a precaution and/or warning, and

one or more of the drugs we have discussed should

not.

A reasonable analogy is statins. As we

know, they all have potential for liver toxicity

and myopathy. That is a class effect, but the

degree of this difference and the time when it

occurs varies and is different enough that one or

more of the drugs have been marketed with a

precaution or warning, and one or more have not.

Tomorrow, we will discuss specifically the

recommendations on celecoxib, valdecoxib, and

rofecoxib, but I thought I would start off the

discussion with this question about a class effect.

DR. WOOD: Okay. Dr. Nissen.

DR. NISSEN: Did you mean class effect for

the COX-2s, or are you talking about NSAIDs, as

well, because the question is asked for both here.

So, I want to know which of those you mean.

DR. WOOD: Let me make a suggestion. I

412

think we should start with COX-2s. The data we

have seen is by far the most convincing for that.

Then, let\'s move on to any other issues.

DR. NISSEN: So, let me agree that is what

we are talking about then.

DR. WOOD: Let\'s have a discussion around

the COX-2s first and whether the available data

support a conclusion that cardiovascular risk is a

class effect for all\--

DR. GIBOFSKY: Could I just interject and

ask then that we discuss it in the context of

patients with arthritis versus patients with other

conditions?

DR. WOOD: Okay, that\'s fine, the

committee can do that, but remember we are not

discussing the relative risk-benefit at this point.

We are discussing whether there is an effect, a

signal, in other words.

DR. GIBOFSKY: I understand, but I think

it is relevant to look at the populations in which

the signal has been detected.

DR. WOOD: Do you want to comment on that

413

and save us going to back? Do you think that the

arthritis population will be likely to have a lower

risk than the other populations?

DR. GIBOFSKY: I am merely saying that I

think that one looks at populations. As we have

heard, there is variability in the population, and

just as we wouldn\'t automatically extrapolate

efficacy data from one population to another, I am

not certain we can automatically extrapolate safety

data from one population to another, and I think we

need to discuss it in the context of the population

studied.

DR. WOOD: Any other comments on this

question?

DR. ILOWITE: I think you made the point

that this was merely a discussion of safety, but I

think the way the proposal was worded, there is

implications about cost-benefit with regards to

whether they should be approved or not. Could you

repeat the\--

DR. WOOD: You have the question in front

of you.

DR. ILOWITE: The proposal.

DR. WOOD: Dr. Gross made a proposal, but

the question we have got in front of us is to

414

discuss the available data supporting a conclusion

of increased cardiovascular risk for COX-2

selective nonsteroidals.

I think we need to discuss that before we

get to risk-benefit frankly.

Dr. Nissen.

DR. NISSEN: I think your proposal is an

appropriate one and I would point out that we have

at least one randomized trial for every drug that

has been marketed in the class that shows an

effect.

DR. WOOD: You mean a risk.

DR. NISSEN: That makes the grade in terms

of calling it a class effect, but I think that

there is clearly evidence of a gradient in risk,

and that gradient is not only by drug, but also by

dose.

So, saying it is a class effect means\--let

me tell you what it means to me. It means that if

415

you give a high enough dose of one of these drugs

to a risky enough patient, you can produce an

increased risk of adverse cardiovascular outcomes.

But it doesn\'t mean that a particular dose in a

particular population is risky.

DR. WOOD: Dr. Fleming.

DR. FLEMING: I think there is a great

deal of data that is giving us a general sense, but

there is an inadequate amount of information to

really get at the specifics, and what I mean by

that is certainly the indication, the dose, the

duration of therapy, the nature of ancillary care,

for example, aspirin use, these are all factors

that obviously could influence the answer.

The approach that I took was to try to

summarize the essence of what I think we have been

presented in the randomized trials, and I focused

in particular on those that were the major trials,

many of them looking at somewhat longer term

exposure and longer term follow-up.

There are about 15, and just to quickly

run through them, in the Vioxx setting, there are

416

23,000 patients from four major trials. Those

studies indicate something on the order of 1.4 to

1.5 relative risk, and driven heavily by VIGOR and

APPROVe, and neutralized somewhat by the

Alzheimer\'s 078-091 trial although that trial had

surprisingly considerable excess deaths.

In the Bextra setting, the Nessmeier 071

trial, the 035, and 069 studies give about a 2 1/2

relative risk even though it is certainly heavily

driven by this CABG setting.

In the Celebrex trials, the CLASS, the

Alzheimer\'s 001, the APC, the PreSAP, now, we know

there is the ADAPT, but we haven\'t been shown that,

so I did the first four, and we are looking about a

relative risk of 1.3, driven heavily by the APC

trial and the 001 study, and neutralized by the

CLASS study and the PreSAP that were more neutral.

The etoricoxib, the EDGE trial, and the

other three that we were presented give us a

relative risk of about 1.625, and in the

lumiracoxib, it is about 1.18 relative risk from

the TARGET trial.

Now, to put these into context, if we were

trying to show\--I am just going to give your four

scenarios\--a doubling. By the way, I am working

417

off a 1 percent background rate, and that is just

about what these data show in the aggregate, in

73,000 patients, about a 1 percent aggregate rate

for the primary cardiovascular endpoint of

cardiovascular death, stroke, and MI.

If you were trying to show a doubling, it

takes 88 events or about 5,000 people. If you were

trying to show a 50 percent increase, it\'s 256

events, 20,000 people. If you are trying to show a

33 percent increase, it\'s 508 events, 40,000

people, and if you are trying to show just a 20

percent relative increase, from 1 to 1.2, it\'s

1,265 events or 115,000 people.

Where we are, if you ignore all those

factors that I was arguing we can\'t ignore because

the answer isn\'t the same, but if you put all this

into a single pool, these add up to something in

the neighborhood of a relative risk of about 1.4 to

1.45.

So, essentially, what it would have taken

to discern that is an aggregate data of about

70,000, although the observed results that you

would have to have, you would have to have a study

on the order of about 5,000 people, because an

observed result of 1.55 or 1.45 is statistically

418

significant when you have about 6,000 or 7,000

people.

So, the point is when you look at the

aggregate, we have substantial data to say there is

conclusive evidence here in the aggregate that

there is the cardiovascular risk.

Now, what can we say individually? In the

Vioxx setting, where the risk is about 1.43, one

would need to have, with that observed rate, you

would have needed to have data on about 6- to 8,000

people. We have data on 23,000. That is why the

evidence there is very clear.

In the Bextra setting, we only have data

on 3,000 in the Nessmeier 035 and 069 trials, but

the relative risk is 2.58, and for a 2.58, you need

less than 2,000 people, hence, that is why it is

419

statistically significant in that setting although

it is only in the CABG setting.

It is also in the etoricoxib setting with

the relative risk of 1.625, we would have needed

less than 5,000 people. We have 17,000, so it is

statistically significant in that category.

In the lumiracoxib setting, we have a

relative risk of 1.18. That would have taken over

40,000 people for that relative risk to be

detectable. We only have 18,000. So, it is

suggestive of a modest or moderate excess, but it

is not proven because of the smaller sample size or

because of the smaller effect.

In the Celebrex, where it is about 1.29,

it would have taken 20,000 people, if you observed

that in 20,000, it would have been marginally

significant. We observed it in approximately

12,000, so it is suggested, but not established.

Now, a lot of this, this is looking at

things in a first pass. It is suggestive that

there is something going on in all of these cases,

but at very different levels is what at least the

420

data show, but the data aren\'t conclusive for us to

be able to say in a reliable way what is the

indication, what is the dose, what is the duration,

is it in aspirin, not in aspirin, but globally,

there certainly is an effect that is going on here,

and for three of these five, it seems to be

conclusively established, and for the other two,

more modest effects that are suggestive.

DR. WOOD: Thanks. Dr. Shafer.

DR. SHAFER: I don\'t know that this will

help our discussions at all, but I think one of the

things we need to address is what is a COX-2. It

has been assumed, I think, that we are going to go

with the company\'s definitions when they way we

have a COX-2 drug, COX-2 selective, but, in fact,

if you go to Warner\'s review in FSAAB here, from

2004, we see that Meloxicam, Sulindac, and as we

have heard, even diclofenac is potentially

considered a COX-2.

Should we include these drugs in the

discussions? We certainly won\'t have the

evidentiary evidence that we have.

DR. WOOD: Let\'s stick to the drugs for

which we have got evidence, otherwise, we will be

here until midnight.

421

DR. WOOD: Charlie.

DR. HENNEKENS: I want to support the very

crucial statements of Steve and Tom here. It does

appear to be a class effect, which varies by drug

and by dose, but the magnitude of that risk, which

I also estimate to be 1.4 to 1.5, is lower than one

would have guessed based on the early

data-dependent stopping of some of these trials,

based on the reported research, and the media

coverage of all of this, so I think it is important

to get Tom\'s quantitation and Steve\'s caveats about

dose and drug and magnitude in there.

DR. WOOD: Dr. Abramson.

DR. ABRAMSON: I want to go back to this

issue of definitions because I don\'t think that it

is that simple to say that the coxibs that we are

talking about are the only drugs that we need to

discuss.

The concept of diclofenac lite, that

422

Garret proposed, or has stuck, but I think that

term could be applied to Meloxicam, nemesulide. I

think what we are stuck with is that assuming there

is a class effect, we haven\'t excluded the fact

that that class includes those other COX-2

preferential drugs, that we might agree that COX-2

inhibition is at fault here, and that is giving

rise to some of these side effects, but it isn\'t

precisely due only to those drugs.

Now, those drugs happen to have done the

long-term studies, they have done them frankly at

2X dose compared to their comparators, and frankly,

when you look at the randomized clinical trial

development program with a relatively few placebo

arms, the drugs look relatively comfortable.

So, if you conclude that there is an

increased risk because of COX-2 effects and

hypertension perhaps, then, I don\'t think it\'s

really fair to restrict the discussion simply to

those drugs that got marketed as coxibs, the

randomized clinical trials, especially if you do

agree that perhaps Naprosyn has a modest protective

423

effect, I think don\'t give a bye to these other

drugs.

I think we have to look at certainly the

case of celecoxib, that drug is relatively

comparable pharmacodynamically to the other several

drugs, so I think it is a much more complicated

question than simply saying the COX-2 coxibs in

this discussion, and we have to do apples to apples

if we are going to make recommendations.

DR. WOOD: Dr. D\'Agostino.

DR. D\'AGOSTINO: My comment is very much

the same. I am concerned about taking all these

individual studies. I think, you know, sort of the

potential is clear, but are we really lumping just

because there is a direction on these here.

Tom, for example, the question about

splitting the arthritis populations versus the

other populations, the arthritis populations come

basically from the old clinical trials where

adjudication was a problem and things of that

nature. So, how much do we believe that data and

how much do we want to draw this inference?

So, I don\'t have a problem with sort of

coming up with some sort of global statement that

we are concerned, but I am concerned at this point

424

about quantification in a very heavy way, and we

just may be overdoing it in terms of how we are

sort of answering this question.

DR. WOOD: Just to make sure I understand

your point, you are concerned about putting a

number on it?

DR. D\'AGOSTINO: I am concerned about this

global, I mean for us to say that it\'s all COX-2.

DR. WOOD: But you would be comfortable

naming names?

DR. D\'AGOSTINO: I don\'t know what I would

be comfortable with. I am uncomfortable with the

sort of global statement that we have seen a number

of studies\--

DR. WOOD: I am just trying to draw out

what you are saying. You would be more

comfortable\--

DR. D\'AGOSTINO: The only thing we said in

terms of separating was the arthritis studies. Are

425

we comfortable with the arthritis studies, do we

have enough information, do we feel comfortable

enough with the adjudication process, the

recognition of the cardiovascular events in those

studies? I mean I think I am much more comfortable

when we come to these new studies.

DR. WOOD: So, what you are saying is that

the dilutional effect of these old studies may be

substantial.

DR. D\'AGOSTINO: Exactly, and I don\'t know

how we are actually dealing with that.

DR. WOOD: So, that is important for

people to understand. Do you want to develop that

a bit?

DR. D\'AGOSTINO: What is that?

DR. WOOD: So, what you are saying is that

the studies that didn\'t have a cardiovascular

endpoint\--

DR. D\'AGOSTINO: And trying to get

adjudication. They were showing a signal. We

already there is a signal.

DR. WOOD: So, they may be diluting the

426

effects from when Tom adds on the back of the

envelope\--is that reasonable, Tom?

DR. FLEMING: Well, I fully agree that the

best analysis of this is one that we don\'t have the

time to summarize here right now, but it is one

that will drill down in all of these dimensions as

best we can.

Almost certainly, the answer is here, if

we had unlimited data. We have about 75,000

people. That is a lot of insight, although we need

far more than that. We do have another 30,000

coming along shortly.

In essence, though, what we really need,

if we had the ideal, is that ability to drill down,

as Ralph says, by indication, and by dose, by

ancillary care, looking at whether or not it is an

aspirin or not an aspirin, by duration of therapy.

These are all things that we have seen the data

suggesting that there is very likely these factors

are influential.

So, essentially, my attempt was to say, in

a very crude way, what do you see from 10,000 feet

427

here, but then acknowledge exactly, as Ralph said,

that you really do need to drill down.

DR. WOOD: It is not likely to be less

than the numbers you gave. It is likely to be

more, right?

DR. FLEMING: Well, my own sense about

this is this is the weighted average of the

compilation of all these different settings, and so

in all likelihood, in fact, with certainty, there

will be settings where it is less, there will be

settings where it is more.

Can you, for example, give Celebrex at a

low dose with a short enough duration that in wide

settings, it would be safe. That is still entirely

possible within the context of what we have said.

Those are issues that we really need to understand.

DR. D\'AGOSTINO: And I am concerned

somewhat that if we give this global statement,

that we sort of can\'t get back to the question you

just raised, can we look at Celebrex at a low dose,

because somehow or other, we are saying it\'s in all

the COX-2s.

So, I want to be just careful in how, the

answer to this question, how it comes out

quantitatively and what it locks us into in terms

428

of further discussion.

DR. FLEMING: What I would say is

that\--and I do agree that we need to look beyond

these five or six products\--but what I would say in

several of these products, not just Vioxx, in the

certain settings that we have looked at, in my

view, there is evidence that establishes there is

an excess risk.

There are other products where there is a

suggestion, and we are underpowered, though, to

discern whether or not that suggestion\--it is not a

suggestion of nothing, though, it is a suggestion

of something, but it is more modest in size than

the other agents although it could be a dose issue,

it could be an indication issue that explains it.

DR. WOOD: Dr. Domanski.

DR. DOMANSKI: I think if one looks, there

is really an attempt here to look very carefully in

these quantitatives that we can. I think Dr.

429

Fleming provided a remarkable compilation just now

for us.

But I think if one backs off to sort of

high altitude and looks at these drugs, the signal,

as people are using the term, it is pretty clear

that there is an excess risk conferred by some or

all of these drugs.

It seems to me the process is sort of

turning around. We are trying very hard, you know,

the idea is to demonstrate\--and it\'s the sponsor

who has to do it\--to demonstrate safety and

efficacy, and not necessarily the purpose of the

FDA or its advisory committees to somehow

demonstrate that the thing is unsafe.

It does look like they are unsafe, but the

problem is that the studies presented really are

not very good studies, and, in fact, one of the

reasons that we probably didn\'t learn sooner that

there is probably a real problem with these drugs

is because of the relatively poor studies that were

presented for approval.

So, I think it is important to remember

430

who has got what role. It is theirs to demonstrate

safety and effectiveness, it is not ours to

demonstrate it\'s unsafe.

DR. WOOD: Right, but I think the FDA is

looking to us to give them some guidance here,

right?

DR. DOMANSKI: Well, that is important for

the future particularly, that is, what studies

should be done next, and that is a legitimate

concern.

DR. WOOD: Bob, do you want to say

something?

DR. TEMPLE: Just that it is the company\'s

job to show that it is safe, but we sort of have to

say what would constitute adequate evidence, what

sort of level of risk do you have to rule out, how

long, and things like that.

Of course, we are in the process of

learning about those things as these data come in.

As I said before, I don\'t think anybody would have

thought you need a four-year study, but that is

sort of on the table now, and it wouldn\'t have been

431

before.

So, it is helpful to know what kind of

risk is plausible to rule out and all the things

that Steve said before, I mean you have got to

worry about what doses to study.

We encouraged everybody to study high

doses to rule out GI distress. Whether that was

wise in retrospect, I am not sure, and I think I

probably had something to do with it a long time

ago. I am not sure that was the best thing. We

want to be really sure you couldn\'t make an ulcer.

I, at least, wasn\'t thinking about maybe making

something else.

So, all of those questions are things we

need help with even though, yes, it\'s the company\'s

job to bring the data forth.

DR. WOOD: Dr. Farrar.

DR. FARRAR: In terms of the specific

question that we are addressing, I also just want

to point out that there is a second part to that,

which it says, also, discuss the possible

mechanisms of action for an increased

432

cardiovascular risk with these agents. I think

that has bearing related to the fact that if we

accept that the in vitro selectivity of the

COX-1/COX-2 analyses at least have some bearing on

at least their metabolic process.

What I am struck by is the variability of

the agents with regards to other factors indicating

that simply COX-1/COX-2 inhibition is not their

only action, and that the ones with some of the

higher risks are not necessarily the most COX-2

selective.

What that suggests to me is that we really

don\'t understand the process yet well enough to be

able to say that it is a group selective, because I

am not sure what a COX-2 selective one is, where do

you draw the line.

I think a more appropriate way to say this

is to say that clearly, the role of COX-1 and COX-2

inhibition are important in the process of both

anti-platelet and perhaps platelet aggregation, and

that those with a more predominant COX-2 component

need to be studied carefully for the potential

433

excess cardiovascular risk.

I have a great deal of difficulty, though,

saying it is the group of drugs that have been

called that by the pharmaceutical industry. I

think that that is being very short-sighted about

this.

In fact, the data that we have seen in

these presentations make me want to go back and

look at ibuprofen with regards to a whole host of

issues that we hadn\'t thought of before. So, I

think it is very important that we keep in mind

that there is not a distinct relationship between

those numbers specifically and that we need to be a

little bit broader in terms of that look.

The other point I would like to make is

that we clearly need to differentiate in terms of

what we are considering between the placebo trials,

which have been done primarily in cancer

prevention, and the comparative trials with other

agents. As has been brought up many times, none of

the agents are the same, and so the comparisons

there need to be carefully considered.

As such, I am in favor of a statement that

says that we are consciously aware that COX-2 is an

important component of this issue, but that all

434

agents that claim to have, really all agents that

are developed in the future and all the current

agents need to be carefully looked at for the

balance between the cardiovascular, GI, and other

risk factors including the hypertension, including

the pulmonary edema that we have heard so much

about.

DR. WOOD: Right. One pragmatic way

perhaps that we could handle this is there are two

drugs of whatever the class we are talking about is

that are left on the market, and for which we have

a number of randomized trials recently, and we

could consider them as a sort of present tense

evaluation, and for future tense, other drugs that

may have signals that we don\'t really understand,

and certainly drugs that were likely to be marketed

in this area, this space, and whatever that means,

and would need some sort of evaluation.

So, that would sort of divide up our work,

435

so that we would be considering what to do about

the ones that are out there, what to do about the

ones that are potentially out there, and I guess a

third group is what to do about other drugs that

may or may not fit into this class or may not be at

some extreme of this class.

Is that sort of capturing the essence of

what you are saying?

DR. FARRAR: That is certainly one way of

dividing up the work.

DR. WOOD: Let\'s think of it in terms of

that as we move forward.

Dr. Holmboe.

DR. HOLMBOE: Actually, a number of the

things that I was going to say have been said. I

would just add one caveat, Tom, to what you said,

that if you look at these trials, over 40 percent

of the patients never made it to the end of the

study, which means that we probably don\'t have over

70,000 patient observations. We probably have

about 20- to 30,000 less who actually made it to

the end of the trial.

That, I am very concerned about, and you

look at these trials also, although they look

similar when they are first randomized, that is the

436

purpose of randomization, the populations that get

to the end don\'t, so I think that we are also

lacking some very important information, what

happened to a fairly large number of individuals

who started but never got to the end of the trial.

DR. FLEMING: Just to respond to that,

that is a key point. Now, the analysis that I did

yielded approximately 7- to 800 events, so we are

getting the total number of events that we would

have needed from a 70,000 person trial, but your

point is still well taken.

We are not underpowered because of the

lost to follow-up, but there may be a bias here

that we all talked about earlier, that if you

really wanted to get the most insightful, reliable

assessment, you need to have high quality

follow-up, so that is something that is still a

relevant point. They are unequal in their quality

of study conduct in the area of follow-up.

DR. D\'AGOSTINO: This was part of my

concern in terms of what I was trying to raise,

that we have studies, but we don\'t have studies,

there is a lot of problems with it.

DR. WOOD: Dr. Dworkin.

DR. DWORKIN: Ralph, I have a question to

437

follow up on what you were saying earlier. If I

understood you, you were saying that you are

uncomfortable with a global statement of the sort

that Dr. Gross was making because you feel there is

some kind of heterogeneity amongst the data, of the

type that Tom summarized.

But then it seems to me you are between a

rock and a hard place, because if you believe that

there is a great deal of variability in the results

with respect to risk, how could we possibly

discriminate amongst the different drugs.

DR. WOOD: We have done that lots of times

before.

DR. D\'AGOSTINO: The qualities of studies

are different. I think the arthritis studies is

where we get the CV information, they weren\'t

438

designed to get the CV information, cardiovascular

information, so I think there is a signal there,

but I don\'t know how to interpret it.

I think there is the problem of lost to

follow-up and things of this nature, and all of

those things make me very uncomfortable, and sort

of making a global statement and then living with

that global statement.

I think it is clear or hopefully it is

clear what I am concerned about. We don\'t want to

be locked into, by making a global statement, later

on saying that no matter what drug we look at, we

have an answer for, and it may be low dose of

Celebrex, that may be viable, and not unsafe.

We really need to worry about the studies

that we are going to suggest, and if we absolutely

thought there were safety problems, why are we

suggesting them, why aren\'t we just saying stop the

studies and get the drugs off the market. I think

there is a lot of room for maybe there is something

going on that is safe, and we want to really pin

the issues down in good clinical trials.

DR. WOOD: Well, we have dealt with drugs

within classes before. I mean a statin was

removed, but the other statin is on the market, and

439

troglitazone was removed, but the other drugs

stayed on the market.

I guess the difference here, which is only

fair to point out, is that this is thought to be

producing toxicity through the primary mechanism of

action. At least that is one of the postulates,

but we certainly should deal with them as

individual drugs, I think, rather than as a class

of drugs.

Dr. Abramson.

DR. ABRAMSON: I guess what I am thinking,

it is possible to accept the fact that many of

these toxicities are via the COX-2 mechanism, but

recognizing that all of the class of NSAIDs, by

definition, when they are effective, are inhibiting

COX-2, and I am still troubled by the population

data which shows signals with indomethacin and

Meloxicam, and by older data which shows congestive

heart failure particularly with the non-selective

440

drugs.

So, I think that we have to look at again

the entire class, and particularly if you look at

the CLASS and the TARGET trials, why is ibuprofen

and diclofenac behaving pretty much like Celebrex

and lumiracoxib, so if there is an assumption on

our part that this class of drugs, even the highly

selective COX-2s, increase by 1.4, 1.5 the relative

risk, why is ibuprofen and diclofenac looking

pretty comparable in those large population trials.

One answer is that they, in themselves,

whether diclofenac is rofecoxib lite or not, but

they themselves are imparting a risk, but they

themselves have not been subject to these long-term

placebo-controlled trials that we see in APPROVe

and ADAPT.

So, therefore, I think the COX-2 mechanism

may pertain, but it cuts across all degrees of

relative selectivity.

DR. WOOD: Dr. Furberg.

DR. FURBERG: Well, I spent about five

years looking for a definition of class effect, and

441

so far I have been unsuccessful. There is in the

literature no definition of class effect. The

closest I came was an FDA definition of class

labeling, and that was not a good one.

So, I think the working definition of a

class effect would be that members of a particular

group or class share common actions in the broad

sense, and I think that would apply to the COX-2s

in my reading. They provide pain relief, GI

protection, raise blood pressure, cause fluid

retention, have the undesired effects on

cardiovascular risk, so in my mind this is a class

and sharing a lot of actions, and that would

include the increased cardiovascular risk.

DR. WOOD: I am going to take two more

questions on this topic and then I would like to

move us to, I guess, considering which drugs, to

answer Question 1, which drugs, rather than a

class, which drugs we see a cardiovascular signal

with, which is one way to approach the problem.

You are the next question, Steve.

DR. NISSEN: What I wanted to make sure we

442

got to is this issue of mechanism, which is

actually in the question here, and the reason it\'s

important is that I am not quite ready to accept

the hypothesis that one can predict from the COX-2

selectivity and duration what is going to happen in

these drugs.

Let me see if I can explain that because I

think it is very important as we think about how to

go forward here. I see a broad spectrum of blood

pressure changes that don\'t seem to be as tightly

linked to the COX selectivity as one would guess.

Lumiracoxib, for example, which is very

COX selective, doesn\'t appear to have much effect

on blood pressure. Rofecoxib has the largest

effect on blood pressure by far and is relatively

COX selective, and they are very different.

So, for the FDA, I think if you want to

characterize the drugs, not only do we need

clinical trials around looking for GI safety and

cardiovascular safety, we need a standardized

method to look at the effect of these drugs and

their intended doses on blood pressure, and they

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ought to all be subjected to similar scrutiny, so

we can compare apples to apples and wherever

possible with active comparators, let us understand

that.

Now, why do I say that? Because Bob and I

have sat at many a meeting and looked at blood

pressure drugs, and I can tell you the data on the

relationship between relatively small differences

in blood and cardiovascular morbidity and mortality

is rock solid across a huge number of drugs and

interventions, and you almost can predict what will

happen.

So, we need to know\--and as I sit here, I

can\'t tell you that drug X in this class has Y

blood pressure effect and drug A has B blood

pressure effect\--and so we don\'t know, and we can\'t

inform physicians about that unless we have better

data on blood pressure.

So, I am making an appeal that we get to

that level of specificity, and that is not a very

big trial to do that. Bob, what do you usually ask

for in the blood pressure study?

DR. TEMPLE: Well, if you use automated

pressure monitoring, I think you can get a decent

answer with 20 or 30 per group, maybe 40. It\'s

444

very easy.

DR. WOOD: Let\'s move on. I am going to

give you the last word in a second. After we get

Dr. Gross\'s comment, we are going to divide this

first question into three things, which drugs do we

see a cardiovascular effect of, and the secondly,

we can ask whether we see a class effect, whatever

we understand that at, and I am not sure we do, and

then the third question that is in Question 1 is

what do we see as a mechanism.

So, let\'s divide them into these three

things and let\'s move to an answer.

Peter, last word.

DR. GROSS: What we say here today about

these is going to have a significant impact in

molding public perception, and if we conclude that

there is a class effect for the selective COX-2

inhibitors, and don\'t say the same thing about

non-selective NSAIDs in general, then people are

445

not going to want to use COX-2 inhibitors at all

and they will be using the non-selective NSAIDs,

which from the data presented, doesn\'t look as

though many of them are better from a risk point of

view.

So, I just issue that note of caution.

DR. WOOD: Does the FDA want us to go

around the table asking people for an answer to

each of these questions, the subsets of these,

John?

DR. JENKINS: I think we really viewed

these questions as things to stimulate your

discussion, not necessarily things that are

amenable to yes/no answer. The yes/no answers come

tomorrow.

DR. WOOD: So, can we move on?

DR. JENKINS: If you think you are done

with No. 1.

DR. WOOD: We are done with No. 1.

DR. TEMPLE: I just wondered if people

could come to grips a little bit with some of what

Steve said and some of what other people said. I

446

absolutely don\'t want to put words in anybody\'s

mouth, but what I heard people say was they think

the class has at least the potential for having

this problem because of the imbalance and because

of the stuff we have heard about before, and that

you need to look at each drug to see whether that

is manifested at a particular dose-dose interval

and all the rest.

I just wondered whether that is getting

close to what people are saying or not, and I

absolutely am not giving my view on it, I am just

suggesting it.

DR. WOOD: Let me try and answer that and

then we will go around and ask other people.

I think what we are saying is almost the

same as the GI effect before the GI effect or not

was worked out for the so-called COX-2 inhibitors,

that I see an effect, a cardiac effect from

valdecoxib, certainly from Vioxx, and from

celecoxib, and there is a dearth of data on the

nonsteroidals, the other nonsteroidals at this

stage in terms of cardiac safety, and we are not

447

going to be able to decide that even on Friday, it

seems to me.

In the presence of that signal, the

prudent activity would be to go look at it sometime

in the future, but we can\'t do that between now and

Friday night. So, that is sort of where I come

down.

Dr. Abramson.

DR. ABRAMSON: I might have a slightly

different view, because I mean I think of the class

more broadly as it is defined now to include both

the COX selective and non-selective drugs. I think

that there is a signal probably for all of these

drugs, maybe by different mechanisms perhaps. I

think we have under-recognized that in the

population, I think physicians have not been

concerned enough about blood pressure changes.

So, my view is that maybe there will be

different mechanisms, but that each of these drugs

is suspect as having an increased relative risk

when used chronically, whether it is ibuprofen or

the most selective COX-2.

My own view is, as I said earlier, is this

is not dissimilar to the late \'90s, and until you

prove otherwise, this is GI warning that these

448

drugs may cause cardiovascular risk or GI warning

it may cause serious adverse events, and I think

each of them should be held to that right now until

someone proves otherwise, because I think it would

be wrong based on the evidence to assume that three

drugs have a cardiovascular risk, and several of

the others don\'t, simply because we don\'t have the

evidence.

I am also concerned about some of the

research that was talked about by one of the public

speakers. At most of our universities, these

studies have actually stopped because of concern

that these drugs are not as safe than the

non-selective drugs.

I think, particularly in cancer and

others, we are doing the public a disservice by

prematurely picking out these drugs as being unsafe

and stopping some very important research where the

risk-benefit might even be more important than in

449

arthritis.

DR. WOOD: Dr. Shapiro, I missed you, I am

sorry.

MS. SHAPIRO: That\'s okay. I think I

agree with you, and I think it is hard to properly

answer this question unless we ask ourselves why it

is being asked, and if it\'s being asked because the

FDA wants some broad-brush, uniform regulatory

approach to this, what I hear people saying around

the table is that that would not be appropriate for

each and every one of the drugs that are in this

possible class.

But if we are saying that we think that

drugs that are related in composition, structure,

this, that, and the other thing, should raise a red

flag, which is what I think you are saying, that is

what I think we want to say, and I think we are

getting hung up on this class effect definition

because we haven\'t gotten behind and asked why we

are being asked the question.

DR. WOOD: Dr. Furberg.

DR. FURBERG: I think I disagree with

450

Steve Nissen, and I think it is a mistake to focus

on one mechanism of action. Members of a drug

class, they don\'t have to share all mechanisms of

action. In fact, I don\'t know of any drug class

where all the members share all mechanisms of

actions, so the term is more loose and relative.

DR. WOOD: Dr. Shafer.

DR. SHAFER: Actually, I think Dr. Nissen

said that it\'s not all one mechanism. I think that

is exactly your point.

DR. NISSEN: Exactly my point. My point,

Curt, was that these drugs do differ by some of

them have much more of pressor effect than others,

and that seems to be dissociated at least somewhat

from their COX selectivity, and so I want to

characterize the drugs individually, not

necessarily collectively.

DR. SHAFER: Continuing that same line of

argument, Bob, in answer to your question that you

had raised, if there was all the FitzGerald

hypothesis, then, the class effect makes a ton of

sense, because you would say okay, you look at the

451

COX-2 selectivity, we kind of go on the list, and

we do our cutoffs.

We have the blood pressure data. I point

out once again we do have the aspirin data in some

very big trials. The effect should have gone away

in the presence of aspirin particularly I point out

again to the APPROVe trial, the thrombotic risk was

3.25.

We have talked about this on and off, and

you haven\'t been feeling well, so we haven\'t had a

chance to really get together and discuss, at risk

of my health, despite having lunch at Chuck E

Cheese, but I am concerned because we haven\'t

explained the aspirin effect, and aspirin, unlike

the other drugs, doesn\'t go away, it doesn\'t have a

pharmacokinetic component. I mean that should have

clearly made a statement if the aspirin effect had

reversed these prothrombotic effects.

Steve, I think that argues to your point

that there are several mechanisms. One is

certainly in part the FitzGerald hypothesis

although there is partly a class effect, but the

452

aspirin also shows that there is something else

going on.

DR. TEMPLE: Then, how do you characterize

the class? I mean it sounds like most people think

you are characterizing the class as one with a

preference for the COX-2 receptor, for that one,

and if you can\'t do that, it is hard to know how to

go forward.

DR. SHAFER: Can I answer that?

DR. TEMPLE: But I agree with you about

the aspirin, it\'s a fly in the ointment.

DR. SHAFER: It seems to me that you can

look at where we have data that is consistent with

the FitzGerald hypothesis, that is consistent with

it, that you can say these drugs are behaving as in

class, and certainly for the coxibs, as Dr. Fleming

presented the data, it appears that they are all

behaving in a way that is consistent with a class

effect.

Where we don\'t have more specific data

that would say they are behaving in this fashion,

and I would point out these are the COX-2s that we

453

don\'t have data because they are older drugs, but

they appear to be COX-2 selective, I am reluctant

to include those in the class and sort of damn them

because of where they show up on some table. At

the same point in time, I am reluctant just to give

them a get-out-of-jail-free card, if you will.

I think that something needs to be noted

that they are potentially at risk for this effect.

DR. WOOD: Dr. Cush, then Dr. Hennekens.

DR. CUSH: I would support what Steve said

and that I think that we came here with the

spotlight focused on Class II specific agents, but

we become more curious as we have seen all of them

fall, but then seen all the other drugs, the

non-selective drugs also seem to have some of the

same failings, we don\'t want to focus solely upon

the COX-2 specifics, but I think that we can start

there and then extend our concerns to the other

agents, as well.

It doesn\'t have to be, it can be linked to

COX-2, and that may be where we start, but it

obviously needs other investigation to look for a

454

mechanism of action.

DR. WOOD: If Raymond Pickey were here, he

would say show me the data that tells you that

these other drugs have this effect in published

trials.

DR. CUSH: Well, one would be I guess some

of the observational data.

DR. WOOD: Randomized, published

randomized trials.

DR. CUSH: Well, I think the only one we

really have is the Norwegian study.

DR. WOOD: Is that a randomized trial?

DR. CUSH: I believe it was. Well, they

were randomized to\--

DR. WOOD: That showed aspirin also had a

negative effect.

DR. SHAFER: Alastair, that is the reason

the Challenger blew up, the sort of show me it\'s

safe, prove to me it\'s safe or I am not going to

make a statement.

DR. WOOD: That is not the issue at all.

I mean we have got to be careful, I think, rushing

455

ahead of credible data on the basis of rumors of

war that are brought in from outside.

I mean we have got four randomized and

controlled trials for three drugs, and we have got

some news of other drugs, it seems to me, that are

not\--and documented very well. That is not giving

anyone a get-out-of-jail-free card, but I think we

have got to sort of go through this in an orderly

fashion. Otherwise, we will be regulating on rumor

forever, and I think that is a very dangerous step

to take.

DR. TEMPLE: You do have some diclofenac

data i comparison to some of the drugs that are of

interest, so you have some. It\'s not the

placebo-controlled trial you are dreaming of, but

you do have that, and you have naproxen and several

comparisons, as well.

DR. WOOD: And that looks pretty good.

DR. TEMPLE: Naproxen looks good,

ibuprofen looks the same as\--there are, I didn\'t

count them up, three or four control groups of the

older ones scattered around.

DR. FLEMING: Well, we can be specific

because Bob is right, we do have\--I mean basically,

because of all of these other studies that were

456

done for the COX-2 inhibitors, there is a lot of

data on naproxen and a lot of data on diclofenac,

and diclofenac in the etoricoxib trial and in the

CLASS trial more or less came out looking like the

COX-2 inhibitors, while the winner is naproxen.

Basically, in the VIGOR trial, in the

etoricoxib trial, very much in the lumiracoxib

trial, it came out positive. Now, we are going to

hear something tomorrow about the ADAPT, but

looking at these others, it sure looks like

naproxen is a winner, and it does look like the

theory that was put forward that diclofenac is

COX-2-like is at least supported by the trials

where it was studied.

DR. WOOD: Right, but all we can say is

they look the same as another drug where we are not

absolutely certain of the effect of that other

drug.

DR. FLEMING: That is true although we

457

have a lot of other studies on the other drug, and

it is always you have got to be careful when you

say A is better than B, and then B is the same as

C, is C worse than A, but there is that kind of

evidence.

DR. WOOD: Which is what I am concerned

about.

Dr. Hennekens.

DR. HENNEKENS: I would say I am

struggling with trying to gain this clarity, but as

I view the drugs that either have been or are

marketed with regard to cardiovascular risk, the

picture that emerges, begins to emerge to me is

that rofecoxib, ibuprofen, and possibly valdecoxib

are in one bin, diclofenac and celecoxib in another

bin, naproxen in a third bin, and then aspirin in

the fourth bin, going from concerns about hazard to

neutrality to benefit.

DR. WOOD: Other comments? Dr. Farrar.

DR. FARRAR: Two quick\--well, I guess

every time we mention aspirin, it never ends up

being quick\--but two quick comments, one of which

458

is that I am not as concerned about aspirin

knocking out the issue of the COX-1/COX-2 problem

primarily because, in fact, aspirin is a surrogate

marker for people with cardiovascular disease.

If you look at the actual rates in all of

the aspirin groups, they are at least, at least 2

to 3 times the rates in the non-aspirin groups to

start with. So, I think that there is an issue

there.

I think the second issue has to do with

what was just discussed in terms of the comparison

of drugs, and just to emphasize the fact that what

we are talking about is we have data for there

being a risk factor in the placebo-controlled

trials, primarily the best data, which we will have

a whole lot more of in two months or three months,

of the cancer prevention trials to tell us what the

level of risk is.

Then, we have the comparison data that Bob

Temple was just talking about in terms of the

non-selective versus the selective that say that

they have very similar levels of risk.

The third point just to make is that all

of this discussion about risk, I don\'t want to

imply that I think that this risk is big enough to

459

actually warrant the continued hold on all the

trials that we have going, and I think, in fact,

what it suggests to me is that we need to continue

with trials to understand better what the data is

telling us.

DR. SHAFER: May I respond to the aspirin

point? This confusion that you raise came up when

I first raised it, I guess it was just yesterday,

but the risk that we are talking about is not

aspirin versus non-aspirin, because clearly,

aspirin will be a marker for increased risk.

What we are talking about is the risk of

rofecoxib in the case of APPROVe, the risk of

rofecoxib versus the comparator in those patients

taking aspirin, so that the increased risk of

cardiovascular events has been evenly distributed

between the two groups, because that is the blinded

comparator variable.

So, we are talking about the risk of COX-2

460

versus non-COX-2 in those patients on aspirin. It

is different from the risk of aspirin versus

non-aspirin, which as you say is, of course, that

risk is confounded. But in this case, that risk is

evenly distributed between the two groups.

DR. WOOD: Go ahead, Dr. Farrar.

DR. FARRAR: I think the problem is that

what you are saying is that aspirin is somehow only

a COX-1 inhibitor and therefore it has a role there

that somehow should balance the COX-2 or there

should be some other process going on.

There is no question that aspirin and its

indication of increased cardiovascular disease has

an effect on the relationship of the COX problem.

We have seen multiple examples in the

cardiovascular risk, in the group who have the high

cardiovascular risk, there is a different response

to the COX-2 problem than in the lower group, so

there is no question about that.

But I would argue that aspirin is as very

different drug in terms of how it works, in terms

of its binding to the sites, so all I am saying is

461

that I am not sure that that obviates the need to

say that there is an issue there with COX-1/COX-2

that we need to look at more thoroughly.

DR. WOOD: Dr. Manzi.

DR. MANZI: I actually have a problem

making inferences about diclofenac and naproxen in

studies where I think we have a difficult time

feeling comfortable with the results in

relationship to the COX-2s. I mean the trials that

are really driving the signal here are the

placebo-controlled trials of long duration.

So, to feel that we don\'t have enough

information to really feel comfortable with COX-2s,

and then to try and extrapolate to the comparators

in those, I think is dangerous.

DR. WOOD: That is what I was saying, too.

You know, it\'s ten past 5:00, just to draw

everybody\'s attention to that.

John, you are saying that you don\'t

necessarily want a vote on this, is that right?

So, I guess the question is, is there further

discussion on this specific question that the

462

committee feels they can\'t hold until tomorrow?

Tom?

DR. FLEMING: I share the caution in that

last comment, but I will just note that

methodologically, it is the exact problem we run

into or situation we run into in non-inferiority

trial designs, because you have placebo-controlled

trial of agent A, and now you want to look at

whether B is adequately safe, and you are looking

at B against C, the new agent, and if C is the same

as B, that was shown to be non-inferior, or you

knew what its relationship was to no treatment, it

is that non-inferiority issue.

Nevertheless, many of us have concerns

with non-inferiority settings, but that is the

methodologic challenge.

DR. WOOD: That is my concern, as well.

Let\'s move on Question No. 2. We may have

discussed this a lot already, but this really

addresses the contributions and limitations of the

currently available observational studies to the

assessment of cardiovascular risk for the

463

non-selective and COX-2 selective\--and let\'s not

bog down in what we mean by that. In particular,

discuss the role of such observational studies in

informing regulatory decisions about postmarketing

safety issues.

Now, let me ask a clarification question.

Does this mean we just sort of ignore the

randomized trials here or take them as a given, or

how do you want us to handle that?

DR. JENKINS: I think the idea here was to

get your thoughts on how we should consider and

weigh these studies in a mixture where we have some

control trials, we have the observational trials.

Sometimes they don\'t agree with one another.

Sometimes the observational data come at a time

when we don\'t have the control data.

We are trying to get your take on what

weight should we place on these data as we are

trying to make regulatory decisions.

DR. WOOD: So that we could modify the

question to sort of include the randomized trials

and say how do we relatively assess these and weigh

464

them up?

DR. JENKINS: Sure.

DR. WOOD: All right. So, that is a

helpful clarification.

Comments on that question? Yes. Dr.

Stemhagen.

DR. STEMHAGEN: A couple things. I think

I want to make sure that it is understood, in my

view, that they are definitely supplementary to the

randomized clinical trials.

I think we all recognize that the value of

randomized clinical trials is the randomization,

that we don\'t have the selection bias that

certainly takes place in observational studies, but

nevertheless, when we think about the magnitude of

the studies that we have, we have over many

hundreds of thousands of patient years of exposure,

we have in the cohort studies.

In the case-controlled studies we have

more than 25,000 cases. We do have a very rich

data set.

I think we have talked a lot about the

465

fact that we have got a number of studies and we

see a lot of consistency in the results between

those studies. There was an issue of maybe they

are all biased in the same direction.

I think they were conducted in very

different ways, many of them, and many very

different databases. We also see some data on dose

response, which is another suggestion that there is

something going on and that the data should be

believed.

I think if we talk about lost to follow-up

in some of the randomized trials, in some of the

very stable populations that we have in some of the

databases, we actually do have long follow-up,

although ideally, we would like these studies to go

on longer. None of them are really as long as we

would like, and part of that I think is the data

being on the market or available within those

databases at the times that the studies were done.

Another thing that really is different

with these studies is we are not just talking about

volunteers. When we do our clinical trials, we are

466

talking about volunteers. In our databases, we

really have the totality of patients, of cases, of

exposures.

So, I think we have got a somewhat

different groups of patients. The clinical trial

patients are essentially a subset to that. We also

are looking at actual use doses, which are somewhat

different doses perhaps than in a lot of these

clinical trials where we have talked about high

doses are pushing the dose.

So, I think they are different pieces of

information. The endpoints that we are looking for

are very hard endpoints, and I think we have talked

about, and there was some evidence, that in some of

these studies, there are adjudications, the same

way there are in clinical trials when the medical

records are collected.

There have been some validation studies

looking at the ascertainment of MI and feeling that

it is very complete. So, I think we can feel

reassured that in these closed populations, we

probably have identified the cases that we are

467

interested in, and we also have a lot of data, not

necessarily exclusive, on the confounders, and

there have been adjustment for confounders.

So, I really want to urge that when we

look at the data, we don\'t just dismiss the

randomized clinical trials, but they are telling us

something. They do have some patterns, and they do

show some differences between the products.

DR. WOOD: Dr. Cush.

DR. CUSH: I think there is obviously a

value for observational studies, but one thing I

keep hearing is that the FDA is not properly

empowered to mandate that postmarketing trials be

done until maybe a significant issue like this

comes up.

This kind of public health issue sort of

underscores some of the weaknesses of the current

MedWatch system where common events like this are

not going to get reported on new drugs, because

people get heart attacks and heart failure and

uncontrolled hypertension, and I think that one

thing I would like to see come out of this is that

468

Congress and others empower the FDA, so they can do

postmarketing trials that need to be done, either

mandate it or as they need to occur, and if they

can, mandate registries as they need to be done, as

well.

That is certainly right now what I think

is a big hole in our current safety system. We

heard today from the patients, they want to know

that we are going to help them. That mainly means

they want to know that we are going to give them

medicines that are safe.

DR. WOOD: Dr. Bathon.

DR. BATHON: I would like to take the

example of naproxen for a minute where it seems

like from observational studies, it has a neutral

effect on cardiovascular risk, at least that was

the overwhelming notion, whereas, in randomized

trials it seems to be more protective.

I would like to explore for a minute why

that discrepancy, if it is true, why it might be

true. I would like to posit that in the randomized

trials, we have people taking drug every day or at

469

least we think they are taking it, and they are

taking it in the appropriate dose to have

consistent COX-2 or whatever, COX-1 and COX-2

inhibition.

In observational data, those are driven,

NSAID drug use is driven primarily by acute pain

syndromes and osteoarthritis, where people, if we

go to the acute, somebody has back pain for a few

months, a lot of the people using those drugs might

be on them for a few weeks or a few months.

The proportion of patients like the

rheumatoids or the bad OA patients who might be

taking them every day is probably relatively very

small in that group. Even within the OA group, I

think a lot of us probably have OA in here, some of

us who have gray hair or getting gray, even the OA

patients do not take the drug every day on average.

The rheumatoids tend to, the OA patients

don\'t, and then the acute pain syndrome people or

the back pain are more intermittent.

So, I wonder if the difference between

observational data and the clinical trial is driven

470

by the fact that we are looking at very different

treatment regimens, treatment durations, and so

forth. So, I think the randomized trials are more

valuable here than the observational data.

DR. WOOD: Dr. Holmboe.

DR. HOLMBOE: I would just make a couple

of points. If we agree on No. 1 that there

actually is harm, then, I think yes, you are going

to have to do observational studies. I mean it is

going to be hard to randomize somebody to study

harm.

I think that we can take some comfort even

though that the effects are different, that the

observational trials were reasonably consistent

with a lot of the randomized controlled trials that

were presented today.

Second, I think a poor randomized

controlled trial actually may be worse than a good

observational study. As I mentioned earlier, a

number of these studies had over 40 percent dropout

with these patients not being followed, and I think

that that is an opportunity for the FDA to follow

471

these people out to see if there is something

inherently different about those populations who

aren\'t continuing on the study drug.

The third point I would make, that with

regard to meta-analysis, it is very important that

the trials be fairly homogeneous in the way they

were done. In all the stuff reported, I did not

see anybody talk about a test of heterogeneity to

see if they really truly could be combined.

While I understand that because the events

are so low, you are trying to pool risk, there is

some danger in pooling studies that are quite

disparate. So, I think that is something that

needs to be taken into consideration.

The last thing I would say is that I think

there is a real lesson here potentially for the

FDA. The comparator drugs were approved before we

truly understood the biologic mechanism of these

drugs. Our understanding of COX-1 and COX-2

occurred long after the original comparator drugs

were approved.

So, it is a real challenge I think for the

472

FDA to go back and say wait a minute, could these

comparator drugs potentially be a lot like the

drugs that we are now studying, that we think are

being proposed as different, but, in fact, may not.

So, I think that that is real lesson, it has

created a lot of the confusion we are now having to

deal with, because a lot of the comparator drugs it

turns out actually are very similar to the COX-2s

that we are evaluating.

DR. WOOD: Dr. Day.

DR. DAY: Concerning the 40 percent

dropout rate in the randomized trials, we have all

the sponsors here, and they have lots of data and

computers, and so on. Would it be useful to get

the percentage dropout for each of the target drugs

and the comparators and/or placebos in a giant

chart before tomorrow to see, and then try to get a

breakdown of what the reasons were for dropout?

Do they retain that information when a

patient drops out, what the reason is, or is that

on file somewhere?

DR. TEMPLE: They always provide it. The

473

question is how reliable it is. A lot of them say

administrative reasons, and it really requires

people to pursue that question, interview the

patient, and while that is properly done sometimes,

it isn\'t by any means always properly done.

DR. DAY: So, the breakdown isn\'t

possible. What about the percentages for each of

the groups that we have seen just in these studies?

DR. TEMPLE: Pretty much all studies know

how many people stopped and completed and when.

DR. DAY: Do we know? Have we been given

those data?

DR. WOOD: Well, I guess the Kaplan-Meier

curves, and under each Kaplan-Meier curve, I think

there is a number of patients at each point.

DR. D\'AGOSTINO: Part of that was dropout,

but part of that was the way they planned, you

know, follow-up on the individual. The individual

could, for some reason or another, say they are not

going to take the drug anymore, and they only

follow them 14 days, so that was legitimate in the

study. A dropout that just disappears was sort of

474

illegitimate, that was not split up.

DR. WOOD: It is still a dropout, I mean

the person didn\'t complete the study.

DR. D\'AGOSTINO: Well, it followed the

protocol. I mean you can\'t now go back and say they

should have done something.

DR. WOOD: Dr. Paganini.

DR. PAGANINI: One of the things that I

was surprised at here was the lack of information

on the older NSAIDs, and that is one of the things

that we are trying to deal with is what is the

difference.

That then speaks to continued

observational studies in the postmarket venue where

if we had had that, we would have at least had some

sort of observational anchor to put some of the

newer drugs on.

Let me also add that while we always look

at prospective randomized controlled studies as

being the be-all and end-all, there is now an

emerging\--and I will ask some of the biostat folks

to comment on this\--a developing thought process of

475

having a wild arm, the wild arm being what is

usually and customary done when doing something.

For example, if you do a dose of a drug,

or you do an amount of O2 delivery or some sort of

a respiratory issue in the ICUs, frequently, when

you enter into a study which is randomly

controlled, you have one arm versus the other arm,

and they are fixed arms, but there is now a third

arm that people are starting to ask for.

It\'s a wild arm, what do people usually do

outside of the study, and I think that is a very

important issue for when you are using drugs in a

common, out-of-the-box way where everybody is using

the drug. So, postmarketing observational studies

might be considered the wild arm for some

prospective randomized controlled trials in that

same era.

DR. WOOD: Dr. Nissen.

DR. NISSEN: It is interesting. We like

our observational studies when they show us what we

want to see, and we just hate them when they show

us what we don\'t want to see.

I have lived through this with the

estrogen business. I had people tell me that it

was absolutely unethical to do a trial of

476

postmenopausal estrogens because everybody knew

they were beneficial, every observational study had

shown it. So, it is important that we use

observational studies as hypothesis-generating

studies.

If you see a signal in an observational

study, it is an indicator that you need to do a

randomized controlled trial, and that is how we

ought to use them. If we get too far beyond that,

we are going to get into the women\'s health

initiative kind of problem again.

It comes up every generation as another

example of this, where every observational study

tells us one thing until we do a randomized trial,

we find exactly the opposite.

DR. D\'AGOSTINO: I want you to recall that

the Framingham studies said just the opposite, it

was the observational study that didn\'t agree.

DR. NISSEN: Thank you, Ralph, you are

477

usually right.

DR. WOOD: You were down next to speak,

Ralph, is that your question?

DR. D\'AGOSTINO: Oh, is it my turn for my

question?

DR. WOOD: Yes.

DR. D\'AGOSTINO: When we have

placebo-controlled trials, randomized controlled

trials, I mean in some sense it is I think the gold

standard, and when you have positive comparators,

randomized controlled, it\'s the next level, I think

that we have a lot of data that is well developed

in terms of the studies.

We have questions about the dropout, and

so forth, and I raised them also, but I think the

randomized controlled trials have put us in the

situation where we can minimized in some sense the

observational studies.

Yesterday, I made my comment about

torturing the data. We can torture the

observational studies forever and ever, but I think

our weight should shift on the placebo-controlled

478

trials.

DR. WOOD: I agree with that.

Dr. Fleming.

DR. FLEMING: Maybe just to be specific

here about different kinds of observational

studies, there is passive surveillance and active

surveillance. Passive surveillance has been widely

used, for example, in vaccines, childhood vaccines,

and with the Veer system.

Essentially, it worked really well when

you are trying to detect rare events and events

that are proximal to the time of the intervention.

So, introsusception with rotovirus and

encephalitis, and anaphylaxis, et cetera, have been

assessed fairly well.

The problem with those, and we heard

naproxen experiences in what I would call passive

surveillance, the problem is if you have events

that occur with more regular frequency in the

background, it is going to be almost impossible.

There is under-reporting, you don\'t have

denominators.

So, a step up is the large-linked

databases or the active surveillance systems, and I

think this is what a lot of what we have been

479

talking about with these observational studies.

They give us numerators and denominators, they give

us more complete ascertainment, but they still have

unavailability often of confounder information on

aspirin use, smoking, outcome specificity and

sensitivities are less reliable.

We have talked earlier today about how it

is extremely difficult in that context to do a

valid ITT type analysis and have a time zero cohort

and minimize lost to follow-up, and ultimately, you

are not randomizing, and randomizing doesn\'t solve

all problems, but it does, in essence, eliminate

the systematic occurrence of imbalance.

It doesn\'t eliminate randomly occurring

imbalances until you have large numbers, but you

cannot, with covariates, go back and adjust for

what is different in an observational study,

because I always say the known and recorded

covariates are just the tip of the iceberg, so you

480

are left with a great deal of uncertainty about

bias.

Where they are very effective is

understanding natural history, understanding event

rates, understanding covariates, understanding how

people are treated, but we really want to use them

to understand causality, does intervention have an

effect.

Essentially, if it is a very large effect,

you can get some reasonable senses, but in most

cases, I think they serve a very useful purpose,

but it\'s hypothesis generation, it\'s development of

clues.

So, if we look at the overview that David

Graham gave, my sense is he was able to give us

insights about a wide array of issues that we have

not yet got adequate randomized trials, so

specifically, the nonspecific NSAs, what does it

look like there, and issues about dose, but I would

call those hypothesis generation or clues.

I would be very reluctant for the majority

of what we saw from those analyses to take those

481

results as established. It rather gives us a guide

because we can\'t do randomized trials in every

setting. It gives us a guide for how to design

those trials and where the most pressing questions

are.

So, the observational studies go hand in

hand, but the ultimate answers in most cases really

come from the randomized trials.

DR. WOOD: Right, and the estrogen studies

shouldn\'t be forgotten, right?

Dr. Morris.

DR. MORRIS: I think Tom said a lot of

what I wanted to say, but a lot better. In terms

of causality assessment, living through what the

Agency of Healthcare Policy and Research went

through for outcomes, I think the conclusion is

unless you randomize, you are never really sure.

In terms of observational studies, I think

it is interesting that like event rates or

something like that, where we think it is so much

better, yet, I was struck in the discussion today

of some of these drugs is how much the event rates

482

varied by center or study or country.

What isn\'t done in observational studies,

what could be done, is more of a population-based

sampling, so we have a better understanding of how

much or how well that particular database is

representative of the broader population of the

U.S., so we can do some kind of sampling or

extrapolation and get much better event rates,

where I think observational studies can really do a

much better job than clinical trials because they

can measure naturally occurring events much better.

DR. WOOD: Dr. Domanski.

DR. DOMANSKI: You know, one always hates

to admit ignorance, but I want to pursue this

business of a wild arm. I mean I have seen some

pretty wild arms in clinical trials, but never as a

third one.

I don\'t understand where that is, I have

not heard of that one, and I would like to learn

more about it. Can you explain that?

DR. PAGANINI: I will give you an example

of an NIH-VA study that is now ongoing looking at

483

dose of dialysis delivered in which there is a high

dose delivered and then there is a low dose

delivered. Then, there is the thought process of

putting a third arm on there is what is everybody

delivering anyway, so it is whatever the wild type

is, to see if, in fact, people are artificially

placed into one dose versus a second dose, and

that, in and of itself, is an artificial placement

of patients as opposed to what people usually do.

So, therefore, what is the comparison

between one dose versus a second dose versus what

is usually and customarily done.

DR. DOMANSKI: But don\'t you usually use a

registry for that kind of question, that is, how

well does it represent practice I guess?

DR. PAGANINI: It could be retrospective,

but in effect now what they are doing is a

prospective collection of data of what is normally

done in that particular institution when people are

off study.

DR. DOMANSKI: Again, registries can be

prospective, of course. I am having trouble seeing

484

the difference. I mean are those people

randomized, as well?

DR. PAGANINI: No.

DR. DOMANSKI: Okay, so it\'s a registry.

DR. PAGANINI: It\'s just a registry.

DR. WOOD: Dr. Hennekens.

DR. HENNEKENS: I would view the strengths

and limitations of observational studies to be a

function of the effect size. For the moderate to

large effects, we can make safe clinical and policy

decisions based on consistency of the data from the

observational studies.

As the effect sizes get smaller, however,

it\'s a two-fold problem because now the effect

sizes we are seeking are as big as the amount of

uncontrolled and uncontrollable confounding that is

inherent in the designs.

There is a certain seduction from these

large-scale databases because you have a large

number of data you control confounding on, you

could get very robust p values, so you begin to

believe that you have really discovered something,

485

but I agree strongly with Tom that for small to

moderate effects, they are useful to formulate, not

test, hypotheses, so what Dr. Graham told us this

morning are useful to formulate hypotheses.

If people took them as serious evidence

that this indicated harm, he might be right, but it

would have nothing to do with the data that we have

seen. I conclude with the statement, I have the

privilege to know Sir Austin Bradford Hill who, on

this question, and I think Rich would agree with

this, he said, \"Don\'t let the glitter of the tea

table detract from the quality of the fare.\"

DR. WOOD: Dr. Elashoff.

DR. ELASHOFF: Two comments. One, in this

situation, especially when there is very specific

evidence that the relative risk may vary over time,

looking at the standard way that observational

studies lump it all into patient years is bound to

be misleading.

A second point has to do with the fact

that in a randomized trial, when you are comparing

events, the analysis per se tends to be pretty

486

transparent, but in an observational study, in

order to understand it in detail, there are many

covariates, pretty fancy footwork in the

statistical realm, and it may not be very easy to

tell exactly what was done or to think of

reproducing it.

So, the observational study tends to be a

lot less transparent in terms of the way it has

been analyzed.

DR. WOOD: Dr. Friedman.

DR. FRIEDMAN: Two points. One, if I can

follow up a little bit on this wild arm, if you

will. As Dr. Wood knows well, this whole issue

came up, to my dismay, if you will, about a year

ago when we were dealing with the ARDSNet issue,

and I think the general conclusion there was that

it, in general, is not a very good way of answering

a specific question. It might contribute in some

fashion, but in general, it is not all that

helpful.

Second, I am looking at the specific

question here, and it says discuss the role of

487

observational studies in informing regulatory

decisions about postmarketing safety. It seems to

me that one of the things we might do is suggest

ways that the FDA can improve some of the

postmarketing surveillance issues.

For example, we have talked about all of

the difficulties in using observational studies,

and I don\'t disagree at all with any of them, but

if some of them are planned ahead of time, with

good ways of collecting data in consistent ways, we

won\'t completely eliminate all of the problems, but

we can reduce them, and I think we ought to at

least consider that approach.

DR. WOOD: Dr. Platt, last comment on

this.

DR. PLATT: To emphasize that point,

taking everyone\'s thoughtful comments into account,

it seems to me we have to be careful not to let the

best be the enemy of the very good. I think that

Tom Fleming\'s reference to the CDC\'s large databank

for vaccines is quite on point. It seems to me

that there is every reason for FDA to require, as

488

part of the approval process, that there be a

substantial and organized observational set of

studies that give at least a sense that generates

hypotheses that would allow us to recognize the

possibility that there is a signal of events that

never be seen in clinical trials, events on the

order of 1 or 2 or 3 per 1,000.

It is possible to do that with what in the

scheme of these discussions we are having would be

a relative small investment, and we wouldn\'t have

to rely on the occasional observational trial or

the clinical trial that shows up to start a

discussion like this.

It seems to me that that is a very easy,

relatively small step for CDC to take, to have

every manufacturer of a new drug commit to doing a

reasonable observational study.

DR. WOOD: But, Richard, isn\'t that the

problem that Tom highlighted ages ago, that that

sort of registry approach will pick up events that

are relatively rare in the background, like

devastating encephalitis or something like that

489

relatively easily.

But where you have got a background noise

that is as high as MI, it is going to be

extraordinarily difficult to pick that up from that

kind of study.

DR. PLATT: Well, in the vaccine field,

the large-linked database has been extraordinarily

useful for things like febrile seizures after a DPT

immunization, and that is a relatively common

event. So, I don\'t take the point that you can\'t

make reasonable observations about even relatively

common events.

DR. WOOD: Bob, do you agree?

DR. TEMPLE: Well, just to make the same

distinction you were making. You can look for

introsusception or something that basically is very

unusual, but how to find an increase in the rate in

the rate of MIs requires a structured study and a

plan to do it, and you sort of have to have a

hypothesis or you don\'t know what to look for.

It is totally different from liver, you

know, from gross hepatotoxicity, which comes in

490

through the AERS pretty well actually, maybe you

could stimulate those, but it is totally different

when you are looking at a change in something that

has a high background rate.

DR. PLATT: The fact that it\'s challenging

doesn\'t mean that you can\'t learn something useful,

and it is pretty clear from the observational

studies we have that we can learn something useful

about that.

DR. TEMPLE: I was reacting to what you

said, should we have the capacity or have the

ability to get people to do studies once something

emerges or once a question arises, or once you know

something about the drug class, I am not

challenging that at all, that\'s fine, but to have

it in place as a mechanism for sort of

automatically putting stuff up, I guess I don\'t

know what that mechanism is.

There has been talk about encouraging

places to report, and we have an arrangement with

some liver centers, and those things are fine.

Those might be ways to find hepatotoxins maybe

491

faster than we do now, but that still doesn\'t

answer the question of a change in the rate of a

common event, which is a fundamentally different

problem, requires a study, not a report.

DR. PLATT: Well, the model of the

large-linked databases I think gets around the idea

of having to have active reporting. I think that

there is a lot of ability to capture the outcomes

that are of interest.

Obviously, you don\'t look for every

outcome for every drug, but you can make up the

list of things that you care about for certain

classes of drugs, and it is possible to use

automated systems to take you a long part of the

way in understanding whether there is a problem

that needs serious analysis.

DR. TEMPLE: Can I propose an alternative?

I think what you are really saying is the thing you

are worried about with drugs, where there is a high

background rate of something, is always

cardiovascular outcomes.

So, I think what you are saying is you

492

might want to look for any chronically used drug at

cardiovascular outcomes, and that you could

probably put in place.

DR. WOOD: Wait a minute. Are you

suggesting that we insist on a cardiovascular study

for every drug that we get approved? I mean that

would make it prohibitive to approve any drug.

DR. TEMPLE: No, no. We used to fund more

of them than we do now, that\'s a problem that other

people will discuss, and certainly I won\'t, but we

have access to databases, whether it\'s California

Medicaid or whatever, and one can do that.

It doesn\'t seem inconceivable to me\--and I

am talking about something that other people know

more about than I do, so I should probably shut up,

but I won\'t\--I can imagine that a couple of years

into the approval of a drug that is widely used,

you could ask the question at certain sites, can we

see an increase in cardiovascular risk.

I am not sure how many other high

background events it is that are common in the

population that we are really that worried about.

493

Maybe that is something that we could think about.

DR. WOOD: So, if we could just sum up

where we are, what the committee is saying, I

think, is that we are impressed as the primary data

source, and that the primary data source should be

randomized and controlled trials, and observational

studies may be good for hypothesis generation, and

I guess the third point is that the AERS database

is of almost no value in detecting adverse events

that are common in the background in a situation.

Is that sort of fair for what we have sort

of got out of this? Do people disagree with that?

Yes, Dr. Farrar.

DR. FARRAR: There is one specific point

to this question, which is that all of the

non-experimental studies that have been presented

here, I would certainly suggest, and I would hope

people would agree, are hypothesis generating at

best. Every single one of them is confounded by

indication.

The best example is the indomethacin one

where it is only used in people who are sicker than

494

people who aren\'t. So, I think there are clearly

examples. What I was hearing before was a

discussion about what we might do, and I just

wanted to be clear that what we might do is very

different than what we have right now.

DR. WOOD: You put it much better than I

did. That is what I was trying to say.

Yes, Dr. Jenkins.

DR. JENKINS: I found this discussion to

be very interesting because I think you all know

there has been a lot of Monday morning

quarterbacking about what FDA has or has not done

in this class, and a lot of that has been based on

observational study results, many of which fall

into the range of what we have been calling small

to moderate, I think, at best.

I don\'t think we need to revisit that

here, but I think the questions we have going

forward, first of all, we have to look at the data

set we have today, and you have to look at the data

set you have tomorrow on answering the questions

about what do we do now, and observational studies

495

are part of that data set. We have controlled

trials that are part of that data set also.

I think we are also interested in hearing

your thoughts on going forward. I suspect that

this going to be a mining exercise for everyone who

does observational studies in the world probably.

They are going to be looking to do another COX-2 or

another NSAID observational study.

We are going to see more and more studies

published, and as I think someone said, it often

becomes attractive to say, \"Oh, look at that, you

have got a very small p value, yeah, the relative

risk is only 20 or 30 percent or 40 percent, the p

value is very small, the study was very large, FDA,

you should take regulatory action, you should take

this drug off the market, you should restrict its

use, whatever.\"

You are telling us you view them primarily

as hypothesis-generating, and that they should lead

to controlled clinical trials. The reality is even

if we have the authority that we might like to

mandate those trials, it is going to take years to

496

get those controlled clinical trial data, and there

is the pressure between people wanting you to act

based on the observational data versus the

scientific desire to wait until you get better

controlled clinical trials.

I would be interested in having the

committee say a little bit more of your thoughts

about, you know, what do we do in the future in

this class when we get the next observational study

that is touted as wow, this really shows something,

FDA, you should take action.

DR. NISSEN: Can I suggest some courses of

action? One of them is that as people have pointed

out, the strength of the association, I mean the

hazard ratio is really important, and if somebody

comes up with something which suggests 2 or 3, that

is very different from a 1.3.

The other obviously is to have a rigorous

process for looking at the quality of it. One of

the things I have learned from several of you is

that there is observational studies and then there

is observational studies, and some of them are done

497

very well, and some of them are not done so well.

The FDA has the expertise to evaluate

that. Now, the problem is, of course, if it gets

into the political arena, you get a lot of

political pressure, but what we would want you to

do in the public interest is look at the strength

of association, look at the quality of the study,

and make a decision on whether there is enough

there to put a warning out.

We have seen some strange things go on,

like the warning around naproxen, that was clearly

based upon pretty weak evidence. So, I think

having a good standard is where you have to kind of

hold your ground.

DR. WOOD: The other thing, in response to

your question, is if we walk through the scenario

here, the first signal was from a randomized

clinical trial, and the question I guess then is

what would we need to strengthen that observation

because it wasn\'t against placebo and all the

problems there were with it.

It would seem to me that we don\'t need is

498

a bunch of observational trials. That hardly is

going to convince anyone, it seems to me. What we

do need is an appropriately powered randomized

trial that looks at the issue directly, and I am

not so sure how long that would necessarily take.

It only took 2 1/2 thousand people and

approved to get the data. The question to which we

don\'t know the answer, in fairness, is would it

have taken less time if we had done a larger study,

and I don\'t know the answer to that, no one knows

the answer to that, but it is certainly potentially

possible that we could have gotten the data quicker

if we had done a larger study and the effect

appeared faster.

We don\'t know the answer to that, but that

is one approach. I guess, responding to your

question, it certainly seems to be in the public

interest that you should have the power to ensure

that that kind of a study gets done, and that is

something certainly people should hear and hear

loudly, I think.

DR. O\'NEIL: Could I say something

499

relative to a point that Janet Elashoff had brought

up? The general process for the review of

randomized controlled trials, such as the ones we

have been reviewing, is we have the data in, there

has been a strong movement for prospective

specification of events, even blind adjudication,

we look at the protocol very seriously. We

actually have the data in hand. We actually can

re-analyze, regroup, adjust, stratify, do many

things.

We are normally not in a position to do

that on observational studies. We don\'t have the

same level of process review for ran observational

study. In fact, it is not even clear what the

prespecified hypotheses were, even if you wanted to

say the best that the observational study could do

is to generate a hypothesis. However, there are

many of them that have confirmed important things

for us, the last of which was a protocol that we

played a heavy role in, and that was propanolamine

and its association with CVAs.

That was a five- or six-year prospective

500

case-controlled study that was done, that we

reviewed the protocol. We had a heavy hand. In

fact, David had a heavy hand in how that was

designed, and that turned out to essentially

support a regulatory conclusion.

The point I am making here is that if we

do open the door for observational studies, we have

to have a different way of actually having access

to the data, the quality of the data, and give it

the same level of attention that we do in the

review of randomized trials but for the fact that

it\'s not randomized.

Right now that is not in place, so we are

talking about trials being balanced against

observational studies where the standards for the

trials are dramatically higher than the standards

for the observational studies, not that they

couldn\'t be better balanced, but I think that is an

important issue.

There has been a society, ISPE, the

International Society for Pharmaco-Epidemiology has

tried to put good principles in place to sort of

501

say these are how you would do these studies, but

we really don\'t have a process that would require

that along the same ways that we would in these IND

type studies or the larger randomized trials that

we are seeing for the safety.

DR. WOOD: Tom.

DR. FLEMING: Just to reinforce some

comments that Bob was just making, and Larry

Friedman was making earlier, and Steve Nissen, as

well. Not all studies are the same, we know that

is true of randomized trials in terms of their

quality, it is certainly true in observational

studies.

Stuart Pocock more than 20 years ago put

forward criteria for what you would want to do if

you were doing an observational study that would be

as reliable as possible.

Essentially, it is just like a randomized

trial, it is very complicated and takes

considerable effort to ensure that you are putting

in the structures. You can then have the

sensitivity and specificity issues assessed or

502

addressed by independent committees. You can do

your best to try to define time zero cohorts.

You still don\'t have randomization,

though, and ultimately, the level of reliability is

increased, but it still doesn\'t match the

reliability of a randomized trial, as Charlie

Hennekens was saying, until you are persuaded that

the signal exceeds the potential magnitude of the

bias, you can\'t be confident that the result is

reliable.

So often what we are looking at are effect

sizes that aren\'t, in fact, larger than the

magnitude of the bias, so that leads us down the

pathway of needing randomized trials.

John, getting back to your point, if you

have a profoundly low p value, this may be obvious,

but it doesn\'t mean we know the truth. There are

two fundamental aspects around the truth. One is

variability and one is bias, and I can have 100

trials put together and give me a highly precise

estimate. I mentioned yesterday, you just end up

with a precisely biased estimate, and that is my

503

concern in the absence of randomized trials.

I believe these are very useful clues, we

need these results, but just because you have

profoundly low p value doesn\'t mean we got at the

truth.

DR. WOOD: That is what happened with the

estrogen studies, of course.

DR. HOLMBOE: I just want to make one

point because we keep hearing about the estrogen

study. There is one very important fundamental

difference here. Estrogen had been posited to have

a positive effect on cardiovascular mortality in

observational trials, so it made a lot of sense to

use randomized controlled trials to prove that

hypothesis.

The hypothesis here is that COX-2

inhibitors are harmful, therefore, you are doing a

randomized controlled trial that in investigating

harm, not benefit, and I think we have to keep that

in mind.

DR. WOOD: Good point.

Now, we are going to move on, Steve, to

504

the next question. The next question is discuss

the available data regarding the potential benefits

of COX-2 selective nonsteroidals versus

non-selected nonsteroidals, whatever they are, and

how any such benefits should be weighed in

assessing the potential benefits versus the

potential risks of COX-2 selective agents from a

regulatory perspective.

DR. JENKINS: Dr. Wood, could I make a

comment about that as you get started about this

particular discussion point? We put this in here

for a reason, because clearly, we didn\'t want a

three-day meeting to just focus entirely on risk,

because the decisions you need to give us advice on

have to be balancing risk and benefit.

I think here we are particularly

interested in hearing your views about benefit in a

wide range of categories.

You know, this class of drugs was

developed for the GI effect, so we are interested

in hearing your conclusions about the benefit of

these drugs on the GI toxicity, but there is also

505

other areas. Any input you have on their efficacy

for pain relief for the treatment of inflammatory

conditions will be useful.

I am also interested in hearing your

comments about the value of choice. We heard that

from some of the people in the public hearing

today, that, you know, don\'t limit my choices, and

we hear that a lot from physicians, we hear that a

lot from patients, but we often are also hearing a

competing view that if you have got one that looks

like it is safer than the others, then, you don\'t

need the others, but that is at odds with the idea

that people like to have choice, because people

don\'t respond the same to every drug, they may be

allergic to one drug or whatever.

So, in this context of benefit, I would

like you to cover a lot of different areas, and not

just to gastrointestinal benefit, but that is

clearly one of the major focuses of benefit here.

DR. WOOD: Okay. Dr. Nissen.

DR. NISSEN: A couple of things. One is I

haven\'t seen any compelling evidence that in terms

506

of pain relief, that the drugs are actually more

effective, and if such data is available, I would

love to see it, but I don\'t find it there, so I

think that is a little easier for me.

I don\'t think we can minimize the

importance of the GI aspect. There is actually two

things, one of which was talked about interestingly

by the public, but not necessarily by us or the

companies, and that is, you know, patient quality

of life and patient preference.

Any of us, I have certainly taken NSAIDs

and gotten gastritis from them, and it is not fun,

you know, having your stomachache, and people who

have that every day, you know, there is a suffering

related to that, that we heard from the public, and

that has to be taken into account as we think about

these drugs.

In addition, I would be the first to say

that a GI bleed is not a benign event. If these

drugs were drugs that were better for treating

acne, and they caused cardiovascular harm, that

would be one thing, but the events, the GI events

507

here are serious events.

They are not as life-threatening as a

stroke or a heart attack, but they can be, and they

don\'t produce the permanent disability that a

stroke or an MI does. You know, I take care of

people with heart failure, and if you have had a

big MI, and your pump doesn\'t work, your life is

changed, the rest of your life is going to be

different.

Most people with a GI bleed recover, and

so as I weigh these events, I don\'t discount GI

benefits, but I have to give them less credence

than the kind of hard, permanently disabling

effects of MI and stroke, and I also think we

absolutely have to factor in here the sort of

suffering of patients who just don\'t tolerate the

conventional NSAIDs, and I think that compassion

has to come into our decisions.

DR. WOOD: Dr. Fleming.

DR. FLEMING: A great deal of the focus on

the data we have had presented to us relates to the

cardiovascular risks and relates to the confirmed

508

complicated upper GI events, so if I start by

focusing on that, it looks as though in a crude

estimate that we might be having the rate of these

events using the COX-2 inhibitors rather than the

non-selective NSAIDs.

It looks as though that might be, in 1,000

people, preventing 5, 6, 7, 8 events, something on

that order. If we took a relative risk of 1.4 as

the relative risk for the increase in

cardiovascular events, that would be about 4

events.

So, coming back to what Steve is saying,

when you look at it in that context, yes, these

ulcerations are important events, but 7 per 1,000,

how is that up against 4 events that are strokes,

MIs, or cardiovascular deaths, I don\'t think it

adds up.

If that is the whole picture, I would have

a concern, but in a number of settings, it isn\'t

the whole picture. We have heard about the

oncology setting. We have talked about, truly, we

haven\'t talked about efficacy. We have only had a

509

number of comments stated that the pain relief

seems to be about the same.

Well, if it is the same, then that balance

that I was saying concerns me as not being a

favorable balance, but we heard a lot of people

testifying, and I will be the first to say open

sessions at these meetings are not random samples

of the entire public, but we still heard a lot of

comments that reflected the fact that there seems

to be some differential protection or pain relief

in certain patients.

Can we quantitate that? Can we, in fact,

more scientifically, rigorously establish certain

subpopulations where there really is a differential

relief? Then, the benefit to risk shifts, or in

the oncology setting, the benefit to risk shifts.

The bottom line here, though, is to me the

issue isn\'t so simple as choices. The issue is

informed choices, and it takes the kind of

scientific studies to reliably identify what are

the true benefits and risks, so that patients are

in a position to make an informed choice, and part

510

of the challenge to this, as one of the speakers at

the public session pointed out, is it is not always

the case that what might be learned by those people

doing the studies is being effectively transmitted

to the bedside or to the patients and their

caregivers, and that is the other aspect, as well.

So, it is critical to follow a strategy

here that allows us to reliably address benefit to

risk and allow patients to make an informed choice.

DR. WOOD: Dr. Hoffman.

DR. HOFFMAN: I think for the last two

days we have been hearing appropriate angst about

damning a class of agents for which there is a

measure of efficacy, both in regards to pain and GI

events because of newly-discovered adverse events,

but I feel like we are walking on eggs in trying to

get away from a consistent observation that is the

dose-response effects, relative risks that we are

looking at in terms of cardiovascular endpoints.

We have heard this from experts at the

FDA, independent investigators. We have even heard

it from the thought leaders of industry, there

511

seems to be a consensus to the effect that there is

a class effect.

I do take Steve Abramson\'s point that all

of these drugs are not pure in their effects in

terms of COX-1 or COX-2, but this is the data that

we have, and it seems like there is a consensus

about a class effect, and there also is a consensus

in acknowledging that the patients that we enter

into randomized controlled studies are probably the

people least at risk that we may not see in our

practices, who come in with 3 or 4 comorbidities

that may have excluded them from being in this

trial and actually having seen even a clear signal.

The data, of course, that we would like to

have is something that we don\'t have, and that is,

the old standards of treatment for pain, whether

it\'s the arthritis pain of OA/RA or postoperative

pain, with NSAIDs plus PPIs over a long, extended

period of time.

We would all like to know the data for

that over 2 or 3 years compared to the COX-2s,

which I don\'t think any of us are saying should, as

512

a class, be taken off the market, but certainly

should be used at the lowest safest dose.

Now, at the lowest safest dose we don\'t

even know their efficacy qualities. We don\'t know

whether at the lowest safest dose we have the same

benefits in terms of preventing peptic ulcer

disease, treating pain effectively, decreasing

inflammation effectively, and that it seems is the

data that we need to have.

I am a little concerned, as a footnote to

that, about the issue of choice. I think it is our

obligation to provide patients choice within the

realm of relatively safe medications, but most of

us would not give as a choice a narcotic analgesic

to a patient with, say, fibromyalgia.

I don\'t think we should keep drugs on the

market because of public pressure if we have a

signal that we feel is a very strong one. We

shouldn\'t give people a choice if we think that

choice is uninformed and potentially does harm.

Now, I am not saying that for the class of

COX-2 inhibitors, I am just saying that we need

513

more data to be able to provide for ourselves

adequate information to make that choice and give

our patients informed choice.

DR. WOOD: Dr. Cryer.

DR. CRYER: We were asked to kind more

widely consider the potential benefits. As I see

it clearly, one of the benefits is GI, and I will

comment on it, but I do want to reiterate some of

the comments that I personally don\'t see the

benefit with respect to efficacy.

I think the clinical trial experience to

date has pretty consistently indicated that the

efficacy is similar to the traditional NSAIDs. We

did see some provocative data with etoricoxib today

suggesting greater efficacy in one trial than

naproxen, but that wasn\'t replicated.

So, overall, I have to think that the

efficacy is the same as we have with the

traditional NSAIDs. I appreciated the testimonials

of the patients about their individual efficacy

responses, but my conclusion about that is those

are anecdotes and it is consistent with the

514

clinical experience that we have with efficacy of

NSAIDs, which is that there is variable and

idiosyncratic, unpredictable responses between

patients, and it is very common that you will have

one patient who responds to one NSAID and does not

respond to another.

I do think that we would still be giving

these patients a wide range of choices given that

there are 20 other NSAIDs available in the U.S.

among which they can choose.

The benefits clearly I think are in the GI

tract, but I will say that my conclusion is that

the GI benefits are less than previously

speculated.

If you look at the three outcome trials

which we have, that looked at GI benefits, we have

VIGOR, CLASS, and TARGET. The results in the VIGOR

are clear, but I think that was clearly also of a

manifestation of the comparator, and one of the

things that I would like to be remembered is that

the comparator NSAID matters.

One sees a greater degree of GI benefit

515

when one compares against naproxen than when one

compares against diclofenac, so I do think there is

value from the CLASS trial. I know that there was

a GI benefit shown against ibuprofen.

In the TARGET trial, those GI estimates

are overestimated primarily because they enroll a

low risk group of individuals and in a lower risk.

We have consistently seen in trials that when you

have low risk GI group, the relative risk is higher

although the absolute risk in a low risk population

is very low.

So, the benefit is going to depend on the

comparator. It is probably less than the 50

percent that you suggested it to be, because that

50 percent is based upon the VIGOR trial. It is

probably closer to maybe a 30 percent benefit that

I would estimate.

It also narrows when you consider low dose

aspirin. In the face of low-dose aspirin, there is

no apparent GI benefit. So, I think we also need

to modify our estimates based upon the population

that would be using or not using low-dose aspirin.

So, my conclusion about the GI events is

that, yes, there is a benefit, it is not as large

as we thought, the appropriate target population is

516

smaller with respect to the target group. It could

be low risk people not taking low dose aspirin, but

this event doesn\'t happen very commonly in low

risk, and when you look at the high risk people in

whom these drugs were originally targeted, several

data sets suggest that the high risk people do not,

in fact, have any appreciable benefit of GI risk

reduction from a COX-2 specific inhibitor.

Final comments about other areas of

benefit. Dyspepsia isn\'t one that is very

convincing. When you look at the dyspepsia data

from the clinical trial experience, it is only a

few percentage points reduced. Dyspepsia, I

consider mostly a nuisance symptom for which we

have other very safe therapies to effectively deal

with this.

Finally, from the GI perspective, the

polyp story could be another potential benefit, but

with regard to the polyps, we have to remember in

517

every trial we have seen, we are only modestly

reducing the polyps and ultimately, we don\'t reduce

cancer risk unless we eliminate adenomatous polyps,

so it doesn\'t really change our algorithm in terms

of how we would manage these patients, which would

be colonoscopy and polypectomy.

DR. WOOD: Before you finish that, there

are only two drugs on the U.S. market now,

celecoxib and valdecoxib, so let\'s review the upper

GI safety for them first.

Is there a study that you are aware of

with valdecoxib looking at complicated ulcers that

showed in randomized fashion that there was a

safety signal?

DR. CRYER: No. Wait, what do you mean by

safety signal?

DR. WOOD: GI benefit. Is there a VIGOR

trial for valdecoxib?

DR. CRYER: No.

DR. WOOD: So, confining our discussion to

the two drugs that are on the U.S. market, there is

no VIGOR equivalent, if you will, in valdecoxib,

518

right?

DR. CRYER: Correct.

DR. WOOD: Now, for the other drug that is

on the U.S. market, celecoxib, the published study

didn\'t show the full data set. For the full data

set for that, there wasn\'t benefit either.

DR. CRYER: Correct, but we did have the

benefit of\--

DR. WOOD: I understand, but there is

always a benefit\--I mean there is mortality

problems halfway through, too, that disappear, that

we ignore when we get to the end of the trial.

So, for the two drugs that are on the U.S.

market now, we have no clear randomized data that

show GI benefit given the endpoints that were

predefined and the end of the trial, not the trial

that was published without the complete data set.

The TARGET trial looks at a drug that is

not on the U.S. market. So, our job is to evaluate

the two drugs that are on the U.S. market, it seems

to me.

DR. CRYER: So, I agree with your comments

519

about the fully published results in JAMA for the

class, however, we did have the benefit of

reviewing the full class results in the FDA hearing

four years ago, and it is based upon that

evaluation that I am deriving my conclusions of the

full data set in which there did appear to be a

demonstrable GI benefit when compare to ibuprofen

in people who were not taking aspirin, certainly

not when compared to diclofenac.

DR. WOOD: But the trial was not\--that was

a subsequent analysis taking out the aspirin. That

wasn\'t the predefined endpoint.

DR. CRYER: Point well taken.

DR. WOOD: So, I mean just summarizing the

point again, we have a benefit in a trial for a

drug that is not on the U.S market, but we are not

prepared to extend a class effect to cardiovascular

risk necessarily, so I don\'t think we can just sort

of step back and say that we are going to give a

class benefit to GI benefit either extrapolating

from studies of drugs that are not on the U.S.

market.

DR. CRYER: Just because they are not on

the U.S. market does not reduce the validity of the

observation, for example, with lumiracoxib, and

520

just because this was not absolutely predefined,

and the benefit was recognized in, let\'s say, a

post-hoc perspective, I still think there is

recognized benefit in the data that we see in terms

of assessing the GI benefits of celecoxib versus

ibuprofen, and lumiracoxib versus its comparators.

DR. WOOD: But the non-aspirin group also

had a cardiovascular risk, right?

DR. CRYER: Absolutely.

DR. WOOD: I mean as we are doing Tom\'s

sort of analysis, when we take out that aspirin

group and say, wow, there is a GI benefit there,

when we take out that aspirin group we find there

is a cardiovascular risk. So, you know, we can\'t

have it both ways.

DR. CRYER: Well, I would say that the

cardiovascular risks extend to both groups, aspirin

and non-aspirin.

DR. WOOD: Right, but it was clear

521

in\--okay, Dr. Fleming.

DR. FLEMING: Just to pursue a bit

further, Alastair, what Byron is saying, there are

two aspects that I hear you saying that are really

critical to the comments that I had made earlier.

One is that I might be overestimating the

actual GI benefit when I say you are having maybe

it\'s a 30 percent.

DR. CRYER: It depends on the comparator.

DR. FLEMING: But the other, even more

important thing to me that you are saying is that

in spite of what might appear in the open session,

which we know is anecdotal, the scientific data you

are saying repeatedly are showing in the RA, OA,

CABG settings where we have done studies, that

there is not a difference in the pain relief and

the efficacy.

I would like to get more sense about that.

If that is even close to true, then, there should

be an incredibly low threshold for what you would

accept in additional cardiovascular events, because

the only thing you are getting relative to

522

nonspecific NSAIDs then would be a very small GI.

So, it seems like the efficacy here about

the pain relief is a key issue.

DR. WOOD: I think the company wants to

say something.

DR. KIM: Mr. Chairman, if I could, I will

just make a comment, please. As I said yesterday,

at the time that Merck withdrew Vioxx from the

market, we based that decision on the available

data that was available to us at that time, and we

also stated that we thought that it would be

possible to continue to market Vioxx with a

labeling change that incorporated the results of

the APPROVe trial.

But we decided and we concluded that the

most responsible course of action to take, given

the information that we had at that time, and the

availability of alternative therapies, was to

voluntarily withdraw the drug from the market.

We have heard over the past two days new

data and we have seen in the New England Journal

new data on some of these alternative therapies.

523

Merck\'s interpretation, as you have heard, of these

data are that we are dealing with a class effect,

and the major question on the table right now is

how large is that class.

We are a data-driven company. If this

committee and the FDA agree that what we are

dealing with here is a class effect, then, I think

it would be important for us to take the

implications of that conclusion into consideration

with regard to Vioxx, particularly given the unique

benefits that Vioxx provides, one of which you are

alluding to.

So, I just wanted to make that point.

DR. WOOD: So, just to understand, what

you are saying is that if we think the

cardiovascular effect is a class effect, you would

consider putting Vioxx back on the market.

DR. KIM: What I am saying is that at the

time we withdrew the drug from the market, we did

so because of the availability of alternative

therapies and the science that was available at the

time. That science has progressed. We are now

524

engaged in a discussion around that science.

There are unique benefits to Vioxx, one of

which is it is the only COX-2 inhibitor with proven

reductions in gastrointestinal events, another one

of which it is the only coxib which is not

contraindicated for patients with allergies to

sulfonamides, and the third is that we have heard

numerous reports, and you have heard a few today,

from patients, including patients with chronic

debilitating pain that Vioxx was the only drug that

relieved that pain.

DR. WOOD: Okay, good.

Dr. Farrar.

DR. FARRAR: I wonder if I could just be

very clear that so far I don\'t think we have talked

about benefits. The point I want to make is that

what we are talking about with the GI, quote

\"benefit\" is, in fact, a reduction of risk. No one

that I know of takes coxibs of any kind for an

upset stomach.

I think what we need to do is focus on the

benefit to the patients, and we heard some of that

525

in the public forum today, and I want to be as

clear as possible about the issue of that benefit.

There are two ways of measuring benefit,

and, in fact, in outcome trials, there really are

only two summary statistics that are possible. One

is a mean or a median or some central tendency with

a spread, standard deviation.

The second is a proportion, and it is a

proportion of responders, it a proportion of people

who die, which is the easiest, and in pain

management, we get into all kinds of arguments

about how much improvement you have to have to be a

responder.

If you look at the data, we are used in

most of our clinical trials to looking at means and

standard deviations, and if you look at means and

standard deviations, it is very hard to find a

difference between any of the NSAIDs and

acetaminophen, any of them.

If you ask patients about what works for

them, in clinical practice, every patient will tell

you that one works and that one doesn\'t. \"I get

526

sick with that one, I don\'t get sick with the other

one.\"

That is not something that we measure

typically in our clinical trials. If you look at

what level of drug is effective, with almost any

NSAID, it is never, it is never above 50 percent in

terms of patients who actually go on using the drug

in a chronic process.

What we are talking about is trying to

identify less than 50 percent of a population who

respond to a drug, and I can tell you from clinical

practice, as any of you who have taken patients

with rheumatoid arthritis know, people like

specific drugs because they don\'t cause side

effects and because they do have an effect.

I think choice actually is a very

important issue. Granted, we don\'t want to provide

choice if there is an absolutely huge risk

associated with that choice, but I think it is

really important to understand that pain kills in

the same way that the drug potentially can kill.

I think it is very important to understand

527

those two principles, the principles of the

difference between a proportion and a mean value.

Now, I am obviously talking to the converted here,

but I think the issue really is looking at those

issues.

We don\'t have any good trials, any that

look at switching behavior within our patient

populations, so there is no data that I know of

that will help inform us about the need to and

exactly how to go about this process, but I do know

that in spite of all of our understanding of what

goes on with the COX-1/COX-2 pathways and the

inflammatory pathway, that when it gets down to

using it in the patient, the issue is, is it

absorbed, does it cause local effects, does it get

to the active site, once it\'s at the active site,

are there enough receptors for it to then cause the

effect that we are looking for, a whole host of

factors that we really can\'t measure and haven\'t

measured yet in terms of metabolic process.

My honest sense from the data that we have

heard here is that the drugs that we are

528

considering today, the two, perhaps three, has to

do with the relative benefit of those drugs.

What is very clear is that there are

people, and a large portion of people, who have

trouble with the current list of what we call

non-selective COX inhibitors, and that there is a

very important role for the more selective COX-2

group, however we want to define that.

I think it is also, however, very

important to understand that not everybody should

be on a COX-2 predominant agent, and one of the

problems that we are struggling with right now is

the fact that because they were marketed as being

safer, there was a very large push to switch people

over who may not have needed to be switched.

So, I think that the issues that we need

to consider are there is very good data that these

drugs are effective at least in some segment of the

patients in whom they are tried.

There is I think reasonable data to

suggest that the potential risks is not clearly

very different between them, at least not the data

529

that we have to date, and that from that

perspective it is going to be important that we

carefully think about how we then go about

controlling those drugs.

I would end with just saying that I agree

absolutely it is about informed choice, and that I

think that there needs to be a fairly large amount

of information in the label and information

conveyed to patients and physicians to help them

make those choices.

DR. WOOD: Dr. Gibofsky.

DR. GIBOFSKY: I am particularly pleased

about the nature of the conversation because as a

student of medical history, it reminds me that the

first treatment we had for arthritis was, of

course, willow bark, and we told our patients to

ingest willow bark in order to get salicylates,

which, of course, have an anti-inflammatory effect.

So, if only our patients could take aspirin,

perhaps we wouldn\'t need the whole class of

non-selective and selective COX-2s, but, of course,

they can\'t. There are problems just with aspirin

530

in the treatment of arthritis at the doses they

need it.

I am intrigued by the comments that, well,

you know, an MI is an MI and you are dead, but a GI

bleed, you get up, you get over it with no long

lasting effect, and that may be true for the people

who survive, but as Dr. Cryer showed us yesterday,

and the best data set we have from Dr. Singh, 16

percent of patients who have a GI bleed die, so for

them, it\'s a fatal event and one that they are not

going to get up and continue on.

I don\'t want to get into a discussion of

the GI benefit and whether, in fact, it was

achieved with one agent versus another, but what is

clear is something that hasn\'t been remarked yet,

and that is for patients going to surgery, who are

going to require anticoagulation following their

surgery, and that is particularly in large part

patients who have arthritis and are undergoing

joint replacement surgery, the risk of a

traditional nonsteroidal with an anticoagulant

appears to be far worse in terms of bleeding later

531

on than the risk of being on a COX-2 because of the

lack of platelet inhibition.

So, certainly there is a benefit for

patients in that group who are going to go to

surgery and require concurrent anticoagulant.

With regard to the issue of patient

choice, there is several sets of data\--and we heard

one\--showing that when you give a patient two

different medications, in one study, the ACDA

study, looked at acetaminophen versus diclofenac,

another one, the PACES study, looked at celecoxib

versus acetaminophen, and you asked patients

without knowing which drug they were getting, in

which arm, patients expressed a preference for

either diclofenac or celecoxib over acetaminophen

in the treatment of their arthritis.

The other issue with regard to choice is

that we have also recognized, even in the pre-COX-2

days, that not infrequently, patients develop what

is called a tolerance to the agent that they were

on, that the latest data set we had suggested that

inside of 18 months, patient who were taking

532

medication for their arthritis chronically had to

be rotated among agents three to four times in that

period of time.

So, the necessity for multiple agents in

our armamentarium, the necessity for agents that

allows for this individual idiosyncrasy that we

have heard of is quite important.

As was alluded to, there can be two

patients in the waiting room on the same drug, one

will swear by it, one will swear at it, and so it

is for that reason that we need to have, not just

one agent in a class, whatever we define that class

to be, but sometimes several. Sometimes they are

agents of allergy or idiosyncrasy which necessitate

having more than one agent available.

I think it is for all those reasons that

we have to consider that in the benefit part as

long as we are discussing benefit in the last part

of the day.

DR. WOOD: I think we have to be really

careful accepting this data, this 15-year-old data

from Dr. Freis. I mean he has published, he

533

published multiple updates on that, and people keep

showing that same data, and that data isn\'t what is

in his latest revision.

DR. GIBOFSKY: Accepted. Dr. Cryer?

DR. CRYER: I would like to comment on

that, and I think your point is well taken. While

I showed the 16,500 data yesterday, at the same

time I said that that estimate, based upon more

recent evaluations, is probably an overstatement of

the actual mortality risk, GI risk attributable to

NSAIDs.

Dr. Singh has showed me more recent data

which he has conducted in the U.S., which has shown

that the risk has dramatically decreased in the

U.S. That is probably related to several factors

included in which is the eradication of HP, the

introduction of PPIs into the U.S. marketplace, as

well as the introduction of COX-2 specific

inhibitors.

The most recent estimates that I have seen

would suggest that the mortality is about half of

what Dr. Singh previously suggested it to be.

DR. GIBOFSKY: Accepted, but even the

mortality rate of 8 percent in a population is

unacceptable.

534

DR. CRYER: It is not 8 percent, it would

be 8,000.

DR. WOOD: It is much lower than that, and

if you look at the curve, the fall occurred long

before COX-2s were on the market.

DR. CRYER: You are correct.

DR. WOOD: The data are out to 2000 on his

paper, and that fall had occurred by 1998, so that

is before any of these drugs were on the market.

My point is that we keep throwing this

100,000 number around, including from the industry

people, when the data is 15 years old, and the

author has updated it multiple times, and that is

not reasonable, guys.

Dr. Singh.

DR. SINGH: As the author of the papers

that you are discussing\--

DR. WOOD: I am talking about Dr. Freis\'s

paper, which was actually published. Yours is an

535

abstract, I think.

DR. SINGH: Also, the 16,500 was from my

paper that we estimated with the Aramis data set,

and that, you are right, it is not 15 years old,

but that is about \'94, \'95 data, and now that we

have newer data sets, that was an estimate from the

Aramis data.

The latest work now is actually on real

hospitalizations based on the nationwide inpatient

sample, which is a much better estimate of what is

really happening than an estimate from a small

patient population.

When we go back and look in \'93, \'94, of

what the total number of deaths that the Federal

Government said occurred in the United States, we

were off by 32, that\'s it. It was like 16,486.

That is how far we were off by, just to let you

know in terms of an estimate.

This is also true that now, today, the

latest data set that we have available from 2002,

that has dropped significantly, and the death rates

are more like 8,000.

But the other place where we

underestimated was the hospitalizations. We

underestimated the hospitalizations, they are not

536

108,000, there are a lot more than that.

The mortality rates today have gone down

tremendously, and the mortality rates today are

probably more in the 5 to 6 percent range, and that

is where Byron is correct, as well.

Then, as far as the trend is concerned,

the data that I showed you today is based on 483

million hospitalizations. We are not counting

about 50 hospitalizations and then extrapolating it

to the country. There are 483 million

hospitalizations and 3.68 billion patient years.

Yes, the trend line started going down way

before the COX-2s were introduced, but then there

are two sharp years of decline. The trend line

actually, if you look at my slide, is very

interestingly correlated with PPI use, and I showed

data to Byron from the same data set, that it also

explains it very nicely because the duodenal ulcer

rates have gone steadily downward, which would be

537

attributed primarily to PPI use and H. pylori

eradication therapy.

The gastric ulcer rates and the gastric

ulcer hemorrhage rate have not gone down in the

same fashion. They went down when the \'94-\'95 H.

pylori eradication campaign started. Then, they

plateaued off pretty much, and PPIs haven\'t done

very much to gastric ulcers until 1999, when the

gastric ulcer rate dropped dramatically.

In 1999, there is a 22 percent drop per

100,000 prescriptions sold in this country. I

don\'t know what it is because of. Coincidentally,

in 1999, January 1, celecoxib was introduced. I

don\'t know what it is because of.

DR. WOOD: Let\'s move on.

Dr. Dworkin.

DR. DWORKIN: Much of what I wanted to say

has already been said, but I just want to emphasize

that while there are no differences on average in

pain relief amongst these drugs, certainly none

that are replicated, as Byron pointed out, that

there is a great deal of variability in response,

538

and I think there is every reason to believe that

some patients respond better to one drug than

another, so you have variability in the pain

benefit, and you have to consider at the same time

there is variability in the tolerability of the

drug.

So, there are two sources of variability

in patient response, which at least to my way of

thinking provides a really solid basis for there

needing to be a choice amongst several drugs,

because you have the variability in the pain

benefit amongst patients and the variability in

their tolerability.

DR. WOOD: Dr. Cush.

DR. CUSH: I prefer to say that these

drugs are equally potent between the COX-2 specific

and the non-selective drugs. I think there is a

variability, but that speaks to the need for

choice.

Every rheumatologist at this table will

tell you they cannot manage in any effective or

compassionate way osteoarthritis or rheumatoid

539

arthritis using just Tylenol and aspirin and

ibuprofen. That would be a gigantic step

backwards.

So, they are equally potent. I think when

it comes, however, to the risk, thankfully, this

risk is incredibly low, but we would like to make

it lower, and what we need to put forward is that

we need a strategy for risk modification that is

going to extend to all these drugs that we are

examining here, much in the same that occurred with

GGI, I think that we can start with some

recommendations and then make it the responsibility

of the manufacturers to come up with studies that

will further define how we can best reduce the risk

in people who may need to receive these medicines.

DR. WOOD: Dr. Morris.

DR. MORRIS: Let me focus on the question

that asks about the weighting, because what we have

is\--I guess everybody interprets this question

differently, but what I interpret it as is how do

you look at these non-comparable outcomes and how

you trade off a TIA from a gastric ulcer or

540

something.

I think what we can do is we can describe

the effect and we can describe the probability of

the effect, but what we don\'t know is what is the

right way to weigh those things, and I would make a

plea that probably the right way is to try to

involve in some way the views of patients in that

decisionmaking.

I don\'t mean that qualitatively, I mean

that quantitatively, is in quality of life type

data where people have looked at various outcomes,

looked at it on a single scale, and apply some of

those ways, so we understand how patients view it,

and go beyond just medically what we think patients

should evaluate it, but how they actually do

evaluate it, and try to use some of the input of

those data.

That literature suggests that we get it

wrong, that there is things worse than death, and

we always think of death as the worst thing to

happen in a medical outcome, but yet from a

patient\'s perspective, being paralyzed by a stroke

541

is perceived as worse, and we need to understand

patients\' evaluation of these outcomes, so we can

make those weightings better for them.

DR. WOOD: Ms. Malone.

MS. MALONE: Obviously, this is

complicated. I agree with most of what the

previous speakers have said especially Dr. Cush,

Dr. Gibofsky.

A big problem is like Dr. Gibofsky had

said about having choice and trying different

drugs, and having a period of time when they would

work, and then they wouldn\'t be as effective and

you would have to try something else.

That is why the need for choice is there.

I have spent the last 35 years probably on each of

the NSAIDs that are still available, and went

through that, and the frustration and the pain, and

just\--it\'s very difficult, so when people give this

anecdotal information and say that they have found

something that works for them, they are going to

fight for that.

We have to be able to prove to them that

542

the risk far exceeds the benefit, and we have to be

able to show that, and we can decry anecdotal

evidence as not being sufficient enough, but, in

reality, it all comes down to anecdotal evidence.

It all comes down to the personalization of it,

what happens to me when I take this drug, what

happens to me when this drug is not available.

But I think behind everything is the whole

element of trust, and they place their trust in us,

in FDA, and we can\'t give in to pressure, okay, but

we can\'t give in to pressure either way. We have

to keep an open mind about it and realize what they

are going through and try to put yourselves in

their shoes.

DR. WOOD: Dr. Platt.

DR. PLATT: In the spirit of supporting

informed choice, it seems to me we could do a very

much better job than we do by using the existing

data that FDA already has to provide good

information to patients about the risk stratum that

they inhabit.

Saying that there is an overall 1 1/2 or 2

543

percent difference in the risk of a GI complication

or myocardial infarction is not doing the best

service to most people who take those drugs.

I would imagine that those data can be

used to support predictive modeling that would

allow a fair amount of discrimination so that

individuals could be told that people like them can

expect a risk of 1 in 1,000 or 1 in 100 or 10 in

100, and that would make it a lot easier, I think,

for individuals and their doctors to make

thoughtful decisions about the tradeoffs of the

benefits and the risks.

It seems to me those data are there and it

would be a straightforward thing to make them

available. We do that with breast cancer all the

time. The NIH did a tremendous service I think to

the public by providing good predictive models that

let women know what their risk of breast cancer is

to help them decide whether to take preventive

action. I think we could do it with these drugs.

DR. WOOD: Dr. Bathon.

DR. BATHON: It is interesting that you

544

would say that because that is, in fact, what most

of us rheumatologists have been doing for the past

four months with every single clinic visit, is

weighing the benefits and the risks based on the

data that exist right now, and it is a difficult

endeavor.

I think that we are really hearing from

our patients, and we heard this today, we are in a

different era of patient-doctor relationships, and

patients want to be a collaborator in these

decisions, and they want to know the information.

I think that the way I am thinking about

this problem right now is that these drugs, whether

they are selective or non-selective, are another

risk factor in the GI complications and the

cardiovascular complications that we have to weigh

along with their blood pressures, their diabetes

status, their BMIs, their family history, and

everything else to come to a final decision about

what we recommend with their input.

Until we see an unequivocal cardiovascular

risk that outweighs all those other factors, I

545

think that is the appropriate approach with the

patient is to put the drug in with all the other

risk factors and try to come up with the best

benefit-risk ratio that exists for that individual.

DR. WOOD: Dr. Hennekens.

DR. HENNEKENS: I find Question 3

extremely complicated in a number of dimensions. I

am attracted to Tom\'s formulation of benefit to

risk, but I think we also have to consider these

arthritis patients with regard to the use of

selective coxibs.

As a group, they are at maybe a double the

risk of heart disease of their non-arthritis

counterparts. They are also suffering terribly

with pain.

From that perspective, the data we saw

over the last two days on naproxen was somewhat

reassuring to me, but for the patient who has

gastroesophageal reflux disease or an allergy to

aspirin or non-selective NSAIDs, I think there the

benefit-to-risk obviously shift although even here,

I think they have to have their cardiovascular risk

546

factors managed aggressively, and I would add three

more dimensions.

One is I am not reassured at all by the

data that are available on the short-acting

non-selective NSAIDs with regard to risks and

benefits, and I think we need a lot more data

there.

I am also not reassured by data we haven\'t

reviewed that acetaminophen is either sufficiently

efficacious or much safer, and then finally, the

problems with high doses of aspirin are real.

I do point out, though, the UK TIA trial

of 2,400 people that gave aspirin 1,200 mg in a

placebo-controlled design for 5 years, the rate of

GI side effects attributable to the aspirin was 14

percent, significant bleeding was 3.3 percent, but

this flies in the face that 25 percent of the

people on placebo had GI side effects and 1.6

percent of them had a significant GI bleed, so I

think nothing is straightforward here.

DR. WOOD: Dr. Nissen.

DR. NISSEN: Just one brief comment, and

547

that is, one of the things I am struggling with for

all of you, and maybe some of those that either

deal with these diseases can help me with this, is

that the people at greatest risk for GI bleeding

are the older and more frail individuals who are

also at the greatest risk for cardiovascular

disease, and so finding the sweet spot for the

drugs becomes a little bit harder.

There obviously are certain populations

where it is obvious, but the big populations where

there is risk, is it not true\--I think I heard from

Byron that older people are at greater risk for GI

bleeding, and I can assure you they are at greater

risk for coronary disease, so the question is how

does it tilt in any given patient. It is not so

easy to figure it out.

DR. PLATT: But you can quantitate it. I

mean it seems to me you could tell the patients

what individually, approximately what they could

expect on both dimensions, and for a lot of

patients, they would be high on both, but at least

they could make an informed decision about that.

DR. CUSH: But it\'s the same situation as

the GI problem. We know what the risk factors are,

and age is a risk factor, and we counsel patients,

548

and we probably should tell the ones who might be

willing to accept some small risk, because they

don\'t seem like they are at risk just because of

their age, but they don\'t have any other factors,

and the same thing can happen here with regard to

the cardiovascular risk if we have some appropriate

guidelines.

DR. CRYER: Steve Nissen, I think you have

got it exactly right and that there seems to be a

great degree of overlap in those who are at GI risk

tend to be, not uncommonly, the same patients who

are cardiac risk. They are older, they may have a

previous history of cardiovascular disease, and

other risk factors which are common to both risk

considerations, GI, and cardiovascular.

DR. WOOD: Ms. Malone, do you want to say

something?

MS. MALONE: Yes, I do. Just what Byron

has said, all of that brings in the importance of

549

the doctor-patient relationship, and today, with

the health care climate that we have, I have heard

patients say how difficult it is to go in and get

an amount of time when you can talk to your doctor,

have a relationship with him, and especially, as

people become older, and where I live in South

Florida, there are many elderly people who do not

have family around, so they are going to their

doctor by themselves, and they are dependent on

that doctor\'s viewpoint.

They will say, \"Well, what do you think?\"

I used to say if I were your child, and then it was

if I were your wife, now it is getting to be if I

were your grandmother, you know, with the age of

everyone, and I hope I live to say if I were your

granddaughter.

But that is very true, and again it is not

a simple situation, and whether we need some sort

of health educator to assist the doctor to be able

to explain this to the patients, so that they are

not taking valuable doctor-patient time, but

something needs to be done.

DR. WOOD: Thanks.

Dr. Ilowite.

DR. ILOWITE: I wanted to talk to a few

550

pediatric issues about these agents, the

granddaughter. First of all, about choice, there

are far fewer choices in pediatrics. There is only

three NSAIDs approved, only two liquids and none

any longer that are available as once-a-day dosing

regimens.

The second issue is about tolerability.

Certainly, children have fewer serious gastropathic

events, but they do have a lot of symptoms, and it

is often difficult to get children to take

medications that give them even bellyaches.

Third, is the risk of cardiovascular

disease, which is very low in pediatrics. A new

clinical research network called CARRA, Childhood

Arthritis and Rheumatology Research Alliance,

organization polled its 130 members of whom 92 or

71 percent responded, and there were no events of

myocardial infarction or stroke that couldn\'t

otherwise be accounted for easily that were

551

attributable to these agents.

Lastly, is the issue of exposure. It is

likely that children with chronic rheumatic

diseases are going to be on these agents longer

even than adults, and the cumulative risk is of

great concern.

I think it would be very important to try

to get some insight into the pathogenesis of this,

not just the frequency, so that early markers could

be explored in children who are exposed before they

exhibit the clinical endpoint.

MR. LEVIN: I haven\'t spoken for two days,

so now I may go on. A couple of thoughts. One is

I am all about informed choice, but the question is

how informed is the choice, I think, as others have

raised, and I want to point out that I think we

have this sort of mythology of a changing

environment which is patient-centered in which

there is this sort of partnership.

With all due respect to the clinicians

around the table in the room, I don\'t think that

characterizes most people\'s experience in the

552

health care system today. I think it is totally

unrealistic. We have 45- to 50,000 people who are

uninsured, who have very haphazard access to care,

certainly don\'t have an ongoing relationship

probably with a practitioner who is going to sit

down and run through the benefits and risks in the

alternative therapies and help them make an

informed decision.

We know from studies of how much time

physicians have with patients and what they convey

when they prescribe a drug, that is far from the

role of the learned intermediary that is sort of I

think mythic, and we need to get over.

I agree with Lou that we need to ask

patients what they want and what their experience

is, but on the other hand, we have a regulatory

context here. We have 1906, we have 1938, we have

1962\. For better or worse, the Congress has

decided that there is a role for government to play

in protecting the public from harm.

So, I don\'t think we can just sort of

slide this all off on patients and physicians

553

supposed in this Nirvana good, up-to-date

information, making intelligent choices through

this very difficult, complex issue.

The Government does have a responsibility,

and that is why we are here. We are being asked

for I think advice on how government can best meets

its responsibilities under statute to protect the

public health and to do what it has to do.

We all recognize that there are lots of

things that need to be improved, I believe, in the

way new drugs come to market, because I have sat

through this before when we are chasing the train.

The train is out of the station, folks, it is going

down the track very fast, and we are trying to

catch up to it and figure out what do we do.

You know, it is heading for the crossing,

there is a car on the track, how do we stop the

train. It is too late. We are always going to

hear from patients no matter what the drug, \"This

drug worked for me, it\'s wonderful, it changed my

life.\"

I believe them, I certainly empathize with

554

them. There will always be that appeal. So, I

guess we have a complex task, the train has left

the station, but we can\'t abrogate our

responsibility, and we can\'t pretend the

Government, through the FDA, doesn\'t have a

statutory responsibility here to protect the public

health.

We can\'t just say put information out

there, make it transparent, let this mythical

doctor-patient relationship sort of bubble up and

make things all right, because it\'s not going to

happen that way.

DR. WOOD: Helpful comments from our

consumer representative.

Dr. Manzi.

DR. MANZI: First, I would like to

congratulate the members of the panel who I thought

have brought some very relevant points to the

table, and I agree with most of them, but it is

interesting to me how many times I have heard the

term \"safe alternatives\" used.

I look at our first question about

555

weighing the benefits of the COX-2s versus the

non-selectives, and I think the assumption, as we

are trying to deal with the coxibs, is that there

is, quote \"safe alternatives\" in the non-selective

agents that we would feel comfortable having our

patients turn to in the event that these other

COX-2s were not available.

My question would be, or I guess my

challenge to my other panel members would be to

provide data that has been obtained with the same

rigor and had to undergo the same scrutiny as the

drugs that we have just looked at to prove that the

other non-selectives are safe alternatives.

I don\'t think we have it. I think we have

signals actually to the opposite potentially. So,

I just think we have to keep that in mind as we are

making decisions that patients are going to have to

turn to something, and do you feel comfortable

saying that the alternatives are safe.

DR. WOOD: Another way to think of the

same thing, though, is that if we were sitting here

thinking about approving these drugs right now,

556

would we approve drugs with a clear cardiac risk in

randomized clinical trials.

I think that is an important question for

the committee to address because if we don\'t

address that, we will either not be able to address

it for drugs coming up in the future and/or we are

going to apply a different standard to drugs that

are on the market, and I understand all these

points, but I think it\'s\--maybe I am wrong\--I think

it\'s highly improbable that the committee would

have approved any of these drugs given the safety

signal we have got right now.

I think it is highly improbable that the

FDA\--I am talking about from randomized clinical

trials\--I think it is highly improbable the FDA

would have approved drugs if they had had all the

randomized studies they have right now.

That doesn\'t mean they wouldn\'t have

approved them eventually perhaps, but they

certainly wouldn\'t have approved them on that

basis. Is that fair, Bob?

DR. TEMPLE: I think it varies depending

557

on how you view various collections of data, but

some of them I think probably would not have made

it.

DR. WOOD: All right, some of them we

would not, but that is a fair comment.

DR. MANZI: Could I just comment?

DR. WOOD: Sure.

DR. MANZI: I would argue that that would

depend on the need for the drug, and it would also

depend on the alternatives available, and so I

think it is hard to look at it in isolation.

DR. WOOD: Fair point.

Dr. D\'Agostino.

DR. D\'AGOSTINO: The Framingham study has

generated many risk assessments. They are in the

cholesterol guidelines. Cardiac risk assessment

tools do exist. Would the physicians use them? I

am not sure that cardiologists use them, nor other

classes of physicians to automatically use them and

sit with the patient and go through that, but they

do exist, and if you could build a scenario for

that, it would be possibly very useful.

But one of the things I wanted to really

mention isn\'t just the existence of these tools,

but there seems to be something synergistic about

558

taking the drug and your cardiac risk, so it is not

just a matter of telling you you are diabetic and

how likely you are to have a heart attack. This

drug seems to double that or triple that, and so

forth, so you will be presenting very high risk to

the subjects, and I am not so sure how easy that is

to do, but it should be kept in mind that there is

an elevated risk beyond the normal cardiac risk.

DR. WOOD: Unless someone else has a

burning question, I am going to give Ms. Malone the

last word.

MS. MALONE: I feel the need to speak up

for rheumatologists. I had been on this panel I

believe starting in 1995, and as a consumer rep. I

filled someone\'s term, and then I had my own term.

So, I was on it for five years, and then I came on

as a patient rep intermittently.

From my 35 years dealing with

rheumatologists and being on the panel, I have to

559

say that rheumatologists, on a whole, are a unique

set of doctors. They are in there for the long

haul and I have always felt that when I was on this

committee, if I were not here, that the voice of

the patient would still be heard.

I find that I don\'t think there is one

rheumatologist on here who would not spend time

with their patient, who would not spend time

educating them and listening to them albeit it it\'s

not a half-hour, but I think they do have the

ability to form a relationship with them, and I

applaud them for that, and I disagree with Arthur

on that point.

DR. WOOD: Stephanie, I will give you the

last word and then we are stopping.

DR. CRAWFORD: Thank you so much, Mr.

Chairman. I simply can\'t quite leave without at

least attempting to address this stunning near

cliffhanger that we were given about 40 minutes

ago.

I am going to ask, if I may\--and please

forgive me if I get your name wrong, it\'s not

560

listed on my papers\--I think it was Dr. Kim from

Merck. Thank you.

Yesterday, I asked the question to Dr.

Braunstein about what was or were the deciding

factors in the extraordinary step that Merck made

in deciding to voluntarily withdraw rofecoxib. I

am not sure I heard a clear-cut answer, so I am

going to ask you something very related to this

last question we have been addressing from the

opposite side.

Tonight, what considerations would you

weigh or would you ask this committee to consider

when we deliberate tonight or tomorrow in

determining the benefit of potential

re-introduction of rofecoxib, or if you wish to say

this class, where the benefits would far outweigh

any issues of safety concerns?

DR. KIM: Thank you for that question, and

I will say that it has certainly been a very

educational and informative day, two days actually,

listening to these discussions. I think the issues

are complex, and I think that all of the complex

561

issues are being brought up.

As I said, Merck believes, based on the

new data that has just become available, that what

we are dealing with here in terms of cardiovascular

risk is a class effect.

The thing that we are struggling with,

which you are all struggling with, is what does

that mean in terms of the size of the class, and,

in particular, is it limited to just inhibitors of

COX-2 or does it include inhibitors of COX-2 that

also now have an effect on COX-1.

The only point that I was trying to make

was that at the time that we decided to withdraw

Vioxx from the market, we did so based on the

information that was available to us at that time,

knowing that there were alternative therapies and

that there were questions that were raised by the

APPROVe trial.

Now, where the science has progressed to,

where we see, we think, and we look forward to your

decisions, but we think we are dealing with a class

effect, then, I think we are no longer dealing with

562

a situation where Vioxx is unique in its

cardiovascular risk, but instead is a member of a

class.

Then, I think it is important for

us\--again, we are looking to you, this committee

and the FDA, for your evaluation of whether or not

you agree with our interpretation that this is a

class-specific effect, but if that is the case,

then, I think we need to take a look at the unique

benefits that Vioxx provides, which I mentioned,

and actually a fourth benefit which was already

mentioned, that is, that Vioxx is the only COX-2

inhibitor which has been proven to reduce the

events, serious GI events, as compared to naproxen.

Vioxx is the only COX-2 inhibitor that was

approved that is not contraindicated in patients

with allergies to sulfonamides, and Vioxx was the

only COX-2 inhibitor with approval for juvenile

rheumatoid arthritis in addition to the fact that

we have heard numerous reports from patients, some

with very chronic debilitating pain, that Vioxx was

the only drug that worked for them.

With that, I will leave it to the

committee. We really await your decision on this

issue.

563

DR. WOOD: Okay. It\'s never the last

word, is it.

DR. STRAND: May I finish the answer to a

question that I was asked yesterday?

DR. WOOD: Who are you?

DR. STRAND: I am Dr. Strand and I

responded to you yesterday about the use of COX-2s

in patients, the benefit-risk profile. I simply to

say that with Dr. Hochberg we authored an editorial

in 2002 after the introduction of the data from

CLASS and VIGOR to point out that there is benefit

with these COX-2s, which is at least numerically

preserved from a GI point of view, both from TARGET

and CLASS data, with a baby aspirin, and, in fact,

most of the cardiovascular risk may be abrogated by

co-administration, and we certainly don\'t have to

then worry about the potential interaction as has

been demonstrated with ibuprofen.

So, I think it is important in your

564

deliberations to consider that point.

Thank you very much.

DR. WOOD: Kimberly tells me the committee

has to meet in the lobby in 15 minutes. I think

that is pretty optimistic, but good luck.

(Whereupon, at 7:00 p.m., the proceedings

were recessed, to reconvene on Friday, February 18,

2005, at 8:00 a.m.)

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