FOOD AND DRUG ADMINISTRATION

NINETY-SIXTH MEETING OF THE

CARDIOVASCULAR AND RENAL DRUG ADVISORY COMMITTEE

8:37 a.m.

Friday, April 12, 2002

Kennedy Ballroom

Holiday Inn

8777 Georgia Avenue

Silver Spring, Maryland

ATTENDEES

COMMITTEE MEMBERS:

JEFFREY BORER, M.D., Chairman

Director, Division of Pathophysiology

Weill Medical College

Cornell University

525 East 68th Street, Room F467

New York, New York 10021

JAYNE E. PETERSON, R.PH., J.D., Acting Executive Secretary

Advisors and Consultants Staff

Center for Drug Evaluation and Research

Food and Drug Administration

5630 Fishers Lane, Room 1093

Rockville, Maryland 20857

PAUL ARMSTRONG, M.D.

Professor, Department of Medicine

University of Alberta

251 Medical Science Building

Edmonton, Alberta, Canada T6C37

BLASE A. CARABELLO, M.D.

Professor of Medicine

Houston Veterans Affairs Medical Center

Medical Service (111)

2002 Holcombe Boulevard

Houston, Texas 77030

SUSANNA L. CUNNINGHAM, PH.D.

Consumer Representative

Professor, Department of Biobehavioral Nursing

School of Nursing, Box 357266

Seattle, Washington 98195-7266

THOMAS FLEMING, PH.D.

Professor and Chair

Department of Biostatistics

University of Washington

Box 357232

Seattle, Washington 98195-7232

ATTENDEES (Continued)

COMMITTEE MEMBERS: (Continued)

ALAN T. HIRSCH, M.D.

Associate Professor of Medicine and Radiology

Minnesota Vascular Diseases Center

University of Minnesota Medical School

420 Delaware Street, S.E., Box 508 FUMC

Minneapolis, Minnesota 55455

JOANN LINDENFELD, M.D.

Professor of Medicine

Division of Cardiology

University of Colorado Health Science Center

4200 East Ninth Avenue, B-130

Denver, Colorado 80262

BEVERLY H. LORELL, M.D.

Professor of Medicine

Cardiovascular Division

Beth Israel Deaconess Medical Center

330 Brookline Avenue

Boston, Massachusetts 02215

STEVEN NISSEN, M.D., F.A.C.C.

Vice Chairman, Department of Cardiology

Professor of Medicine

Ohio State University

The Cleveland Clinic Foundation

9500 Euclid Avenue, F15

Cleveland, Ohio 44195

SPECIAL GOVERNMENT EMPLOYEES:

ANDREW S. BREM, M.D.

Professor in Pediatrics

Brown University School of Medicine

Director, Division of Pediatric Nephrology

Rhode Island Hospital

593 Eddy Street

Providence, Rhode Island 02902

ATTENDEES (Continued)

SPECIAL GOVERNMENT EMPLOYEES: (Continued)

JEFFREY B. KOPP, M.D.

Senior Investigator

Kidney Disease Section, Metabolic Diseases Branch

National Institute of Diabetes, Digestive

and Kidney Diseases

National Institutes of Health

Building 10, Room 3N116

Bethesda, Maryland 20892-1268

FOOD AND DRUG ADMINISTRATION STAFF:

JAMES HUNG, PH.D.

ROBERT TEMPLE, M.D.

DOUGLAS THROCKMORTON, M.D.

SPONSOR REPRESENTATIVES:

RAY BAIN, PH.D.

BARRY BRENNER, M.D.

MICHAEL C. ELIA, PH.D.

JONATHAN FOX, M.D.

BONNIE GOLDMAN, M.D.

STEVEN HAFFNER, M.D.

WILLIAM KEANE, M.D.

MARVIN KONSTAM, M.D.

PETER KOWEY, M.D.

SHAHNAZ SHAHINFAR, M.D.

SCOTT ZEGER, M.D.

C O N T E N T S

NDA 20-386/S028, Cozaar (losartan potassium)

Merck and Company, Inc.

Proposed Indication: For the Treatment of

Type II Diabetic Patients with Nephropathy

\* \* \*

AGENDA ITEM PAGE

CONFLICT OF INTEREST STATEMENT

By Dr. Jayne Peterson 7

SPONSOR PRESENTATION

Introduction

By Dr. Michael C. Elia 9

Background, Rationale and Results

of the RENAAL Study

By Dr. Shahnaz Shahinfar 14

Review of the Evidence and Conclusions

By Dr. William Keane 117

OPEN PUBLIC HEARING 204

COMMITTEE DISCUSSION OF QUESTIONS PRESENTED 205

P R O C E E D I N G S

(8:37 a.m.)

DR. BORER: We will call the meeting to order. This is the 96th meeting
of the Cardiovascular and Renal Drugs Advisory Committee.

The agenda consists of consideration of one NDA for losartan potassium
for the indication of treatment of diabetic patients with type II
diabetes with nephropathy.

We have no applicants for public discussion this morning.

I need to announce that Dr. Michael Artman, who made every effort to be
here, was unable to get here because of a last minute problem, so the
committee will be without Dr. Artman today.

I also want to announce prophylactically that I have been importuned to
provide a break at 9:45. We didn\'t do that the last time, and so we
will. So, don\'t worry.

Now, we will begin then with the conflict of interest statement. Dr.
Peterson, do we have one?

DR. PETERSON: Yes. Before we go on I just want to caution the committee
that if you are going to speak you need to push the center button to
turn the mikes on.

DR. BORER: Yes, I\'m sorry. I should have mentioned as well that as for
the committee, as well as for anybody among the presenters or among the
audience, if you are recognized, we do need you to state your name
before you start talking so that the transcription can be as accurate as
possible. Thank you.

DR. PETERSON: I\'ll read the conflict of interest statement now. The
following announcement addresses the issue of conflict of issue with
regard to this meeting and is made a part of this record to preclude
even the appearance of such at this meeting.

Based on the submitted agenda for the meeting and all the financial
interests reported by the committee participants, it has been determined
that all interests in firms regulated by the Center for Drug Evaluation
and Research, which have been reported by the participants present,
present no potential for an appearance of a conflict of interest at this
meeting with the following exceptions.

Dr. Susanna Cunningham has been granted waivers under 18 U.S.C.
208(b)(3) and under 21 U.S.C. 355(n)(4), an amendment of Section 505 of
the Food and Drug Administration Act, for ownership of stock in the
sponsor valued between \$25,001 and \$50,000.

Dr. Andrew Brem has been granted waivers under 18 U.S.C. 208(b)(3) and
under 21 U.S.C. 355(n)(4), an amendment of Section 505(a) of the Food
and Drug Administration Modernization Act, for ownership of stock in the
sponsor valued between \$5,001 and \$25,000.

Dr. Alan Hirsch has been granted a waiver under 18 U.S.C. 208(b)(3) for
his participation on a sponsor\'s bureau supported by firms that have a
financial interest in the product at issue and the competing product. He
receives less than \$10,001 per year.

Dr. Steven Nissen has been granted a waiver under 18 U.S.C. 208(b)(3)
for his consulting with the sponsor on unrelated matters. He received
less than \$10,001 over the past year.

A copy of these waiver statements may be obtained by submitting a
written request to the agency\'s Freedom of Information Office, room
12A-30 of the Parklawn Building.

In the event that the discussions involve any other products and firms
not already on the agenda, for which an FDA participant has a financial
interest, the participants are aware of the need to exclude themselves
from such involvement, 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 any current or previous financial involvement
with any firm whose products they may wish to comment upon. Thank you.

Dr. Borer?

DR. BORER: Thank you. We will begin with the sponsor\'s presentation.
Dr. Elia.

DR. ELIA: Good morning Mr. Chairman, members of the advisory committee,
FDA, ladies and gentlemen. My name is Michael Elia from the Department
of Regulatory Affairs at Merck Research Laboratories.

I would like to thank the Advisory Committee and the FDA for the
opportunity to present Merck\'s data on the efficacy and safety of
losartan in providing renal protection in type II diabetic patients with
nephropathy.

I am going to provide an introduction today to our presentation that
will focus on the results of Merck\'s renal outcome study RENAAL, which
stands for reduction in endpoints in non-insulin dependent diabetes
mellitus with the angiotensin II receptor antagonist losartan.

RENAAL is a multicenter international, double-blind, randomized,
placebo-controlled trial to evaluate the protective effects of losartan
in patients with type II diabetes and proteinuria.

Just to remind you, as we stated in our briefing document, we will use
the words \"nephropathy\" and \"proteinuria\" interchangeably today.

Prior to initiating RENAAL, no convincing long-term renal protection
outcomes data were available in type II diabetic patients with
nephropathy.

To address this, RENAAL was designed as a long term renal protection
outcome study. In RENAAL the primary endpoint was a time to event
analysis of a the composite of doubling of serum creatinine, end-stage
renal disease, defined as the need for chronic dialysis or
transplantation, or death.

As we will show you today, this study provides persuasive evidence that
losartan delays the progression of renal disease in type II diabetic
patients with nephropathy.

Complete data on the hard endpoints of end-stage renal disease and death
were collected on all randomized patients. No patients were lost to
follow-up. The results of RENAAL confirm that the safety and
tolerability profile of losartan is these patients is consistent with
that in the currently approved U.S. product circular for Cozaar.

Furthermore, RENAAL demonstrated that the benefit of losartan treatment
in these patients exceeds that attributable to blood pressure reduction
alone. We believe that these results merit modification of our product
label, with the following new indication. Under the heading of renal
protection in type II diabetic patients with proteinuria, Cozaar is
indicated to delay the progression of renal disease, as measured by a
reduction in the combined incidence of doubling of serum creatinine,
end-stage renal disease, or death.

It\'s important to note that at present there are no drugs approved in
the United States for renal protection in type II diabetic patients with
proteinuria.

While we believe that the RENAAL study provides compelling evidence to
support our proposed indication, it is a single study. In an earlier
meeting this year, this committee and the FDA discussed the evidence
needed to support a new claim for renal protection in type II diabetic
patients with proteinuria. In considering the questions before the
committee today, it\'s useful to review the evidentiary standard needed
to support a new claim for an approved drug. This is especially
important when the basis for the proposed claim rests largely on the
results of a single study such as RENAAL.

Although the FDA has relied on data from a single study to support a new
indication, their views on the matter had not been fully delineated
prior to the issuance of a guidance document.

In 1998 the FDA issued a guidance document entitled \"Providing Clinical
Evidence of Effectiveness for Human Drug and Biological Products\", that
gives the agency its current thinking on the approval of new claims
based on data from a single trial.

When regulatory decisions are based primarily on a single study it is
important to determine the level of confidence one can have in the
results of that study. Are the data scientifically convincing or simply
due to chance? FDA\'s guidance document provides several points to
consider in evaluating whether one has sufficient confidence in the
results of a single study to support a new effectiveness claim.

As you will see you a few minutes in Dr. Shahinfar\'s presentation, the
RENAAL study satisfies several of the key features of a single study
that can be used to support an effectiveness claim. For example, RENAAL
is a large, multicenter study conducted at 250 clinical sites in 28
countries, and it provides persuasive evidence that losartan delays the
progression of renal disease in type II diabetic patients with
proteinuria.

The consistent and significant benefits of losartan across multiple
endpoints and multiple subgroups in the RENAAL study promote confidence
in its findings and provide strong support for our proposed indication.

Furthermore, as described in the advisory committee\'s background
package, several separate smaller clinical studies and preclinical
studies have demonstrated the beneficial effect of losartan therapy on
renal endpoints. These latter studies support the biological
plausibility of renal protective effects of losartan observed in RENAAL.

In summary, we will show you today that the efficacy and safety of
losartan in patients with type II diabetes and proteinuria support our
proposed indication.

Finally, the agenda for today\'s Merck presentation is as follows. After
discussing the natural history of type II diabetes and current
treatments, Dr. Shahnaz Shahinfar from Merck\'s Department of
Cardiovascular Clinical Research will describe the efficacy and safety
results from the RENAAL study. Next, Dr. William Keane, Vice President
of Clinical Development in Merck\'s U.S. Human Health Division, will
summarize the evidence that supports and confirms the RENAAL results,
and end our presentation with our overall conclusions.

The advisory committee members have previously received a briefing
document from Merck that provides more detailed information than time
allows us to present here this morning.

In addition, Merck has brought several consultants to the meeting. These
experts are available to facilitate the Advisory Committee\'s
discussions and deliberations.

Here today are Dr. Barry Brenner from the Harvard Medical School, who
served as Chair of the RENAAL Steering Committee; Dr. Steven Haffner
from the University of Texas, who chaired the RENAAL Endpoint
Adjudication Committee; Dr. Carl Erik Mogensen from Aarhus
Kommunehospital in Denmark, who chaired the Data and Safety Monitoring
Committee; Dr. Peter Kowey from Jefferson Medical College, who was a
member of the Data and Safety Monitoring Committee for RENAAL; Dr.
Marvin Konstam from the Tufts New England Medical Center: and Dr. Scott
Zeger from the Johns Hopkins University.

I would now like to turn the podium over to Dr. Shahinfar.

DR. SHAHINFAR: Good morning. I\'m Shahnaz Shahinfar of Cardiovascular
Clinical Research of Merck Research Laboratory. I was the clinical
monitor for the RENAAL study, which I have the pleasure of presenting to
you.

Today I will be reviewing the background and rationale for the RENAAL
study, followed by a presentation of demographics, efficacy results, and
safety results. Dr. William Keane will conclude our presentation with a
review of the evidence and our conclusion regarding the renal protective
effect of losartan in type II diabetes.

Diabetes mellitus is a major public health issue worldwide. The most
common type of diabetes is type II diabetes, which is the focus of our
discussion today. Up to 40 percent of type II diabetic patients develop
kidney disease. End-stage renal disease is a devastating complication of
diabetes mellitus. Studies have shown that the incidence of end-stage
renal disease is increasing worldwide. In the United States diabetic
nephropathy is the leading cause of end-stage renal disease.

It should be noted that end-stage renal disease is an irreversible
condition, and dialysis is a life-support system to prevent death in
these patients. Even with dialysis, up to 40 percent of diabetic
patients die within 2 years of its initiation, a mortality rate
comparable to that of end-stage heart failure.

No treatment has shown conclusively to delay end-stage renal disease in
type II diabetic patients with nephropathy. It is extremely important to
identify a therapeutic intervention for this unmet medical need.

In the search for a therapeutic intervention to reduce end-stage renal
disease, it should be remembered that diabetic nephropathy is primarily
a glomerular disease. The exact mechanism of progression of diabetic
nephropathies are known, but many factors, both hemodynamic and
nonhemodynamic, may contribute to the development of this glomerular
injury. Angiotensin II has been hypothesized to play a role in the
progressive nature of this glomerular injury.

The proposed mechanisms by which angiotensin II is involved in diabetic
glomerular injury are shown pictorially on this slide. The glomerulus is
the site of the original injury in diabetic nephropathy. As a result of
the original insult to the glomerulus and the loss of the nephrons,
there is a remarkable adaptation within the kidney to compensate for
this nephron loss. The remaining nephrons increase the workload through
a state of hyperfiltration in order to maintain overall glomerular
filtration rate.

Angiotensin II plays an important role in this adaption by increasing
resistance in post-glomerular vessel or efferent arteriole. In addition,
in diabetic patients, resistant in preglomerular vessel or afferent
arteriole is reduced. This combination of increased efferent arteriolar
resistance, mediated by angiotensin II, and decreased efferent
arteriolar resistance results in an increase in intraglomerular pressure
or glomerular hypertension.

This glomerular hypertension, while favorable in the short term, has
long-term detrimental effects on the nephron. This increasing glomerular
pressure initiates an up-regulation of a series of nonhemodynamic
factors. These factors include increased permeability of the filtering
membrane, which may result in proteinuria and activation of fibrotic and
inflammatory processes, in which angiotensin II also plays a role. The
end result is glomerulosclerosis and death of the nephron. This cycle of
nephron death continues until all nephrons are lost, and that\'s when
end-stage renal disease occurs.

Since angiotensin II appears to be play an central role in many of the
hemodynamic and nonhemodynamic mechanisms of the progression of diabetic
nephropathy, it has been hypothesized that the blockade of angiotensin
II will provide renal protection in this disease.

This hypothesis has been tested repeatedly with both losartan and ACE
inhibitors in animal models of diabetic nephropathy. There is no perfect
experimental model for type II diabetic nephropathy. However, the
streptozotocin-induced diabetic rats have been used for this purpose. It
has been demonstrated that the blockade of angiotensin II in this model
is associated with a reduction in glomerulosclerosis and proteinuria.

Furthermore, in an animal model of non-diabetic renal disease, blockade
of angiotensin II reduced proteinuria and glomerulosclerosis. In the
same studies, other antihypertensive agents did not confirm these renal
protective effects. These findings support the biological plausibility
of the effect of angiotensin II blockade in renal protection.

This hypothesis was tested clinically with captopril in type I diabetic
patients with nephropathy, approximately a decade ago. In this study, in
409 type I diabetic patients with proteinuria and retinopathy, with a
mean age of approximately 35, captopril significantly reduced end-stage
renal disease or death. However, until now, conclusive clinical data on
end-stage renal disease have not been available in patients with type II
diabetic nephropathy, which is the most common type of diabetes. It is
important to note that type I and type II diabetic patients represent
two different populations, and it is difficult to extrapolate data from
type I to type II and vice versa.

Patients with type II diabetes are typically older, obese, and have
insulin resistance, advanced atherosclerosis, and long-standing
hypertension. Many of these patients are hypertensive even before the
onset of nephropathy. The kidney of a patient with type II diabetes, in
addition to the glomerular injury of diabetic nephropathy, also has
other morphological changes, which may be a reflection of long-standing
hypertension, older age and macrovascular disease. Only a portion of
this disease burden may be susceptible to the blockade of the
renin-angiotensin system.

In evaluating a therapeutic intervention, especially the magnitude of
benefit, these differences between type I and type II diabetes should be
taken into consideration.

In the absence of definitive data, current therapeutic approaches among
clinicians for renal protection in type II diabetic nephropathy have
focused on metabolic control and blood pressure control. Valuable
amounts of data are available for each strategy. However, there is no
conclusive clinical evidence that these therapeutic approaches are
associated with a reduction in end-stage renal disease in type II
diabetic patients with nephropathy.

Prior to the initiation of RENAAL, the question remained. In patients
with type II diabetes and nephropathy does angiotensin II blockade with
losartan offer renal protection? The RENAAL study was designed to answer
that question.

RENAAL, reduction of endpoints in non-insulin dependent diabetes with
the AII antagonist losartan, was a multicenter, multinational,
double-blind, randomized, placebo-controlled study to evaluate the renal
protective effects of losartan in patients with type II diabetes and
nephropathy.

There were three oversight committees in RENAAL: the Steering Committee,
the Data and Safety Monitoring Committee, and the Endpoint Adjudication
Committee.

The Steering Committee, chaired by Dr. Barry Brenner, was blinded to the
study results and oversaw the overall conduct of the study.

The Data and Safety Monitoring Committee was chaired by Dr. Carl Erik
Mogensen. This committee was unblinded to the results of RENAAL, and
oversaw the safety of the patients in the study.

An Endpoint Adjudication Committee, chaired by Dr. Steven Haffner,
included two cardiologists, three nephrologists and one endocrinologist,
who were blinded to the results, and adjudicated all the primary renal
and secondary cardiovascular endpoints in RENAAL.

Merck functioned as the coordinating and data management center, with
national and regional coordinators. There were 250 centers from 28
countries worldwide.

The primary hypothesis in RENAAL was, in type II diabetic patients with
nephropathy, losartan compared to placebo would increase the time to the
first event of the composite endpoint of doubling of serum creatinine,
which represented more than 50 percent loss of renal function, end-stage
renal disease, defined as need for chronic dialysis or transplantation,
or death, defined as all-cause mortality.

These components of the primary endpoints were selected based on the
natural course of nephropathy in type II diabetic patients. Serum
creatinine progressively rises, leading to a doubling of this
biochemical marker, which represents approximately 50 percent loss of
renal function, followed eventually by the clinically irreversible
condition of end-stage renal disease.

In patients who reach end-stage renal disease, dialysis or
transplantation is necessary to sustain life. Thus, death and dialysis
are competing events. Despite dialysis, mortality remains high in these
patients. Of course, death from any cause can occur at any time.

There were three secondary hypotheses in RENAAL. The first two were
renal hypotheses. Losartan would reduce the rate of progression of renal
disease as measured by the slope of reciprocal of serum creatinine
compared to placebo. Second, losartan would reduce proteinuria, compared
to placebo, during the course of this study.

Another secondary hypothesis was a cardiovascular hypothesis. It should
be noted that RENAAL was specifically designed as a renal protection
study. However, since cardiovascular events are common in these type II
diabetic patients, we made cardiovascular morbidity and mortality a
secondary hypothesis and adjudicated all cardiovascular events.

The cardiovascular hypothesis was that in type II diabetic patients with
nephropathy losartan, compared to placebo, would increase the time to
first event of the composite endpoint of cardiovascular morbidity and
mortality. This cardiovascular composite endpoint included
cardiovascular death, myocardial infarction, stroke, first
hospitalization for heart failure, first hospitalization for angina and
revascularization, both coronary and peripheral revascularization.

The major inclusion and exclusion criteria in RENAAL are noted on this
slide. Since RENAAL was a renal protection study, we enriched our
population with patients who had risk of progression of renal disease.

Important inclusion criteria were that these patients were required to
have type II diabetes and had to be between the ages of 31 and 70 years,
with proteinuria defined as an albumin-to-creatinine ratio of more than
300 milligrams per gram on a first morning void, which demonstrate
macroalbuminuria, or greater than 500 milligrams protein in a 24-hour
urine. Serum creatinine was required to be between 1.3 and 3 milligrams
per deciliter.

Important exclusion criteria included patients with known non-diabetic
renal disease, such as patients with renal artery stenosis and
polycystic kidney were excluded. Patients with uncontrolled diabetes,
defined as hemoglobin A1C greater than 12 percent, were excluded.
Patients with a history of myocardial infarction or CABG within a month,
stroke or PTCA within 6 months, and TIA within a year of randomization,
were excluded. Patients with a history of heart failure were excluded. A
heart failure exclusion criterion was added shortly after the initiation
of the study.

The RENAAL study design is shown on the next few slides.

RENAAL was a double-blind, randomized, placebo-controlled, multicenter
study. Because of the known effect of proteinuria on the progression of
renal disease in type I diabetics and in non-diabetic patients with
renal disease, patients were stratified, based on an urinary
albumin-to-creatinine ratio, less than 2,000 or greater than or equal to
2,000 milligrams per gram.

During the follow-up, clinic and laboratory evaluations were performed
every 3 months. We planned for 1-year enrollment and 5 years maximum
follow-up.

This is a schematic diagram of the study design. Qualified patients with
type II diabetes were screened by urine protein dipstick, and were
placed in a run-in period for 6 weeks. During this period, prior
antihypertensive therapy was maintained, except for angiotensin
converting enzyme inhibitors or angiotensin II receptor antagonists,
which were stopped 6 weeks prior to randomization, and were replaced by
other antihypertensive drugs if needed.

To qualify patients at baseline, they first were stratified, based on
urinary albumin-to-creatinine ratio, less than 2,000 or greater than
2,000 milligrams per gram. Within each stratum, patients were randomized
to receive either 50 milligrams losartan or matching placebo once daily,
on the background of the run-in period antihypertensive therapy. The
goal was a trough blood pressure of systolic less than 140 millimeters
of mercury and diastolic less than 90, which was the WHO-recommended
guideline for diabetics at the time of initiation of the study.

If this goal blood pressure was not achieved within 4 weeks, the study
drug could be increased to 100 milligrams losartan once daily or
matching placebo. If the goal blood pressure was still not achieved,
other open-label antihypertensives, except angiotensin II antagonists or
ACE inhibitors, could be added, or the dose of the existing drug could
be adjusted.

Comprehensive patient follow-up was an important feature of RENAAL, to
ensure that doubling of serum creatinine, end-stage renal disease, and
death events were collected in all patients.

Importantly, in RENAAL patients were required to remain on a study
therapy, regardless of nonfatal events until the completion of the
study. For example, if patients doubled their serum creatinine, they
were to remain on therapy until the end of the study unless the patient
died. If patients experienced end-stage renal disease, they were to
remain on a study drug until the end of the study, unless the patient
died.

We collected end-stage renal disease and death data in all patients,
regardless of doubling of serum creatinine events. This permitted the
independent assessment of treatment on the clinical endpoints of
end-stage renal disease in all patients. For all patients, including
those who discontinued the study drug, clinic visits were to continue
every 3 months to capture renal and cardiovascular endpoint information.

After discontinuation of the study drug, if clinic visits were not
feasible, telephone follow-up was done to capture end-stage renal
disease and death information. Whereas doubling of serum creatinine and
cardiovascular morbidity information were not captured in telephone
follow-up, data on end-stage renal disease and death were collected for
all patients randomized.

On February 10, 2001, the Steering Committee, while blinded to the study
results, voted unanimously to end RENAAL prior to its planned
termination date of March 2002, because of concerns of continuing the
placebo group without the blockade of the renin-angiotensin system. This
decision was based on increasing evidence that ACE inhibitors may be
effective in reducing cardiovascular events in patients with
cardiovascular risk factors. These data were from the Heart Outcome
Prevention Evaluation study, HOPE, and a subpopulation of patients with
renal impairment, which was reported by Mann, et al. in Annals of
Internal Medicine, April 2001.

I would now like to discuss the RENAAL demographics and efficacy
results. In discussing the efficacy results, I will first present the
information under primary and secondary renal data, followed by the
secondary cardiovascular data.

This slide summarizes the patient disposition in RENAAL. In RENAAL,
3,893 patients were screened, 1,513 patients were randomized, 751
patients were allocated to losartan, 762 patients were allocated to
placebo.

The breakdown of patients who completed on the study drug and the number
of patients who discontinued the study drug after reaching a primary
event or prior to reaching a primary event are shown in these boxes.
There are no patients lost to follow-up in RENAAL. Outcome data on
end-stage renal disease and death are available for all patients
randomized.

The next 4 slides provide the baseline demographic data in RENAAL.

Patients were equally distributed with respect to baseline demographics
between losartan and placebo arms of the study. With respect to gender,
age, blood pressure and body mass index, the two treatment groups were
comparable.

The two treatment groups were also comparable with respect to race and
region. The RENAAL study achieved an excellent representation from
diverse ethnic groups. Among the patients in RENAAL, about 17 percent
were Asian, 15 percent were Black, 49 percent were Caucasian, and 18
percent were Hispanic.

The treatment groups were comparable with respect to past medical
history at baseline. As anticipated, the majority of patients in RENAAL
were hypertensive at the beginning of the study and were treated with
antihypertensive drugs. At baseline, the number of patients with
cardiovascular history of angina, myocardial infarction, and stroke was
relatively low in our study.

This slide provides selected mean laboratory values at baseline in
RENAAL. The two treatment groups were comparable with respect to mean
serum creatinine, serum potassium, hemoglobin, and hemoglobin A1C. I
will discuss the differences baseline proteinuria later in my
presentation.

As a reminder, the primary hypothesis of RENAAL was that losartan
compared to placebo would increase the time to the first event of the
composite endpoint of doubling of serum creatinine, end-stage renal
disease, or death. The analytical approach to the primary composite
endpoint was the time to each patient\'s first event. In the next two
slides I will illustrate how patients contributed to this time-to-event
analysis.

In the left column, we have 5 hypothetical patients, A through E. In the
next 3 columns, we show three endpoints that contributed to the primary
composite endpoint. As you can see, patient A doubled his serum
creatinine, developed end-stage renal disease, and died. Compare this
patient to patient D, who died without doubling of serum creatinine or
developing end-stage renal disease.

On this slide we have circled the endpoint that occurred first for each
patient. Each of these values were used as the first event in the
analysis of the primary composite endpoint. Thus, for patient A,
doubling of serum creatinine was the first event captured, and this
event was used in the analysis of the primary composite endpoint.

For patient D, death was the first event, and this event was used in the
analysis of the primary composite endpoint. Note that also 4 of the 5
patients in this example died. Only the death of patient D would
contribute to the primary composite endpoint.

The next slide will illustrate the results of our analysis on the
primary composite endpoint.

DR. BORER: Dr. Shahinfar, can you just stop for a moment? Before you
actually show the outcome data, I would like a clarification that sounds
like you won\'t get to later.

In the book that you sent us, it suggests that there was a distinct
difference in the average years of patient follow-up. It says here on
your page 12 that you had an average of 173 patient-years of follow-up
in the losartan group and 234 years of patient follow-up in the placebo
group. That is clinic follow-up. And with regard to telephone follow-up,
there was the same discrepancy.

Now, in the FDA analysis, however ‑‑ and this was looked at in a
different way ‑‑ the conclusion was that exposure to drug in the placebo
group and the losartan group was approximately equivalent.

Before you actually go on and present the data, I\'d like to understand
why this apparent discrepancy exists, or is not a discrepancy, or do I
not understand these data correctly?

DR. SHAHINFAR: Thank you very much for your question. The numbers that
you are referring to in the background refer to the patients who were
discontinued and they went to some kind of follow-up.

Basically, after patients were discontinued from the study, we tried to
keep them in the clinic regardless of whether they were on drug or were
not on drug. So, in those patients, some of them couldn\'t come back for
subsequent clinic visits, but we followed these patients in telephone
follow-up. Does that answer your question?

DR. BORER: Yes, it does indeed. What we are seeing here is that people
stayed on losartan longer. That\'s why there were presumably fewer
patient years of follow-up in the losartan group. I understand. Thank
you.

DR. SHAHINFAR: The next slide will illustrate the results of our
analysis on the primary composite endpoint. In all the slides that you
will see today, losartan is depicted in yellow and placebo in white.
Unless otherwise noted, all efficacy analyses are based on intention to
treat.

The primary composite endpoint results of RENAAL are demonstrated in
this Kaplan-Meier curve. In this slide, the y axis is the percentage of
patients with events. The x axis is the duration of follow-up. The
number below the x axis represents the number of patients at risk at
each time point.

As this slide illustrates, RENAAL began with 762 patients in the placebo
group and 751 patients in the losartan group. By 36 months in this
study, year 3, there still remained 296 patients at risk in the placebo
group, and 300 patients in the losartan group. As anticipated, by month
48 a relatively small number of patients at risk is available in each
treatment group.

The risk reduction for losartan was calculated using the Cox
proportional hazard regression model. The results demonstrate that
losartan significantly reduced the risk of the primary composite
endpoint of time to first event of doubling of serum creatinine,
end-stage renal disease, or death by 16.1 percent; p equals .022.

In RENAAL, there were prespecified analyses of the irreversible clinical
endpoints, collectively referred to as end-stage renal disease, death,
and a composite of end-stage renal disease or death. Since patients were
followed after the occurrence of a nonfatal primary endpoint, many
patients experienced multiple clinical endpoints. In these cases the key
principles applied were that a patient counted as having had an endpoint
in all relevant analyses and that a patient counted only once in any
analysis.

This slide summarizes the analytical approach taken for the irreversible
clinical endpoints. For end-stage renal disease, the analytical approach
included all patients who reached end-stage renal disease, regardless of
whether doubling of serum creatinine occurred first.

For death, the analytical approach included all patients who died,
regardless of whether doubling of serum creatinine or end-stage renal
disease occurred first.

For end-stage renal disease or death, the analytical approach included
patients who reached a first event of end-stage renal disease or death,
regardless of whether doubling of serum creatinine occurred first.

These analyses were performed on the entire patient cohort, because all
patients were followed for the occurrence of end-stage renal disease and
death for the entire study.

The next slide illustrates how these events would be captured for
separate analysis of ESRD, death, and the composite of ESRD or death.

This slide illustrates the same 5 hypothetical patients that we showed
you earlier. For each patient, the first occurring primary event is
circled. Now, let me show you how these events in these patients would
be captured in each of the analyses of the irreversible clinical
endpoints of ESRD, death, and the composite of ESRD or death.

The three columns on the right-hand side of the slide illustrate the
analysis of end-stage renal disease, death, and the composite of ESRD or
death, and the contribution of each patient\'s event to each analysis.

Patient A contributes to all three analyses, whereas patient D
contributes to the analysis of death and to the analysis of ESRD or
death.

Please note that although a patient can experience each of the three
endpoints of doubling of serum creatinine, end-stage renal disease, and
death, a patient is only counted once in each analysis.

For the prespecified analysis of end-stage renal disease, defined as
need for chronic dialysis or transplantation, the y axis shows the
percentage of patients with events. The x axis demonstrates duration of
follow-up.

Losartan treatment reduced the risk of end-stage renal disease by 28.6
percent; p equals .002. As you see in this Kaplan-Meier curve, the
effect of therapy is observed about 18 months after the initiation of
losartan, as demonstrated by the separation of the curve at this time
point.

This is the first time that a therapeutic intervention has shown a
beneficial effect on end-stage renal disease in type II diabetic
patients with nephropathy.

For the prespecified analysis of all-cause mortality, there was no
significant difference in this endpoint between losartan and placebo; p
equals .884.

End-stage renal disease and death are competing events in type II
diabetic patients with proteinuria because these patients may die before
reaching end-stage renal disease or die as a result of requiring but not
receiving dialysis, which is a life support therapy in these patients.
Therefore, we evaluated the effect of losartan on the risk of
experiencing either of these two endpoints. The prespecified analysis of
the composite endpoint of end-stage renal disease or death demonstrated
that losartan significantly reduced the risk of this outcome by 19.9
percent; p equals .009.

To summarize the results of the RENAAL primary hypothesis and
prespecified analysis of irreversible clinical endpoints, this chart
displays the percent risk reduction and its 95 percent confidence
interval.

Note that the horizontal scale is a logarithmic scale from plus 50
percent on the left, corresponding to a reduction risk due to losartan,
to minus 50 percent on the right, corresponding to an increase in risk
with losartan. The confidence intervals are symmetric on this
logarithmic scale. Losartan significantly reduced the risk of the
primary composite endpoint and the irreversible clinical endpoint of
end-stage renal disease and end-stage renal disease or death.

Before the initiation of RENAAL, we recognized the overall importance of
proteinuria on the progression of renal disease, but the precise nature
of this relationship in type II diabetes was unknown. Therefore, RENAAL
patients were stratified at baseline, based on a level of proteinuria
less than 2,000 or greater than 2,000 albumin-to-creatinine ratio.

As a result of the stratification, within each stratum an equal number
of patients were randomized to each treatment group. However, there was
an imbalance in the distribution of baseline proteinuria within the
higher stratum of greater than 2,000. Specifically, more patients with
baseline proteinuria above 4,000, the highest level of proteinuria, were
randomized to the losartan arm compared to placebo. I will now
illustrate these two points in each of the next two slides.

This slide demonstrates the patient randomized to losartan or placebo in
each stratum. The x axis demonstrates categories baseline proteinuria
and the y axis is the percentage of patients in each category. The two
strata are noted: the lower stratum below 2,000 on the left, and the
higher stratum above 2,000 on the right.

As you see from this slide, stratification ensured that overall there
was an equal number of patients on losartan and placebo in each stratum.
But such a stratification does not eliminate the possibility of an
imbalance of distribution of patients within each stratum. As I will
show you next, that occurred in RENAAL.

As demonstrated on this slide, there is a statistically significant
imbalance in the distribution of patients between losartan and placebo
with respect to baseline proteinuria within the higher stratum. This
imbalance is especially pronounced in the category of greater than 4,000
patients where we have more losartan than placebo patients. I will show
you later that these patients are at the highest risk of progression of
renal disease, and that 80 percent of these patients had a primary
endpoint during the study.

In RENAAL, we demonstrated that in type II diabetic patients there is a
strong relationship between baseline proteinuria and the risk of the
primary composite endpoint as shown on this slide. In this analysis we
pooled the losartan and placebo groups. On the x axis, different levels
of baseline proteinuria are listed. On the y axis is the hazards ratio
for the primary composite endpoint, which is the hazard rate for each
level of proteinuria relative to 300 milligrams albumin-to-creatinine
ratio, which was the entry criterion for proteinuria in our study. The
larger the hazard ratio represents the higher risk for primary event. As
it is shown, the risk for primary events increases substantially as
baseline proteinuria increased.

For example, in a patient at baseline proteinuria of 2,000
albumin-to-creatinine ratio, the hazard rate for the primary outcome is
approximately 3 times higher than a patient with 300 milligrams
albumin-to-creatinine ratio. In a patient with 4,000
albumin-to-creatinine ratio at baseline, the hazard rate is about 8
times higher than a patient with 300 milligrams albumin-to-creatinine
ratio.

Because of the important role of proteinuria and the risk of the
progression of renal disease, and since prespecified primary analysis
did not adjust for imbalances within strata, it was reasonable to adjust
for imbalances in baseline proteinuria for RENAAL. The results of this
analysis are shown in the next two slides.

Using the baseline proteinuria as a continuous covariate, in the Cox
proportional hazard regression model, the risk reduction with losartan
on the primary composite endpoint increases from 16.1 percent to 22.2
percent; p equals .001.

Adjustment for baseline proteinuria also results in an increase in
treatment effect on irreversible clinical endpoints of end-stage renal
disease and a composite of end-stage renal disease or death. This slide
demonstrates the risk reduction with losartan for the primary composite
endpoint, end-stage renal disease, death, and end-stage renal disease or
death. The solid line with a circle represent the prespecified analysis,
and the dotted line with the square represents the adjusted value, using
baseline proteinuria as a continuous covariate. As you can see, the
dotted line with the square moves toward the left of the 0 line in favor
of losartan.

DR. BORER: Before you go on, Dr. Shahinfar, this is Jeff Borer for the
microphone for the tape there. Those adjustments are very interesting,
and intuitively they seem reasonable and I don\'t want to suggest that
there isn\'t an effect here and that the proteinuria isn\'t important.
But I have some concern about accepting adjustments and numbers based on
adjustments per se because my understanding is that to make an
adjustment you have to assume that you know the relationship
quantitatively between the variable for which you are adjusting and the
dependent variable, the outcome variable. I don\'t think we know that.
So, you\'re assuming a model.

I am going to ask Tom Fleming and the FDA statistician, if we have him
or her here, to comment on that. But, what I would like to see, if you
have the data ‑‑ and you may not have them this minute, so you can pull
them out ‑‑ is an analysis of absolute numbers for the outcome in people
above 4,000, understanding that there\'s an imbalance in favor of more
on losartan, and for 2,000 to 4,000, which are the patients where there
was an imbalance in favor of placebo, still above your prespecified cut
point.

I would like to know that, and, Tom, I would like to have some comment
from you about the validity of this kind of adjustment, if you would.

DR. FLEMING: I would be happy to look at the results as you have asked
for them, and then I can comment. You have asked, since in particular
what we are seeing is a breakdown of imbalances in those above 4,000, it
would be interesting to see the results in that stratum above 4,000, and
then in the complement.

DR. BORER: I was also asking about the generic issue of making
imbalances based on models when we don\'t really know the relation
between the variables that we are adjusting for.

DR. FLEMING: Okay, I\'ll go ahead a comment now then.

The approach that is being used is a very standard approach to address
any potential confounding that can exist, and a confounder arises, as
you know, when you have a very predictive variable that is imbalanced
between the two arms.

What we are seeing here is a recognition that baseline proteinuria in
advance is obviously a very important predicted variable. The structure
that was imposed was to balance for those below 2,000 and above 2,000.

What we\'re seeing here ‑‑ and I would like to probe a little bit later,
at exactly how this functional form was derived ‑‑ I think it is in
slide 54, which is certainly very informative and relevant. Taking that
as the truth, what it is showing is that there\'s a striking monotonic
trend toward increasing risk of the outcome as you increase that
baseline proteinuria level, such that there could readily be emerging
imbalances in the cohort above 2,000 because there was no structure
imposed beyond what randomization does itself to assure a balance in
those people who were above 2,000.

What emerged in the data was an excess of 92 versus 71 people with
values above 4,000. So, there was a confounding that emerged in spite of
the structure imposed at randomization, and that confounding certainly
has the potential of biasing the results.

If you use a Cox regression or a stratified log rank analysis, you get a
very appropriate and legitimate adjustment for that balance. You don\'t
have to assume you know the functional form. If it\'s a highly
predictive covariate and it\'s imbalanced, we don\'t have to assume we
know that to do a Cox regression analysis or a stratified log rank.

The problem that we run into in interpreting this, though, is post hoc
analyses that are adjusting for imbalances that can occur even in a
random way in a randomized stratified trial require some careful
interpretation because one could do these analyses in numerous ways;
i.e., you could form innumerable different types of covariate
adjustments. And I\'d like to come back to this discussion later on.
That\'s the issue that I think we have to be a bit cautious about how we
interpret.

But it is certainly very appropriate in a supportive analysis to look
for what might be profound or very substantial evidence of confounding
and in a supportive analysis to look to see whether that strengthens or
weakens our sense of association.

DR. BORER: Thank you.

Dr. Temple?

DR. TEMPLE: So, I think the first thing Jeffrey asked was where did you
get those numbers. How did you decide how to make the adjustment? And,
your answer, if I understand it was, they looked at the relationship
between proteinuria in both the untreated and treated people and found
that relationship in these data. The risk in there is that you can find
it even if it\'s not true as a matter of chance sometimes. So, you have
to judge its degree of plausibility. If it were extremely plausible, of
course it would have been prospectively defined. This comes up all the
time. People are smarter after the fact than before.

The other point I guess is that looking at the two groups, people over
4,000 and under 4,000 is sort of the poor man nonstatistician covariate
analysis, and it\'s very helpful for people who don\'t quite understand
what covariate analyses are, like me. So, that\'s always very helpful.

DR. FLEMING: In this discussion, I think if you could put slide 54 up as
well, which I think is your slide that showed what I call the functional
form. This is very important.

For a covariate to be a confounder you need to have an imbalance. Okay,
we\'ve seen that, 92 against 71. It has to be imbalanced in a way that
matters, i.e. those people, i.e., the 92/71, or the people who are at
4,000 or to the right, and those people are at much higher risk than
people who were to the left. Two questions.

I\'m always a little skeptical about a curve that is so smooth. That
probably is what nature really is, but our data usually has much more
noise. So, how did this function form? Was it derived from this study or
other data? That\'s question 1.

Question 2 is, is this the relationship of baseline proteinuria with a
triple endpoint, and if so, I might speculate the relationship with what
I care more about, which is the double endpoint. End-stage renal
disease/death would be even a more striking gradient.

Can you answer those two questions?

DR. BAIN: Yes. Ray Bain, clinical biostatistics, Merck Research Lab.

You\'re correct. This slide here was based on the pooled groups from the
RENAAL study, the 15/13 patients. You are also right that this
particular analysis, this hazard ratio of increasing baseline
proteinuria, relative to a patient who has 300 milligrams per gram, is
based on our primary triple endpoint, doubling, death, or dialysis.

Now, Dr. Temple is also correct that sometimes if we were more
intelligent we would have probably introduced this correction way back
when we were designing the protocol. It turns out that we were half
intelligent. We did recognize the importance of baseline protein and
therefore prestratified. Now, unfortunately we only prestratified by
less than 2 and greater than 2, but we recognize that it was a very
important baseline risk factor.

In addition to that ‑‑ and we can go into this later ‑‑ we also
prespecified in our data analysis plan to do a risk score analysis,
which looked at a number of different baseline risk factors. It turns
out 1 of the risk factors that we included as potentially being a risk
factor for our triple endpoint was, again, baseline proteinuria. We can
go into that later if you like.

Dr. Borer, did we answer your question?

DR. BORER: Reasonably.

DR. TEMPLE: Do you have that curve for the renal endpoint alone?

DR. BAIN: Yes, we do.

DR. LINDENFELD: Jeff, may I ask?

DR. BORER: Yes.

DR. LINDENFELD: I wonder if we could back to the last slide. Can you
just show us that same data on slide 54 when the endpoint is end-stage
renal disease or death?

The reason I ask this ‑‑ and everyone can help me with this ‑‑ is I
think all of us who see these patients recognize as the proteinuria goes
up and up the diuretics go up and up. And while in the past we have
considered a doubling of creatinine a real endpoint ‑‑ that is, it
reflects loss of renal function ‑‑ when we start to add those diuretics,
we have all seen the creatinine double. We withdraw diuretics and it
goes back down. So, I wonder if this same endpoint holds when we don\'t
use the doubling of creatinine.

DR. BAIN: We do not have that particular graph, but we could probably
get it.

DR. FLEMING: The second question that I was intending to ask was that I
wanted to see that same curve not for the triple endpoint, but what I
call the double endpoint. I think of the double endpoint as end-stage
renal disease/death, where my speculation is the gradient or the slope I
would expect would be even greater, but I\'d like to see that.

DR. BAIN: Okay, we\'ll work on that.

But, as you can see here, this is again one of these curves where now on
the x axis here is hazard ratio, so the .5 is that 50 percent reduction.
You can see the doubling of serum creatinine if you look at that line.
I\'m sorry. The primary composite outcome is at the top there. At the
very top, the solid line is our primary outcome, the .022. The next line
below that is what Dr. Shahinfar already discussed. When you adjust for
baseline proteinuria, it moves the effect to the left and you get a p
value of .001 that she showed.

Now, we haven\'t shown you that curve for baseline proteinuria as a
prediction of ESRD or death, but you can see the same type of effect
here when you look at the ESRD. We haven\'t gotten there yet I think,
but you\'ll see that endpoint of ESRD or death, and then you\'ll also
see that when you adjust again for continuous baseline proteinuria it
moves the treatment effect to the left.

DR. FLEMING: Let me just clarify a little bit. Put that slide back up.

I guess to provide the most precise statement, where I\'d expect the
biggest gradient is end-stage renal disease as a single endpoint,
because certainly what we are seeing is an effect on end-stage renal
disease much more so than death, doubling in serum creatinine for
reasons we can discuss later. It doesn\'t strike me as an endpoint that
should be as strongly affected by baseline proteinuria as end-stage
renal disease itself. In fact, if we look at the adjustment here, the
adjustment is in fact visually the greatest for end-stage renal disease.

So, my speculation is if we show that gradient curve that you were
showing on slide 54, it would be very interesting to show what the
relationship is of baseline proteinuria not just with the triple
endpoint, but with the double endpoint and with end-stage renal disease
itself.

DR. BAIN: Okay, so your request is to look at slide 54 for the single
endpoint of ESRD and then the double endpoint of ESRD or death. Will do.

DR. TEMPLE: And end-stage renal disease or doubling, just for me.

DR. BAIN: And end-stage renal disease or doubling. Okay.

DR. SHAHINFAR: In RENAAL, we prespecified several sensitivity analyses
for the primary composite endpoint, using hemoglobin A1C and mean
arterial pressure as time varying covariates. We also performed analyses
of baseline subgroups. Hemoglobin A1C, as mentioned in your background,
was comparable between the two treatment groups. In the next several
slides, I will discuss the sensitivity analysis for mean arterial
pressure and baseline subgroups.

Blood pressure control was an important treatment goal in the RENAAL
study. Blood pressure was aggressively treated in both treatment groups
in order to get to equal blood pressure levels between losartan and
placebo, a trough systolic less than 140 and diastolic less than 90
millimeters of mercury.

The goal blood pressure was achieved by titrating losartan or matching
placebo from 50 to 100 milligrams first and then titrating other
open-label antihypertensives from different classes, with the exception
of ACE inhibitors and AII receptor antagonists.

The next slide shows concomitant antihypertensive drugs used during the
study. As you see from this slide, many drugs from different classes of
antihypertensives had to be used in order to control blood pressure in
these patients.

It should be noted that in addition to study drug, patients in both
treatment groups took an average of 3-and-a-half antihypertensive drugs
from different classes. The use of each class of antihypertensive agents
was comparable between the losartan and the placebo group.

This slide demonstrates the mean systolic and diastolic blood pressure
in each treatment group during the study. The y axis is blood pressure
in millimeters of mercury, and the x axis is duration of follow-up.
Overall, the mean systolic and diastolic blood pressure were reduced
throughout the study. In the losartan group blood pressure declined from
152 systolic and 82 diastolic at baseline to 140 systolic and 75
millimeters of mercury diastolic at the study end, while in the placebo
group, blood pressure declined from 153 systolic and 82 millimeters of
mercury diastolic to 142 systolic and 75 diastolic at the study end.

Since both systolic and diastolic blood pressure were aggressively
treated, the best approach would be evaluation of mean arterial
pressure, which reflects both.

This slide demonstrates by percentile the distribution of mean arterial
pressure. The y axis is the mean arterial pressure in millimeters of
mercury, and the x axis is duration of follow-up. The line in the middle
of each box represents the 50th percentile of mean arterial pressure.
The bottom of the box is the 25th percentile, and the top of the box is
the 75th percentile of mean arterial pressure. The whiskers represent
the 5th and 95th percentile of mean arterial pressure in all patients.

As you can see, we were successful in reducing blood pressure in these
patients. Mean arterial pressure decreased in all patients throughout
the study. Overall, except for the first year of the study, the mean
arterial pressure was comparable between the losartan and the placebo
group. On the average there was a 2 millimeter of mercury difference in
mean arterial pressure, with the losartan group having lower blood
pressure. This difference, although small, did achieve a statistical
significance.

Adjusting for differences in mean arterial pressure, using a predefined
analysis of a time varying covariate, demonstrated that the losartan
effect on the primary composite endpoint and on the irreversible
clinical endpoints of end-stage renal disease, death, and a composite of
end-stage renal disease or death, were minimally affected by this
adjustment.

As is demonstrated on this slide, the dotted lines with squares shows
the treatment effect after adjustment for mean arterial pressure, using
mean arterial pressure as a time varying covariate.

This supports the conclusion that the renal protective effects of
losartan on the primary composite endpoint and on irreversible clinical
endpoints of end-stage renal disease, and end-stage renal disease or
death, is over and above the antihypertensive effect of losartan.

DR. BORER: Excuse me, Dr. Shahinfar, two things. First, because I always
keep my word, it\'s 30 seconds short of 9:45, and we\'ve been importuned
to have a break at 9:45 for about 10 minutes, which we will. This seems
like a reasonable break point.

At this point I want to just take my 30 seconds to ask you about these
data, because to me these are particularly important in judging the
independent effect of losartan for this indication.

Here I am even more concerned about the relation of the model to the
conclusion, because, in fact, the adjustment makes the drug appear to be
somewhat less effective. I don\'t care about the p values and all
because it\'s hard for me to interpret those in this setting when we\'re
talking about adjustments.

But, did you do anything with blood pressure that was analogous to what
you did with protein? For example, you found 4,000, after the fact, that
there was an imbalance above 4,000. Wasn\'t there an imbalance above 160
or 180 in favor of placebo, and is that where most of the events lay in
the placebo group? I don\'t know.

The other question I would ask is why, and we don\'t need a prolonged
answer here, and maybe one of your consultants wants to get up and talk
about this, because they know more than I do. You looked at mean
pressure and you said that really was the best integrator, and I would
wonder about that.

As data emerged it appears that systolic pressure and pulse pressure,
particularly in the population that you studied, might be more
important, and mean blood pressure would tend to minimize the effect of
the widening pulse pressure that you see when you look at the difference
in the systolic and diastolic blood pressure curves on drug and on
placebo. There is a wider pulse pressure on average throughout the
course of the study in the patients on placebo than on losartan. You
tend to lose that when you define a mean blood pressure.

So, I would like some quick answers to those questions, and if one of
them is going to be long, we\'ll wait until after the break. But first,
how about the cut points for blood pressure?

DR. SHAHINFAR: We didn\'t do exactly what we did for proteinuria. It\'s
not exactly the same picture. It was to see where are the outliers.

One important factor is that we saw events in all different levels of
blood pressure control. But the important finding is that the better the
blood pressure is controlled, so even in the placebo group, when blood
pressure is controlled absolutely great, we have better treatment effect
with losartan, which basically proved that this is not just blood
pressure.

The answer to your next question, I think is very important, and I agree
with you. In looking at the pulse pressure and systolic and diastolic in
these patients, we look at all of those factors. Mean arterial pressure
was predefined. What I presented today is the predefined analysis and
the correction that we did. Did I answer your question?

DR. BORER: Pretty much. But it looks like we have an additional answer
here.

DR. KEANE: Thank you. I\'m Bill Keane. I\'m the last presenter this
morning, but maybe I could just quickly come in here and talk to the
issue before we do break. I\'m Vice President for Clinical Development
in U.S. Human Health.

Let me give you some numbers, and if we want to discuss these more ‑‑ we
did look at the prespecified, as Dr. Shahinfar has indicated, the mean
arterial pressure ‑‑ and you\'ve already seen that data.

We\'ve also looked at obviously each of the components, the systolic,
the diastolic, as well as the pulse pressure, to see the influence on
our risk reduction. In essence, the risk reduction all was approximately
16 percent. For the mean arterial pressure, it was 15 percent. For the
diastolic pressure alone, it was a 17 percent risk reduction. For the
systolic blood pressure alone, there was a 13 percent risk reduction,
and for the pulse pressure, there was a 13 percent risk reduction. So,
this basically I think answers the issue that you are raising.

I think that this is an important point because overall, as Dr.
Shahinfar has said, we did aggressively lower blood pressure in the
trial. We came from about 150 over 80 at the start. We brought it down
to about 140 over about 75 at the end. Blood pressure changed, and these
were our adjustments as we looked at them.

DR. BORER: We may want to come back to this, but I wonder if anybody,
before the break, has any other comments they want to make on the
committee about this issue. Otherwise, we can come back to it in later
discussion. Tom?

DR. FLEMING: Just very briefly, if that slide can go back up. It
confirms what your sense was, Jeff. Basically the imbalance seems to be
more with systolic than with diastolic, and so when you adjust for
systolic rather than the mean you do see the bigger effect of the
confounding.

DR. BORER: Okay. Thank you very much. We may come back to this later.

Let\'s take a short break now and reconvene at 10 o\'clock.

(Recess.)

DR. BORER: Okay. Dr. Bain.

DR. BAIN: Dr. Borer, your original question was, was there a difference
in baseline blood pressure? Actually you were interested in some of the
upper distributions. We looked at the distribution of blood pressure at
baseline and there was no difference in the distribution, if you look at
the percentiles over time.

Now, this morning already we\'ve talked about two different adjustments,
and what I want to do is make sure that everybody understands the two
different adjustments we\'ve talked about so far.

The first one we introduced was the adjustment because we observed this
difference in baseline proteinuria. As we showed, there were higher
levels of proteinuria in our upper stratum, the greater than 2 grams.
The rate was higher in the losartan group. Because of that baseline
imbalance we showed you, when we adjusted the treatment effect, the
treatment effect got stronger because of the losartan group having the
higher baseline protein. So, that\'s the first one we talked about.

Then we introduced another adjustment when Dr. Shahinfar was talking
about the difference that we observed in mean arterial pressure over the
course of the trial. Okay. So, now we\'re not talking about baseline
anymore. Now we\'re talking about adjusting for that difference in mean
arterial pressure during the study. And what we showed there was, when
you adjust for the mean arterial pressure as a time varying covariate,
is it had minimal impact on that same treatment affect that we observed
on our primary composite endpoint. Okay?

DR. BORER: Okay. Thank you.

DR. KOPP: Could I ask a blood pressure question? You have blood
pressures out to 48 months. Were patients censored for collection of
that data when they went on dialysis?

DR. SHAHINFAR: No. All patients were included in the analysis, so that
included all of them.

DR. BAIN: Let me clarify that. If you are talking about the blood
pressures that we were using to adjust for the primary composite
endpoint, in that adjustment we were only adjusting up to the time they
had the event. We continued to collect blood pressures after that, but
the adjustment is only in effect up to the time of the event.

DR. BORER: Dr. Hirsch?

DR. HIRSCH: Thank you. Alan Hirsch.

I want to talk about a little bit of physiology and the pre hoc
hypothesis for the adjustments. As a non-nephrologist, for me, I am
still a little bewildered by what I would have anticipated the
adjustment would have accomplished. In other words, in a patient with
greater than 4 grams of urinary protein excretion, was it anticipated
that losartan would have a greater impact or a lesser impact on the
primary outcome, based on the time to the first event? In other words,
if we adjust for those patients who are sicker, would we have
anticipated a lesser or a greater effect of the drug?

DR. BAIN: I think the question was, in patients that entered ‑‑ we\'re
back to baseline proteinuria ‑‑ with relatively high levels of protein,
we were adjusting for that imbalance, because that\'s mainly where the
imbalance was. It turns out that, as Dr. Shahinfar has already
indicated, in those patients that have high baseline protein ‑‑ like,
say, greater than 4 milligrams per gram ‑‑ 80 percent of them had an
event. And when you adjust for that baseline difference, that\'s what\'s
having the effect to push the treatment effect to be larger than what we
observe when we don\'t adjust for that imbalance in the high levels of
baseline protein.

DR. BORER: Does that satisfy you, Alan?

DR. HIRSCH: Well, I\'ll come back to this later then. I\'m not entirely
satisfied.

DR. BORER: Before you start the next section, we\'ve been talking about
nephropathy and proteinuria, and Dr. Elia said that the terms are going
to be used interchangeably. I would just like to hear from the
nephrology members of the panel about that equivalence and how we should
interpret these data based on definitions and what have you. Dr. Brem?

DR. BREM: Andrew Brem.

I was a little bit troubled I guess by the opening remarks, stating
something to the effect that proteinuria will equal nephropathy.
Proteinuria is a sign of the nephropathy perhaps, and biopsy is the gold
standard to establish what the nephropathy is and to make that
diagnosis.

I certainly realize that one is not going to biopsy 1,500 patients, so
that\'s not a possibility, but I think it\'s important to recognize that
we are using proteinuria as a surrogate for the nephropathy, not as the
nephropathy itself.

As such, is it well established enough to be used as a surrogate?
You\'re doing your statistics and presenting outcomes based on it as a
surrogate. Have we established well enough that higher the proteinuria,
the worse the outcome? I think probably much of the discussion that
we\'re having about the statistics right now sort of centers on that
question.

DR. GOLDMAN: Yes. That\'s a great question. Bonnie Goldman, Regulatory
Affairs.

I\'d asked that we try to come back because we do have data, if the
group would like to see it, especially within this study, about
essentially what you\'re asking about the surrogacy. But it literally
would take quite a while to go through during the course of this.

The bottom line is, in this study, in fact, there\'s a very good
relationship between the proteinuria and the outcomes. Okay?

DR. BORER: At the end of the day, we are not looking at proteinuria as
an endpoint, just as an admission point, so that may mitigate against
any concern about that.

Tom?

DR. FLEMING: I think it just might be worth a quick comment, that we\'ve
been thinking and talking about proteinuria now in at least three
different ways, as a predictor, as an effect modifier, and as a
surrogate. Those are in fact completely separate concepts.

I am persuaded that proteinuria is a predictor. It is related to the
risk of the outcome. Whether it\'s the triple endpoint, the double
endpoint, or the single endpoint, the higher the level of baseline
proteinuria the higher the risk of these outcomes we\'re looking at. So,
it is a predictor.

Is it an effect a modifier, which might be related to Alan\'s comment.
I\'m not sure, but as an effect modifier, the question is, is the
treatment effect different in people above 4,000, versus in people 2,000
to 4,000, versus less. I don\'t know the answer to that, but that\'s an
entirely separate question than whether we should adjust for baseline
proteinuria if there is an imbalance because it is a potential
confounder.

The third issue is, is it is a true surrogate? That\'s the question I
ask when I wonder is looking at treatment effect in change in
proteinuria levels an adequate measure of whether I\'m truly achieving
clinical benefit. I would agree that that is entirely unestablished,
that proteinuria levels would be an adequate replacement endpoint.

DR. BORER: Here we\'re not doing that, fortunately.

Dr. Temple?

DR. TEMPLE: Tom\'s second question would be answered by the display that
you initially requested, and that I asked for also, which is to look at
what the effect of treatment is in the greater than 4,000 and less than
4,000, which is still your poor man\'s covariate adjustment for people
who don\'t understand covariate adjustments very well. It is very
informative. We still hope to see that.

DR. BORER: We poor men probably will see that after lunch, and poor
women, if there are any of you among us.

DR. SHAHINFAR: I think this is where we left off.

Next I would like to show you the analysis of primary composite endpoint
across predefined baseline subgroups.

This slide is intended to convey by visual impact the consistent benefit
of losartan across a variety of subgroups. The primary composite
endpoint was explored in 18 predefined subgroups, which are shown on
this slide. For each subgroup, the point estimates on the graph are all
on the left side of the zero line in favor of losartan. Overall, there
was no significant interaction between losartan treatment and these
predefined subgroups, except for region.

When testing as many as 18 subgroups, it\'s not unexpected that by
chance alone one subgroup would have a significant interaction. While it
appears that the effect of losartan varies among regions, note than none
of the point estimates are to the right of the 0 line.

As noted in the FDA review, there is not a significant regional
heterogeneity.

DR. BORER: Can we just stop you there for one second? I think that one
issue that may come up and that I don\'t understand so well may have to
do with definition.

Dr. Armstrong, did you want to say something about that?

DR. ARMSTRONG: As a non-nephrologist, I would appreciate some discussion
about the definition of end-stage renal disease, which is the clinically
robust, meaningful component of the double endpoint, which we are
relying on. I guess the issue is how systematic is this definition
applied across centers and countries, since there were many in your
study? To what extent did it relate to some of these other markers such
as proteinuria and creatinine?

For example, was there heterogeneity across centers or countries as it
relates to the application of this to a non-nephrologist\'s subjective
decision about transplantation or dialysis, which is obviously modulated
by several factors. So, I would really appreciate some enhanced
understanding around this issue.

DR. SHAHINFAR: That\'s a very important question, and the criteria for
the definition of end-stage renal disease was a requirement for dialysis
or transplantation. As you mentioned, there are some countries where
there is less transplantation, and there are more transplantations in
other countries.

But if the patient required dialysis or transplantation, and the
investigator identified that, that this patient needs to be dialyzed,
and if the patient refused to be dialyzed, or dialysis was not
available, which can happen in some countries, then the Adjudication
Committee used the criteria, estimated GFR. The GFR had to be below 10
ml per minute, corrected for body surface area, in order to adjudicate
that patient as an end-stage renal disease patient. So, this way we have
information on end-stage renal disease in all patient randomized.

DR. ARMSTRONG: May I, Mr. Chairman, just pursue this? So, could you then
reassure me about the homogeneity versus the heterogeneity as it relates
to the application of this across the centers and countries, and the
extent to which the definition was aligned with, as I understand it ‑‑
we\'ve just had a discussion about proteinuria for example ‑‑ could you
comment about alignment of that measurement with this endpoint?

DR. SHAHINFAR: We used a central lab for measurement for all
proteinuria, so it was done uniformly across all countries in the world.
With respect to the definition of end-stage renal disease, there are
very few patients who either required and did not get dialysis or
refused dialysis.

DR. HAFFNER: I\'m Steve Haffner. I was chair of the Events Committee. It
turns out that very few people actually fit into this category. I think
there were 16 subjects. 10 were in one group and 6 were in the other; 10
in placebo and 6 in losartan. I couldn\'t remember which group it was.
It turns out that it was a very small percentage of the people who were
identified as end-stage renal disease. We had to go to the Walser
formula to characterize them. Of those, I think most were refusals, and
not the absence of dialysis as a practical issue.

DR. BORER: Looking at it the other way, was there a substantial number
of people who were put on dialysis with GFRs that were greater than 10
milligrams per hour or cc per hour, whatever it is, adjusted for body
surface area? No.

DR. SHAHINFAR: We did not systematically measure estimated GFR. When the
physician made a distinction that this patient needed to be dialyzed,
based on the condition of the patient and requirement for dialysis, and
if that patient was dialyzed, that was captured as dialysis.

DR. BORER: So, there might be some non-homogeneity across regions in
that regard or no?

DR. HAFFNER: We can look at that but we have not looked at that at this
point. Once they went on dialysis, we didn\'t calculate Walser\'s.

There\'s another issue ‑‑ there were some people who got end-stage renal
disease who were not classified as doubling. That can happen for two
reasons. One is that serum creatinine didn\'t actually double, or two,
in order to be called doubling, they had to get two measures of serum
creatinine, and some people were put on dialysis before the second
confirmation of it.

We actually had long discussions that if there was doubling after
dialysis ‑‑ you\'d figure it would probably double before dialysis ‑‑
but we excluded that from the doubling. So, we took what I think is a
fairly rigorous point about doubling, and the second measurement also
had been done by the central lab. So, there were a few people who
didn\'t make that, but we could do that analysis. But we have not yet by
region.

DR. BORER: Dr. Nissen?

DR. NISSEN: Could you put that slide up on the various subgroups please?
I need some clarification because the slide is at variance with the
briefing document we received from the FDA.

According to our briefing document, the hazard ratio for the Europeans
is actually 1.05, so it actually goes in the wrong direction, and you
show it in the favoring losartan group.

I guess what I want clarification about is that it looks to me, from the
FDA briefing document, that virtually the entire benefit for the whole
cohort comes from the group from Asia. That is, if you look at the rest
of the cohort, there are virtually no effects. The 20 percent of
patients who were from Asia completely drove the endpoint in the trial.
Is that correct or incorrect?

DR. SHAHINFAR: You\'re referring to the region?

DR. NISSEN: Yes.

DR. KEANE: Again, I\'m Bill Keane. Maybe I can take a shot at that at
this point in time. I\'m in clinical development. I think we were going
to get into some of these questions later on, so we can answer it now or
we can postpone it to later on.

I think one of the important points that Dr. Shahinfar has already
mentioned to you is that in fact there was by region a slight
interaction that achieved a level of about .047 that was seen in the
Asian group. I think as we looked at this with the FDA and in greater
detail, actually the FDA ‑‑ and I think that\'s in your briefing
document itself ‑‑ did not really underscore that this was an important
interaction.

Now, part of the reason for that is the way we defined regions, first of
all. The region was a geographic region that included not only the
Pacific Rim but also included the Middle East as well, specifically
Israel. There were, from a regional perspective, just inherent reasons
in our definitions that maybe this might have been shown as a difference
basically, with the point estimates slightly to the left for Asia.

DR. NISSEN: No, but your point estimate for Europe favors losartan, and
in the FDA briefing document the point estimate favors placebo. So, in
Europe this doesn\'t gibe with the FDA\'s data that we got.

DR. BAIN: Ray Bain, Clinical Biostatistics, Merck Research Labs.

If you look at the Merck briefing document, they are all in the right
direction. I assume possibly that the FDA was doing a different baseline
adjustment. I have to look at their briefing document to figure out
exactly what the slight differences were.

DR. NISSEN: For the committee, I am looking at page 22 of the FDA\'s
briefing document, and the data don\'t agree with the data up there. So,
I think we really do need to clarify this from the agency as to what are
the correct numbers here?

DR. BAIN: We also need to look at page 63 of the Merck briefing document
because that\'s what this slide is based on. In the Merck briefing
document, we\'re adjusting for baseline protein as a stratum, but not
region, since region is the variable that we\'re looking at. So, if you
look at page 63 in the Merck ‑‑

DR. NISSEN: I now understand the difference. So, what you did was you
took the post hoc adjustment for protein and added it to this.

DR. BAIN: No. We took our prespecified adjustment, which is the
categories of baseline protein. That was our prespecified analysis. In
that analysis those numbers on page 63, although they\'re in hazard
ratios, so you just take 1 minus that times 100, you\'ll get everything
on the left. For example, in Europe it\'s .943, which is a risk
reduction of roughly 5 percent.

DR. NISSEN: Tom Fleming, maybe you can help me understand this. I don\'t
understand why the two don\'t agree here.

DR. FLEMING: I think we need to sort this out, as we have a chance maybe
over the break, to get a clear ‑‑ my sense is it has to do with the
difference in either ‑‑ and I don\'t think it\'s this exactly ‑‑ who\'s
in which region or what covariates are used in these two analyses for
adjustments. I would suggest maybe at the break we can get that ironed
out.

DR. NISSEN: All right. Maybe not now, but I do want to come back to this
question later on whether the entire treatment effect for the entire
study was driven by the 20 percent of patients that were in Asia.

DR. FLEMING: Just on that point, Steve, in either of these two analyses
the same general, at least qualitative picture is that Asia carries the
greatest part of the signal in either of the analyses.

DR. NISSEN: The overwhelming majority of the signal.

DR. BORER: Dr. Konstam.

DR. KONSTAM: Hi. I\'m Marv Konstam from Tufts New England Medical
Center. I am here as a paid consultant to Merck.

You know, I just wanted to comment from my own experience and
perspective about subgroup analyses, and I think the panel is all aware
about how treacherous this can be of identifying one subgroup.

I just want to point the panel to the FDA medical reviewer analysis of
this, because I personally found it enormously instructive.
Specifically, in the medical review, page 24, figure 7, it breaks it
down by individual countries. What\'s nice about it is that it shows you
the impact of size of the particular subgroups on the relevance of the
relative risk that comes out.

You can break these down all sorts of different ways, but if you look at
this analysis, the individual countries really are all over the map.
Actually, it\'s interesting that the big Asian contribution comes from
Israel, by the way, so you can think about that.

But, I just want to point that out. I think to me this was a very
instructive way of looking at it, and sort of not focusing too much on
this Asian business is at least my perspective on it.

DR. BORER: Dr. Kopp, you had a comment. Before you do, I just want to
point out, Dr. Konstam, I never understood you to be such a humorist. In
fact, the countries are all over the map.

(Laughter.)

DR. KOPP: I wanted to follow-up on a response to Dr. Armstrong\'s point.
I think we had a lot of discussion about how to adjudicate people at the
low end of the GFR spectrum who weren\'t placed on dialysis. I think it
is worth thinking a little bit about the patients with presumably GFRs
between 10 and 15 or 10 and 16, whatever, who were started on dialysis,
and admit that there is undoubtedly both heterogeneity across countries
and within countries about whether a particular patient gets started on
dialysis on the typical day, and think about what the indications would
be. They would certainly, for most nephrologists, include fatigue,
anorexia, falling albumin, among the key criteria that would be looked
at, that I think would be unrelated that I can think of to the therapy
in question.

But there are two that at least might play a role that could potentially
could be related, and one would be potassium levels, difficulty
maintaining potassium, admittedly not too much of a problem with chronic
renal failure patients. The other would be difficult to maintain
congestive heart failure, a patient for whom diuresis was becoming
increasingly difficult. Each of those at least ‑‑ and here I\'m
speculating ‑‑ run in opposite directions. That is, a losartan patient
might be more likely to have hyperkalemia than a placebo treated
patient, but less likely to have difficult to manage congestive heart
failure.

Having said that, there is no way we can really be sure, and I guess the
major protection is this idea that it was all placebo-controlled, and so
the decision was being made by somebody without advance knowledge about
how the treatment was based.

But at least maybe you\'d comment upon the possibility of how some of
those factors that are potentially related to losartan might play into
the decision to start dialysis.

DR. BORER: You can hold that until you have a chance to think about and
come back to it later if you like.

Dr. Lindenfeld, did you want to make a comment?

DR. LINDENFELD: Just a quick question. When we come back to this issue
of region ‑‑ and I think we fully understand the problem with subgroups
‑‑ I wondered if we could see by these regions the numbers of patients
that had a doubling of creatinine versus end-stage renal disease. If we
could divide those up by regions and just see if that was different by
region.

DR. SHAHINFAR: We will show that.

DR. BORER: While you\'re doing that, I think there will be time to
respond specifically to Dr. Kopp\'s question. I know you\'re going to
show us a cardiovascular endpoint analysis, where the heart failure
issue will be death with and a safety analysis where the hyperkalemia
issue and its relation to sudden death will be dealt with. So, let\'s
bookmark that so you can specifically respond to the question when you
get to it.

DR. SHAHINFAR: There were two prespecified secondary hypotheses to
support the renal protective effect of losartan. The first was that
losartan, compared to placebo, would reduce the rate of progression of
renal disease as measured by the slope of reciprocal of serum
creatinine.

This is an important measure that is used by clinical nephrologists to
predict the time to dialysis for the patient. Note that the literature
on nephropathy indicates that the inverse of serum creatinine value for
an individual tends to fall in a linear fashion over time. The slope of
this line is an indication of the speed of progression of renal disease.
The more negative the slope, the faster the progression. This analysis
takes into consideration all patients, not just those patients who have
reached a renal endpoint.

Another secondary endpoint hypothesis in RENAAL was that losartan would
reduce proteinuria during the course of the study, compared to placebo.
The next two slides demonstrate the effect of losartan on these
secondary hypotheses.

For the analysis of the progression of renal disease, we calculated the
slope for each patient, and present here in this chart the median slope
for two treatment groups. As I referred before, the more negative the
slope, the faster is the progression.

This slide illustrates the rate of loss of renal function as measured by
the slope of reciprocal of serum creatinine. On the y axis is the change
in the slope of 1 over sCr. There was a significant reduction in the
rate of loss of renal function by 18 percent with losartan with p equals
.01.

Another secondary hypothesis was the effect of losartan on proteinuria.
Reduction of proteinuria has been considered an important therapeutic
target for treatment of diabetic nephropathy among clinical
nephrologists.

On this slide the y axis demonstrates the mean percent change based on
geometric mean for urinary protein excretion. The x axis is the duration
of follow-up.

Losartan was associated with a reduction in urinary protein excretion of
25 percent within 3 months, and this reduction was maintained throughout
the study. There was an overall 34 percent reduction in proteinuria
compared to placebo, with p less than .001.

The significant treatment effect of losartan on proteinuria was
unchanged after adjustment for blood pressure at each time point,
supporting the conclusion that the antiproteinuric effect of losartan is
over and above its blood pressure lowering effect.

In summary, in type II diabetic patients with proteinuria, losartan is
renal protective by delaying the onset of the primary composite endpoint
of doubling of serum creatinine, end-stage renal disease, or death. In
the entire cohort losartan reduced the risk of end-stage renal disease
by 28.6 percent.

Losartan reduces the rate of decline of renal function as measured by
the slope of reciprocal of serum creatinine.

Losartan reduces proteinuria, and has a beneficial effect on the primary
composite endpoint and proteinuria beyond its beneficial effect on blood
pressure.

I would now like to turn to a discussion of cardiovascular secondary
hypotheses. We designed RENAAL as a renal protection study, but
recognizing the importance of cardiovascular events in type II diabetic
patients, we made a cardiovascular morbidity and mortality a
prespecified secondary hypothesis, and adjudicated cardiovascular
outcomes.

The cardiovascular hypothesis in RENAAL was based on the effect of
losartan on cardiovascular morbidity and mortality. We hypothesized that
losartan compared to placebo would increase the time to the first event
of the cardiovascular morbidity and mortality which was a composite of
cardiovascular death, myocardial infarction, stroke, first
hospitalization for heart failure, first hospitalization for angina, and
revascularization. The next three slides summarize cardiovascular
secondary endpoint data in RENAAL.

This Kaplan-Meier curve demonstrates the result of the secondary
composite endpoint of cardiovascular morbidity and mortality. Although
numerically lower on losartan, there was no statistically significant
effect of losartan compared to placebo on the composite endpoint of
cardiovascular morbidity and mortality.

This plot demonstrates the effect of losartan on cardiovascular
morbidity and mortality and the individual component of this composite
endpoint. The risk reduction and 95 percent confidence interval are
presented for the composite endpoint and each of the components of this
composite endpoint: cardiovascular death, myocardial infarction, stroke,
first hospitalization for heart failure, first hospitalization for
angina, and revascularization, both coronary and peripheral
revascularization.

As you see, the point estimates are all distributed around the 0 line
for different components, but overall there is no significant difference
in the composite endpoint of cardiovascular morbidity and mortality.

During the January 17th advisory committee meeting for irbesartan, this
committee expressed interest in the effect of irbesartan treatment on
the composite of renal and cardiovascular endpoints in the irbesartan
diabetic nephropathy trial. In light of this we performed a post hoc
analysis, time-to-event analysis, of the composite of irreversible
clinical endpoints of end-stage renal disease, myocardial infarction,
stroke, or death in the RENAAL study.

As is demonstrated in this Kaplan-Meier curve, losartan significantly
reduced this combined endpoint by 21.2 percent; p equals .003. This
analysis demonstrates that the renal protective benefits of losartan do
not come at the expense of increased risk of cardiovascular endpoints,
and in fact demonstrates the benefit of losartan in this population.

As mentioned earlier, we designed RENAAL as a renal protection study,
rather than a cardiovascular study. Therefore, we enriched the
population with patients at high risk for progression of renal disease.

In summary, in RENAAL there was no statistical significant difference in
cardiovascular morbidity and mortality.

Post hoc analysis of end-stage renal disease, myocardial infarction,
stroke, and death indicate that renal protective benefits of losartan in
RENAAL did not come at the expense of increased risk of cardiovascular
events, and therefore supports the overall benefits of therapy in these
patients.

DR. BORER: Excuse me one second.

Dr. Kopp, do you want to come back to your issue here. We have just seen
the total cardiovascular endpoints. The sponsor hasn\'t broken out the
heart failure, which they did in their briefing document. They did
actually have one slide that did. Did you want to restate your question,
or are you satisfied with what you\'ve gotten here?

DR. KOPP: I don\'t think it directly addresses the issue. Is it possible
that when a clinician is sitting with a patient with a creatinine of 5.5
and trying to decide does this person needs dialysis, would the presence
of heart failure or the presence of hyperkalemia have tilted one way or
the other that decision. But I think we may get that later from Dr.
Haffner\'s group.

DR. HAFFNER: I don\'t think we\'re going to get really good data on
this. We did not ask people, when they went to end-stage renal disease,
to answer a special questionnaire on why they went to end-stage renal
disease. Was it dialysis, hyperkalemia, nausea and vomiting?

We do have some data on prior events for CHF. We have events on
potassiums. But it would be linking data and this isn\'t all entered. My
guess is eventually we could probably figure some of this out, but
because they weren\'t done at the time of dialysis, I\'m not sure it\'s
going to be really good data, to tell you the truth.

What we clearly could do is we can calculate by regions for instance the
Walser to see if creatinine clearance differed by region. We could
clearly do that. I am not sure we can do that today. We can clearly do
that by whether they were on losartan or in the placebo group, so we can
see whether this is systematic bias by area for people who enter
end-stage renal disease.

But I don\'t think we\'re going be able to get a detailed thing about
hyperkalemia versus failure. We can look at the events prior to it. We
haven\'t done that because that doesn\'t enter into the composite. But I
am really not so sure, as an epidemiologist who works on clinical
trials, how worthwhile that data really is.

DR. BORER: Dr. Lorell.

DR. LORELL: Yes, I wonder if you can provide us with data, in regard to
the all-clause mortality, as to a breakdown of cause of death, including
what percent of deaths were cardiovascular deaths? I think it is a
potentially important issue for this committee to discuss for a couple
of reasons.

One is that this trial was, in fact, shaped and stopped early because of
ethical safety concerns of the committee regarding the growing evidence
of cardioprotective effects of ACE inhibitors on multiple cardiac
events. That letter that was sent to the investigators is in our
brochure.

So, it raises the question, in regard to your last slide, as to the real
issue, a real issue that was also addressed by the Safety and Monitoring
Board, not whether the renal protective effects of losartan were at the
expense of increased risk, but were at the expense of the absence of
cardioprotection from a competitive therapy. That was an issue that
clearly was a concern for the Safety and Monitoring Board.

So, I think it would be of interest for this committee to know the
breakdown of all-cause mortality, if you have that data.

DR. SHAHINFAR: Can I first clarify one question you raise? You mentioned
the Safety and Monitoring Committee. In fact, the study was not stopped
by the Safety Committee. It was stopped by the blinded Steering
Committee, who didn\'t have access to unblinded information. So, that
decision was clearly unrelated to internal information from RENAAL. That
was the decision of the Steering Committee.

Now, with respect to the causes of death and all-cause mortality, would
you like me to present that now, or do you want me to present the safety
and we can present all the information?

DR. LORELL: Why don\'t you include it whenever you think it would be
fit. That would be fine.

DR. SHAHINFAR: If you agree, I\'ll finish the presentation of safety.
Thank you.

Now I would like to present to you the RENAAL safety results. Overall,
the safety profile of losartan in this study was consistent with that
listed in the U.S. prescribing information for losartan. In this
population of patients with type II diabetes and underlying kidney
disease, we expected to see many clinical or laboratory adverse
experiences. In fact, this is demonstrated in high event rates of
clinical adverse experiences in both treatment groups.

On this slide, on the y axis we present the percentage of patients with
clinical adverse experiences. For clarity the percentage of patients are
also shown on the top of each bar. Up to 95 percent of patients in each
treatment group had clinical adverse experiences during the study. There
was a slightly higher number of drug-related clinical adverse
experiences in the losartan group. There were more patients on placebo
who had discontinued for clinical adverse experiences. The number of
patients who died because of clinical adverse experiences was comparable
between losartan and placebo group.

With respect to laboratory adverse experiences, we see a similar
pattern. It is important to note that the laboratory adverse experiences
were those that were reported by the investigators, not based on a
predefined laboratory value. The number of patients with drug-related
laboratory adverse experiences was higher in the losartan group. This
was mostly attributed to a higher number of patients with hyperkalemia.
No patient died because of a laboratory adverse experience.

Because of the population that we studied in RENAAL, we predefined six
adverse experiences of interest, and performed a prespecified analysis.
This table provides the results of our analysis on the six predefined
adverse experiences that are listed on the left column.

The reason for selecting the six adverse experiences was that acute
renal failure has been reported by ACE inhibitors and AII receptor
antagonists. Hyperkalemia and hypokalemia were adverse experiences of
interest since we were studying diabetic patients with underlying kidney
disease. Anemia has been reported with ACE inhibitors and angiotensin II
antagonists. It is listed in the prescribing information for losartan.
It is also common in patients with advanced renal disease. Since we
studied diabetic patients, hyperglycemia and hypoglycemia were also
adverse experiences of interest.

Except for hyperkalemia with losartan, and hypokalemia in the placebo
arm, there was no significant difference in any of the predefined
adverse experiences between losartan and placebo. Hyperkalemia is not
unexpected in patients with type II diabetes and underlying kidney
disease, especially when a drug that blocks the
renin-angiotensin-aldosterone system, such as losartan is used.

In contrast, the higher incidence of hypokalemia in the placebo arm is
probably related to the high use of diuretics. Hypokalemia is important
in patients with chronic renal disease. These patients have low
bicarbonate, and therefore low serum potassium levels are a true
reflection of low intracellular levels of potassium.

This slide demonstrates the distribution of serum potassium by
percentile in the two treatment groups during the study. The y axis is
the level of serum potassium in milliequivalents per liter. The x axis
is duration of follow-up. The line in the middle of each box represents
the 50th percentile of serum potassium. The bottom of the box is the
25th percentile, and the top of the box is the 75th percentile of serum
potassium. The whiskers represent 5th and 95th percentile of serum
potassium at each time point.

Overall, mean serum potassium was significantly higher in patients who
were treated with losartan at each time point. However, the mean
differences did not exceed .3 milliequivalent per liter. 95 percent of
all patients\' serum potassium values were below 6 and above 3.5
milliequivalents per liter at each time.

This table shows the number of patients who had serum potassium less
than or equal to 3.5 and equal or greater than 6.0 milliequivalents in
each treatment group at any time during the study. As you can see on
this slide, there were more patients in the placebo group with potassium
less than 3.5 and more patients in the losartan group with potassium
greater than 6.0 milliequivalents per liter.

There were more patients with adverse experiences of hyperkalemia in the
losartan group. The number of patients with serious adverse experiences
of hyperkalemia was small, but higher in the losartan group. Relatively
a small number of patients had to be discontinued for hyperkalemia in
each treatment group, indicating that hyperkalemia was clinically
manageable in these patients. No deaths were attributed to hyperkalemia
during therapy.

DR. BORER: Dr. Shahinfar, can you just go back to that slide, the last
one? That\'s it. I don\'t want to overstate the case here. You\'ve shown
us total mortality. You\'re going to show us the breakdown of cause of
death, and that\'s of interest, and overall the difference in deaths was
so small that I think that this may not be a major issue.

But you say that no death is due to the adverse event or has been
attributed ‑‑ that was what you said ‑‑ attributed to the adverse event
of hyperkalemia, and I\'m sure that\'s true. I think the only way you
could, with certainty, make such an attribution is, the last time you
saw the patient alive, the potassium was high.

But it\'s interesting that nominally there is an excess of sudden deaths
in the losartan group from your briefing document. Not a tremendous
number, but an excess percentage of sudden deaths nominally. It is not
statistically significant.

I have to wonder whether ‑‑ and this may relate more to labeling if the
drug is ultimately approved for this indication ‑‑ whether this may not
have been related somehow to electrolyte imbalance that just wasn\'t
picked up because deaths occur when they occur, not necessarily right
after the last lab value was done.

Can you just comment on that?

DR. SHAHINFAR: What I would like to do, basically in response to
all-cause death and cardiovascular death, and for sudden death that you
just mentioned, I would like to ask Dr. Jonathan Fox, who is the
cardiologist at Merck, to respond to this question.

DR. FOX: Thank you, Dr. Shahinfar. My name is Jonathan Fox. I am a
cardiologist with cardiovascular clinical research, Merck Research Labs.
I will try to address the question. If I could have slide 1228, please.

Just to remind members of the committee, you have already seen these
data. These are the data described in the cardiovascular composite
endpoint and the components, and I believe you\'re most interested, as
Dr. Lorell already pointed out, the cardiovascular deaths. What I\'m
going to try to do over the next few slides is to walk you through all
of the adjudicated causes of death, and to focus on those that were
adjudicated as cardiovascular causes.

This table shows you a breakdown of the adjudicated causes of death by
the Endpoint Committee on the entire intention to treat population.
Those causes were adjudicated into the following categories: fatal
myocardial infarction, known non-cardiovascular cause. In other words,
that included categories of non-cardiovascular death, for which there
were sufficient data or other clinical information to allow the Endpoint
Committee to come to that conclusion.

There was a category of \"not determined\". There were other cardiac
causes, and those could include arrhythmia, for example; other vascular
causes, including hemorrhagic death, progressive heart failure, and the
category of sudden cardiac death, which Dr. Borer has already pointed
out. There was a numerical imbalance in favor of placebo 45 deaths
compared to 30 in the placebo arm, for a total of 158 deaths in the
losartan arm and 155 deaths in the placebo arm, which contributes to the
overall Kaplan-Meier curve you saw earlier, which were almost entirely
superimposed.

Next, please, 1231. This is a subset from that same table, so the totals
are different. These are Endpoint Committee adjudicated causes of
cardiovascular death in the entire intention-to-treat population.

So, again, the categories are exactly the same as you saw in the
previous slide, except that the non-cardiovascular causes have been
omitted. The upshot of this slide is in the last category of \"sudden
cardiac death\", where, again, you see 45 deaths in losartan and 30 in
placebo. But in terms of the percentages, those have now been boosted by
the removal of the non-cardiovascular deaths, so that the sudden cardiac
deaths comprised 50 percent of those adjudicated causes of
cardiovascular death in the trial, compared to 38 percent.

1232 please. Now, I think it\'s important at this point to point out
what the definition was of sudden cardiac death that was used by the
Endpoint Committee to adjudicate these cases of patients who died. If
there were insufficient clinical information or other supporting data
for the Endpoint Committee to categorize patients\' death events as one
of the other categories of cardiovascular death, for example, fatal
myocardial infarction, those patients were adjudicated as sudden death,
regardless of what the actual mechanism might have been. There just was
not sufficient information.

So, the definition of sudden cardiac death in a way becomes a default
category when there is a lack of specific information. So, that included
any death occurring without warning, any death occurring within 24 hours
of new symptoms, and any unwitnessed death at home.

Let me just pause there and ask if that satisfies Dr. Lorell and Dr.
Borer, if that answers the question.

DR. BORER: Dr. Lorell.

DR. LORELL: Thank you. That\'s very helpful. Just to be very clear to
me, because I didn\'t see either of those two tables in our briefing
books, could you just restate, of the total deaths in the losartan and
placebo groups, what percent of total deaths in each group was
cardiovascular?

DR. FOX: I believe we can get that information from 1230. There were 90
cardiovascular deaths in the losartan arm out of a total of 158. There
were 79 cardiovascular deaths out of a total of 155 in placebo.

DR. LORELL: Thank you.

DR. ARMSTRONG: I found this safety presentation very helpful. Thank you.
As an entree to my question, I just want to recap my understanding and
focus on hyperkalemia and the relationship between hyperkalemia and the
endpoint, i.e., transplantation or dialysis. As I understand it, 1 out
of 4 losartan patients and 1 out of 8 placebo patients had hyperkalemia,
and 1 out of 10 losartan patients had hyperkalemia in excess of 6, and 1
out of 20 placebo patients had hyperkalemia in excess of 6.

As I understand it, also, this hyperkalemia was perceived to be
clinically manageable, and none of this hyperkalemia was perceived to
have related to death, notwithstanding the chairman\'s caveat.

My question is, if you look at hyperkalemia, all comers, what proportion
of those patients went on to dialysis or to transplantation in the
context, as Dr. Kopp pointed out, of that being a meaningful indication
for that endpoint, and what proportion of the losartan versus the
placebo hyperkalemia led to the development of that endpoint?

DR. SHAHINFAR: We can get that information for you. We haven\'t looked
at the relationship between hyperkalemia and initiation of dialysis, if
I understand your question correctly. We can look into that and get back
to you.

DR. KEANE: I think one has to recognize that our values of potassium
that were determined were determined on a regular interval, and actually
dialysis, as you\'re rightly pointing out, is a therapeutic intervention
that may occur. So, our ability to measure potassium immediately prior
to the initiation of dialysis is really not within the design of the
trial. So, we really don\'t have that kind of information those kinds of
patients that are actually starting dialysis, to define whether that was
truly an indication for initiation of dialysis. I don\'t think we\'re
really going to be able to adequately define with precision and clinical
reliability the exact answer to your question.

DR. BORER: Dr. Kopp?

DR. KOPP: Just to clarify ‑‑ if a nephrologist had a potassium come back
of 6, he could call the study and say, tell us if the patient is on
losartan or not, and he would have the option of stopping the study drug
‑‑ well, I guess at that point they would come off the study in either
case. But that would be an alternative to putting the patient on
dialysis.

DR. SHAHINFAR: They managed patients as they would manage these patients
in their clinical practices. Only 6 patients were unblinded throughout
the study, so we did not unblind every single hyperkalemia in the study.
It was not actually the reason for unblinding. Is that the question
you\'re asking?

DR. KOPP: Is that because the physician never contacted the study, or
they weren\'t allowed to ask that question?

DR. SHAHINFAR: No, they were allowed to ask any question, but they never
asked that question. In fact, the reason for unblinding those 6 patients
was not by the investigator; it was by a cardiologist. The patient had
heart failure, MI, and they asked for the unblinding so they could make
a clinical decision in that patient.

Hyperkalemia was overall managed. We had guidelines in the protocol of
how to handle hyperkalemia, and people were used to handling these
patients with hyperkalemia and underlying kidney disease. So, they used
potassium lowering agents in both treatment groups.

DR. BORER: Just for clarification, in the FDA briefing document there is
a table that presents all the patients who were unblinded, so we have
that information.

Let me just remind the committee or ask the committee, because there
will undoubtedly be some discussion as we move forward through the
summary here, if you want to say something and you press the button on
your microphone, the light comes on and I catch it immediately. We\'ve
taken care of 99 percent of the problem that we\'ve had by shifting the
table so you don\'t have to break your neck to see the slides. But what
that does is cause everybody to focus on the slides instead of on the
hands being raised. So, if you press the button that will make it easier
to recognize whoever wants to talk.

DR. FOX: Jonathan Fox, Merck Research Labs.

Mr. Chairman, if I could just expand just a little bit on the death
issue. I think this will also perhaps anticipate the intersection
between the concerns of several of the committee members, in terms of
the relationship between hyperkalemia and sudden death, which I believe
you raised yourself earlier. If I could have 1236 please.

This slide is a table of some selected laboratory test results that were
associated with patients who died in the trial, specifically patients
who were categorized in that adjudicated category of sudden cardiac
death that I explained a moment ago.

The first column is the last central lab measure that was obtained prior
to death, and I\'ll tell you something about that time interval in a
moment. It is broken down between the losartan arm and the placebo arm.

We have included some laboratory measures that I think are relevant in
this patient population who is quite ill in the trial. It would be the
serum potassiums and the serum bicarbs, blood glucose, in this diabetic
patient population, the serum creatinine, and the urine protein.

The conclusion I would like to leave you with from this slide is that in
terms of overall means, for what that\'s worth, the potassiums were in
the normal range at that last central lab visit. The bicarbs were near
normal. Blood glucose was reflective of this diabetic population, but
not indicative of hypoglycemia. Serum creatinines indicated that these
patients were well along the way in their nephropathy, and that\'s also
reflected in the means urine protein.

Could I have 1237? This table shows you the results of the deaths of any
cause of death in patients, and their potassium results if they had a
potassium result less than or equal to 3.5 milliequivalents per liter at
any point during the study.

So, in the losartan arm there were 70 patients who fell into that
category and 90 in the placebo arm. Those are all patients who had that
measurement. There were 12 patients in that category who actually died
during the trial and 11 in placebo. 10 of the 12 in losartan were
categorized as 1 or more causes of cardiovascular death, and 3 of those
10 as sudden cardiac death. 2 of the 11 patients who died in the placebo
arm were cardiovascular deaths, a 1 of those was a sudden cardiac death.

Also on this next slide, these are investigated causes of death in those
same patients who had any measure of potassium less than or equal to 3.5
at any point during the study.

So, I want to emphasize that, independent of what the adjudication was
of the Endpoint Committee, again, they relied on a strict set of
criteria that had to be satisfied by a sufficient body of information
for them to adjudicate a particular death to one of those categories
that I showed you earlier. So, if there is insufficient evidence
available to them, many of those patients were categorized as sudden
death.

So, independent of that adjudication, this table shows you clinical
information that was obtained from the CRF narratives entered by the
investigator. As you can see, there is quite a broad collection of
different diagnoses without any particular pattern that I can discern
for you in this table.

Now, this takes a look at the same kind of an examination of the
information that we have, but looking at patients who had a measurement
of potassium greater than or equal to 6 milliequivalents per liter at
any time during the study. There were 123 patients in the losartan arm
and 61 in the placebo. Of those patients, of the 123 in losartan, 23
patients died, 7 of those had a cardiovascular death, and 4 of those
were adjudicated as sudden cardiac death. 61 patients in placebo had the
results of a potassium greater than 6. 13 of those patients died. 6 of
those had a cardiovascular death, and 2 were categorized as sudden
cardiac death.

This is a similar table to what you saw a few slides ago. The
investigator reported causes of death in patients with a potassium
result greater than or equal to 6 at any time during the study who were
adjudicated as cardiac death. Again, it contains quite a broad range of
diagnoses without any particular pattern.

I promised you that I was going to show you some information that
related the measurement of serum potassium to the time interval between
when that last laboratory measure was obtained and when the patient
actually died.

What this plot shows you on the ordinate is the last potassium value
that was obtained that went to the central laboratory, and on the
abscissa, the time in days to the death event from that last
measurement. As you would expect, there is a scatter of those data, both
in terms of the values of potassium on the y axis, and a scatter with
respect to time on the x axis.

The legend is shown underneath the title of the slide: in yellow,
losartan; in white, placebo. The circles are patients who were still on
study therapy at the time they died. The triangles are those were off
therapy at the time they died. In fact, there was a group of patients
you might consider outliers and just in anticipation of the question as
to what happened to those 2 patients who had values at or near 6 or
above at the time they died and close in time to the time they died.

This is a listing of some clinical characteristics of those 2 patients.
The first patient, allocation number 4141, was a patient who had already
achieved end-stage renal disease and was on dialysis. This laboratory
result was obtained approximately 6 days prior to death. It was obtained
immediately prior to the dialysis session.

Concomitant medications the patient was taking are listed there; and
concurrent condition, as I mentioned, the patient already had end-stage
renal disease.

The other patient, allocation 4455, had the laboratory measure taken
approximately 4 days prior to death, was on the medications you see
listed there. Of note, the patient had chronic acidosis as revealed by
the serum bicarb measurement that was obtained at the same time.

Is that helpful to the committee?

DR. BORER: It is to me. Let me ask you one more question before we get
to the summary. You know, I am a cardiologist. I don\'t know much about
endocrinology, but you have a lot of fire power sitting there.

It was interesting to me that on losartan and on placebo, although the
frequency of hyper- and hypoglycemia was not statistically significantly
different in the two groups, there was a different direction in the
trend of the events; that is, hypoglycemia up in one, and hyperglycemia
up in the other group. Although statistical significance wasn\'t
reached, and in fact, even the nominal criterion for a statistical trend
wasn\'t reached ‑‑ the p values were both about .12 and .15, ‑‑ still,
the fact that they were directionally opposite was interesting to me. Is
there any reason why losartan should affect blood glucose differently
than placebo?

DR. HAFFNER: This is interesting. I\'m not sure it\'s going to be
resolved, but I\'ll tell you what I believe. I was one of the PIs in the
diabetes prevention program. This is an area we\'re interested in.

First of all, the data you\'ve seen is among deaths. So, it\'s not truly
representative of the overall population.

The hemoglobin A1Cs during the trial did not differ, and that suggests
to me there may not have been a major effect.

On the other hand, there\'s some very interesting literature with both
ACEs and now with ARBs, that maybe these agents could prevent type II
diabetes.

Now, the mechanism is, again, kind of interesting. There is one report
of losartan improving insulin sensitivity, but it\'s a relatively small
study, and it clearly needs to replicated.

So, I think the safe answer would be that the data within this trial
does not provide strong evidence for a glycemic effect. There is a
related trial we haven\'t talked about, which did sort of quasi show an
effect relative to atenolol, but it could have been the atenolol or it
could have been the losartan. And there are certain equivalent data with
captopril. I think it\'s not quite resolved at this point.

DR. SHAHINFAR: Just answering, glycemic control was comparable, and
glucose levels were comparable between the two treatment groups
throughout this study.

DR. LINDENFELD: JoAnn Lindenfeld. I\'d like to just ask a couple of
questions before you finish.

Patients were withdrawn from ACE inhibitors, about half the patients in
this study as I understand it. There was a 6-week period between
withdrawal and randomization. Am I correct there?

DR. SHAHINFAR: Yes.

DR. LINDENFELD: Can you assure me that those groups were equal in the
randomization ‑‑ in other words, patients who were withdrawn from ACE
inhibitors were equal in both groups?

DR. SHAHINFAR: Yes. There was an equal number of patients in each
treatment group.

DR. LINDENFELD: For my interest, and just a quick answer if you have it
‑‑ if not I don\'t desperately need it ‑‑ is there a difference in the
results of the study in patients who were previously on ACE inhibitors?

DR. SHAHINFAR: There is no interaction between losartan treatment and
use of ACE inhibitors on the primary outcome of the study.

DR. LINDENFELD: I don\'t mean the use of ACE inhibitors during the
study.

DR. SHAHINFAR: At baseline, that\'s right. And that\'s in the background
that we provided.

DR. LINDENFELD: Okay. For clarification, when we come back to discuses
cardiovascular endpoints, I know there were a number of exclusions here
with recent MI, et cetera. Can you give me a percentage of patients who
had had a cardiovascular endpoint at baseline prior to randomization? In
other words, what percentage of patients in this trial had had some
previous cardiovascular endpoint? I know MI was excluded within 6
months, but how many patients had had a distant cardiovascular endpoint
of some type? Again, I\'m just trying to get at the risk of this group.

DR. SHAHINFAR: This is the history for myocardial infarction, angina,
stroke.

DR. LINDENFELD: So, less than 1 percent had had a previous
cardiovascular event?

DR. SHAHINFAR: Yes, that\'s right.

DR. LINDENFELD: Okay. That\'s 12 percent. I\'m sorry. Right.

DR. CARABELLO: What was the mean time to difference in endpoint? The
time difference. In other words, the losartan delayed the endpoint. What
was the difference in time between when patients reached the endpoint?

DR. SHAHINFAR: Our analysis was a time-to-event analysis. In the study,
during the 3-and-a-half years period of follow-up, we were able to
demonstrate that for every 16 patients treated, 1 ESRD was delayed
basically or was prevented.

DR. BORER: But Blase is asking a different question, which is of
interest, although I understand that it\'s difficult to draw firm
inferences since some people didn\'t ever have an endpoint. Among those
who had an endpoint, what was the average time to endpoint in the
placebo group versus the average time to endpoint in the losartan group?
Do you have that? I think there is something in the FDA briefing
document about it. Do you have those numbers?

DR. KEANE: That\'s actually a relatively difficult number to calculate
as you would imagine. I think as Dr. Shahinfar has already indicated,
what was easier to identify and to calculate is really the number needed
to treat, which was 16 patients needed to be treated to prevent 1 case
of end-stage renal disease.

We were also able to demonstrate that we reduced overall end-stage renal
disease days by some 32 percent in the losartan group. So, that gives
you an estimation of the impact.

Considering the fact that the diabetic patient today represents almost
40 percent of end-stage renal disease, and we have already projected by
the end of this decade that it\'s going to up to 50 percent, that\'s a
substantial impact I think from a public health perspective.

DR. CARABELLO: I\'m still not clear. We have X number of patients that
reached an endpoint on losartan, and X number of patients that reached
an endpoint on placebo, and each patient reached that endpoint in a
certain number of days from when he or she began the study. My question
is, what\'s the difference in days or months between those two
endpoints?

DR. KEANE: I think we can go ahead and get that analysis for you in a
little bit more specific way. I don\'t have the exact answer right now
beyond what I\'ve given you, but we\'ll provide that in a moment or two.

DR. CARABELLO: Thank you.

DR. FLEMING: Yes, I think it\'s in the statistical review and evaluation
hand out. I think what you\'re looking for is on page 8, which is best
obtained with a Kaplan-Meier estimate of time-to-event distribution. Is
that what you\'re looking for? The difference in the median times to
events by Kaplan-Meier estimates?

It is on page 8 of the statistical review and evaluation, and the
numbers here are 1,303 days versus 1,373 days. It does raise another
methodologic issue that I\'d like to pursue, but I\'d be happy to delay
that. I don\'t need to discuss it yet.

DR. BORER: Dr. Kopp?

DR. KOPP: I had a question on the same point, and maybe, Tom, this is
what you\'re going to get at. As I understand, that was the primary
proposed method of analysis, the time to event. The slide you showed
this morning talked about time to event, but then you actually gave risk
reduction of 16 percent and p .022.

I notice in this table on page 8, that it also gives p .022. So, again,
it may be my statistical ignorance, but both are ways to look at time to
event? Am I being clear?

DR. BAIN: I\'m not sure I understand the question.

DR. KOPP: I\'m confused about when you started out saying this was going
to be a time-to-event analysis, and then the slide that kind of captured
the key data was actually risk reduction. I had the same question you
did: what was the actual data? Now I see it on page 8 of the FDA
analysis with the same p value.

DR. BORER: I think we may be getting into sort of a semantic issue.

DR. FLEMING: This is the slide to show. There really are two separate
analyses that are being done. One is where do these two curves cross the
50 percent line, which is basically a difference in median time to
event. And another very mainstream analysis ‑‑ it\'s really a separate
parameter looking at treatment effect ‑‑ is to say suppose there\'s an
underlying failure rate over time on the control arm, and suppose the
intervention arm alters that by a multiplicative constant, the hazard
ratio. What is that reduction in relative risk? And that\'s what the
hazard ratio is, and that\'s a 16.1 percent relative reduction in the
failure rate. So, those are related, but those are, nevertheless,
separate measures of treatment effect.

DR. KOPP: So, is it by chance that they\'re both .022, or is that
inherent in the way these statistical tests are done?

DR. FLEMING: The p of .022 I\'m sure relates only to this analysis of
hazard ratio estimates in the confidence interval. We rarely test that
difference in medians as the basis for statistical p values. The p
values that you see are going to be based on the proportional hazards
model and the estimate of the relative risk, the confidence interval,
and the corresponding significance from that.

DR. BORER: Dr. Temple.

DR. TEMPLE: Tom, help us a little more. It\'s common in representing the
results of a study to give the total number of events, because you can
work with that. You know what that means. Whereas, Kaplan-Meier curves
are sort of something that doesn\'t have a number attached to them. You
just have to look at them.

But you could apply a hazard ratio risk reduction statement either to
the total number of events, sort of independent of time ‑‑ some studies
do that ‑‑ or you can do it this way, which as I understand it, is the
risk reduction or hazard ratio of the likelihood of getting an event in
a given time or over the entire course of the study. The hazard ratio is
a time-related function as usually presented in these analyses.

DR. FLEMING: There are many different measures that we could use to
assess the nature of treatment effect and the strength of evidence that
it\'s been an established effect.

The most traditional or most common analysis in a time-to-event setting
is to say we\'re going to make no assumptions on the nature of the
failure rate on the control arm. We\'re only going to make an assumption
that if treatment affects that failure rate, it does so in a
multiplicative fashion. It reduces the failure rate by some
multiplicative constant, that is constant over time. That\'s what
proportional hazards mean. If treatment reduces the failure rate early
in time by 16 percent, we\'re going to assume it\'s reducing it late in
time by 16 percent. What is that percent?

That is the fundamental common analysis. It\'s called the log rank test,
the Cox regression. Those are all based on that same fundamental
principle. Essentially almost all estimates that we would see, which is
the relative risk or the reduction, is based on that hazard ratio
estimate, with confidence intervals and p values.

Now, there are other analyses that we could do. You can look at total
numbers of events. I like to look at that as well as just a descriptor.
You could look at the differences in rates at a given time, so you might
say is what I really care about is, is there a difference in these
events at 2 years? In which case, I would look at the difference in
Kaplan-Meier estimates standardized by Greenwood variance estimates.
That\'s a different analysis.

Another analysis is to look at the medians. It\'s a good descriptor,
although I tend to favor the proportional hazards analysis because the
medians is only telling you how the curves separate at one place,
whereas the proportional hazards analysis is looking at a weighted
average of what the nature of the effect is on the outcome failure risk
over the entire duration of the curve.

DR. BORER: Still, Blase is raising a point that we really haven\'t
discussed that I think is very important. If I am understanding
correctly, the time-to-event analyses that have been done show us that
there is a significant effect by this analysis and that the magnitude of
the effect ‑‑ that is, the failure rate ‑‑ is a reduction of 16 percent.
Blase is saying, what does that mean to the patient? You know, 73 days
more of dialysis? 73 less days?

DR. CARABELLO: Yes. As sort of the dull normal on the committee ‑‑

(Laughter.)

DR. CARABELLO: ‑‑ that was really the intent. If I start a group of
patients on this medicine, by how many days will I delay an endpoint?
Specifically, that\'s the question I\'m asking.

DR. FLEMING: If these curves were exponential, and they are not ‑‑ but
if they were ‑‑ then a 16 percent reduction in the failure rate would
translate into a 16 percent extension in the average duration of time to
when the event occurs.

DR. BORER: Good. Well, we\'ve got that one settled for the moment. Ray,
did you have anything else you wanted?

DR. BAIN: Just as Tom mentioned, the counts are in your background
document by the two treatment groups. Our analysis is that 16 percent is
based on the Cox regression hazard, with the prespecified adjustment for
baseline proteinuria stratum and region.

DR. FLEMING: There is one methodologic issue here that I\'d like to
pursue at least briefly. It doesn\'t trouble me greatly, and I\'ll
preface my comments by saying that the reason it doesn\'t trouble me
greatly is because ‑‑ at least as I noted back in January ‑‑ I\'m much
more persuaded by end-stage renal disease/death as a dual endpoint than
the primary specified doubling in creatinine/end-stage renal
disease/death as a triple endpoint. I am even more persuaded that\'s the
case here because of my understanding of the way follow-up was done, and
I\'d like to at least clarify to make sure my understanding is correct.

I am absolutely delighted to hear, by my understanding, that all
patients were followed until the outcomes for end-stage renal disease
and death. So, we have complete information on the endpoint that I am
referring to as my preferred endpoint, that dual endpoint.

But there were a number of people who had a termination of their serum
creatinine assessments prior to the time that any of those endpoints,
i.e., the triple endpoints, prior to the time that either a doubling of
end-stage renal disease or death occurred. So, they hadn\'t had any of
those three components as yet.

Those people were in fact, though, followed for subsequent assessments
of end-stage renal disease and death. So, the analyses that we get for
the endpoint I care most about are fully valid and are perfectly fine,
in spite of the concern I am about to raise.

My understanding is for the triple endpoint, though, in those cases ‑‑
and if I understand there were 130 of those people on losartan and 137
on placebo ‑‑ 267 ‑‑ so about 17.6 percent of our cohort were people who
did have cessation of assessments of serum creatinine before a triple
endpoint occurred and were subsequently followed for the other elements.
They are included in your primary analysis.

In essence, in those 267 people as you are continuing to follow them,
we\'re really underestimating the subsequent rates at which the triple
endpoint occurs, because we\'re only using the double endpoint
assessments in those people. Now, of course that\'s happening in both
treatment arms. So, both treatment arms are being underestimated.

But then when questions come up from my colleagues about how do we
interpret the extension in time or delay in the triple endpoint, I
can\'t interpret that anymore, because I haven\'t followed people for
the triple endpoint. I followed some for the triple endpoint, but 267
people were followed over a substantial duration only for the double
endpoint.

Of course, I don\'t care that much about the triple endpoint. I like the
double endpoint. So, this is no problem for me on the double endpoint.

(Laughter.)

DR. FLEMING: But it makes me even more worried about interpreting your
data on the triple endpoint. Am I off target here or is my
interpretation correct?

DR. BAIN: Your interpretation is correct. What we\'re focusing on right
now are those patients who discontinued their therapy, their blinded
therapy, prior to one of those triple endpoint events. Once those
patients discontinue their primary therapy, their follow-up could be
classified into one of three groups.

Either they continue their quarterly measurements, which was by
protocol, and we continue to get serum creatinines, a potentially
documented doubling, which they get counted in the intention to treat
analysis. That\'s one bucket.

The other bucket is, as soon as they discontinue their therapy, they go
into what we classified as telephone follow-up, where during telephone
follow-up we\'re not collecting serum creatinines.

The third bucket is patients discontinue their meds. They go into clinic
follow-up for a period of time, and then they go into telephone
follow-up.

With those three kinds of different classes, it\'s difficult to really
give you a number as to how much is in telephone, et cetera, but we
attempted to. What we did was look at the total follow-up time after
discontinuation of their study therapy and determined patient years of
follow-up from that time of discontinuation of therapy. Then we also
calculated what percentage of that time was in clinic follow-up versus
what percentage of that time was in telephone follow-up. We estimated
that, and 60 percent of the follow-up post discontinuation of the study
therapy is 60 percent. 60 percent are followed in clinic that time.

So, that gives you a general idea of how we are following those patients
post discontinuation of the therapy. Obviously we continued to follow
them for the hard endpoints.

Now, when we go ahead and do that triple endpoint intention to treat
analysis, what we are actually doing is what I would consider to be a
conservative analysis, because we\'re not documenting doubling in either
group, so we\'re assuming that any effect that losartan would have would
be the same in the losartan and the placebo group after discontinuation.
So, our triple endpoint, even though we had 40 percent of the patients
in telephone follow-up, actually the analysis is holding up mainly
because it\'s conservative.

DR. FLEMING: Just a brief addition to what you were saying. The only
conclusion I am confident to make here is, in these 40 percent of the
person years of follow-up time after discontinuation, where we no longer
continue to follow the triple endpoint ‑‑ we\'re only following the
double endpoint ‑‑ if you really care about the triple endpoint ‑‑
we\'re underestimating in both arms the time to the occurrence of the
triple endpoint.

Whether that leads to a conservative or anti-conservative estimate of
treatment effect entirely depends on in these people who are
discontinued for follow-up of serum creatinine doubling times, in those
people who are discontinued, would the doubling time have occurred more
rapidly in the placebo versus the losartan arm? I have no clue about
that.

So, it leaves me uncertain about how to interpret the data, to an extent
at least, if I really care about the triple endpoint, because, again, in
40 percent of the person-years of follow-up after discontinuation ‑‑ and
after treatment discontinuation I do care to continue to follow people
‑‑ I might surmise that I would have less treatment effect after
treatment discontinuation. I don\'t know. That\'s only a guess. But I do
care, if I really cared about the triple endpoint, to know what time is
to triple endpoint in all patients.

My conclusion in this is that there are 267 people, balanced by
treatment arm, in whom I am underestimating the time to the triple
endpoint in both arms. I have no clue if it\'s more so in one than the
other, and it\'s just another reason that from my perspective the double
endpoint, which occurs in this setting not that much later than the
triple endpoint, and is clinically a much harder endpoint, and is free
of all of these problems, is an endpoint that I particularly would focus
on more so than the triple endpoint.

DR. BAIN: Correct. Let me make one other point. When we are talking
about these patient-years of follow-up and we\'re talking about the
triple endpoint, if you actually calculate the patient-years of
follow-up in clinic over the whole time, not just focusing on those
patients who discontinued their therapy, the clinic follow-up is over 90
percent. It\'s only when you get into that subset of patients that it
drops to 40 percent.

DR. BORER: Dr. Lorell.

DR. LORELL: Thank you.

In follow-up of Dr. Fleming\'s comments, there were two queries that I
had. One is, in this difficult group of the 40 percent patient-years who
have the issues of discontinuing treatment and problems of telephone
contact, do you know what percentage of those patients in each of the
intention-to-treat groups actually got put on an ACE inhibitor by their
clinical nephrologist? Is that known?

DR. SHAHINFAR: We know for the entire cohort those patients who were
discontinued from the study, and they were placed on ACE inhibitors or
AII receptor antagonists. I have to remind you that this collection of
the concomitant medication was extremely difficult after a patient was
discontinued from the study.

DR. LORELL: I understand that.

DR. SHAHINFAR: So, it\'s going to be either underestimation or ‑‑ the
data that we have ‑‑ can I have that?

DR. LORELL: Perhaps you can get that to us in a little bit.

DR. SHAHINFAR: This is basically those patients who discontinued the
study drug, and we have information on them that they went to either ACE
inhibitors or angiotensin II receptor antagonist therapy.

DR. LORELL: That\'s very helpful.

The second question I had that relates to Dr. Carabello\'s efforts to
understand the clinical impact. In our briefing supplement that we were
provided with in table 1-A, there is a comment about the median time to
reach the triple event, but we\'re not provided with data, I don\'t
believe, that might address Dr. Carabello\'s concern and mine too, as to
what the median time is in the losartan and placebo group of reaching
end-stage renal disease or reaching the double endpoint. Maybe we could
be provided with that.

DR. BAIN: Ray Bain, Merck Research Labs.

Now, Tom kind of caveated around doing this but we did calculate the
number. If I understand the question, it\'s of the patients who reached
a primary composite endpoint event, which there are 327 in the losartan
group and 359 in the placebo group, if you actually calculate the median
number of days to the event, it\'s 652 days in the placebo group and 724
in the losartan group.

So, there is a delay, but that\'s a subset of the patients. You\'re just
looking at those patients who actually had the event, ignoring all the
other patients, which, if you do the median analysis and go across the
median and drop it down to your time line, you\'ll get estimates of
differences in time.

DR. BORER: That\'s for the double endpoint?

DR. BAIN: That was the triple endpoint.

DR. LORELL: That\'s different from the table.

DR. BORER: Yes. Maybe you can pursue this just a little bit.

DR. LORELL: In the table 1A that we were provided, the number is
actually quite different, but I would also be interested in following up
Tom Fleming\'s comment that I think for many of us the important issue
is end-stage renal disease/death ‑‑ what the median time was for
reaching that double endpoint. Do you have that data?

DR. KEANE: Again, are you asking the median time for doubling, or are
you asking the median time for end-stage renal disease?

DR. LORELL: No. We\'re provided in table 1A with the median time to
reach the triple endpoint. In follow-up of Dr. Fleming\'s comment and
Dr. Carabello\'s, can we know what the median time is to reach end-stage
renal disease and the median time to reach end-stage renal disease or
death.

DR. KEANE: I think we can go back and calculate that. We just don\'t
have that immediately on our data set here, so we\'ll find that out and
get back to you.

DR. LORELL: Thank you, sir.

DR. KOPP: Could you explain the discrepancy that your last question just
brought up between the median time to event in our table of about 1,300
days for the two groups, and the median time of about, I think you said,
about 650 and 704? This is in both cases the median time to the
composite endpoint, triple.

DR. FLEMING: I think I might be able to, while you\'re bringing somebody
up. The distinction between the two ‑‑ the Kaplan-Meier is the 1,300,
whereas I think the analysis of the 700 was if you just take the people
with the event, what\'s the median time at which that event occurred.
And that\'s always going to be a lot less. That was 700.

DR. BAIN: Yes.

DR. FLEMING: And I would caution against ever looking at that because
it\'s very misleading.

What I really care about is what\'s the Kaplan-Meier? What\'s the
percent free of having an event? If I have two treatment arms, and
let\'s say in one treatment arm 10 percent of the people have an event
at a year, and in the other treatment arm, 10 percent have an event at a
year, and another 10 percent have an event at 2 years, the latter is a
worse scenario. And yet the median time to event in the latter case is a
year and a half, whereas it\'s a year in the first arm.

So, I don\'t want to look at, given you\'ve had an event, what\'s the
time to event. I want to look at the entire cohort and see what\'s the
percent free of the event and what\'s the time at which that crosses the
median. That\'s the 1,300 type number

DR. SHAHINFAR: In summary, in type II diabetic patients with
proteinuria, there were no unusual or unexpected adverse experiences
beyond those already noted in the U.S. prescribing information for
losartan. Losartan had a higher incidence of hyperkalemia, and lower
incidence of hypokalemia compared to placebo. Losartan was generally
well tolerated.

I would now like to introduce Dr. William Keane, Vice President of
Clinical Development, Merck U.S. Human Health. Dr. Keane will provide
the review of evidence and conclusions regarding the renal protective
effect of losartan in type II diabetes. Thank you.

DR. KEANE: Thank you, Dr. Shahinfar.

Members of the committee, representatives of the FDA, other invited
guests, ladies and gentlemen. My name is Bill Keane, and I\'m delighted
to have the opportunity to appear before the advisory committee again in
my new capacity.

As many of you know, I have recently joined Merck as Vice President of
Clinical Development in U.S. Human Health after 28 years in an academic
practice of nephrology.

Most recently I was professor and chairman of the Department of Medicine
at Hennepin County Medical Center at the University of Minnesota in
Minneapolis. I was intimately involved with the RENAAL study, both as a
member of the Steering Committee, as well as a primary investigator, and
participated in the design, the conduct, the oversight, the analysis and
publication of this important study.

In addition, as President of the National Kidney Foundation, which is a
patient-focused organization, I can assure you that we have recognized
that the treatment of the type II diabetic patient with proteinuria is
an unmet medical need.

I would like to provide you with my summary that emphasizes the salient
features of this study that make it a compelling data set supporting our
proposed indication.

The strength of the evidence provided by the RENAAL study is sufficient
to support our conclusions, based on a number of critical features,
including the robust study design, the results that are clinically
important, as well as statistically significant, and the presence of
internal consistencies across multiple endpoints and multiple subgroups.
Moreover, as you\'ve seen, after adjusting for differences in relevant
patient characteristics, particularly the chance imbalance that was
observed in baseline proteinuria, an even more dramatic impact can be
seen.

First, let me re-emphasize that this was a large, multinational study
conducted in 28 countries at 250 clinical sites. It included a diverse
study population, with demographics of patients with type II diabetes
here in the United States. There were no patients lost to follow-up in
terms of ascertaining their clinical status with respect to end-stage
renal disease and death. The key renal endpoints and cardiovascular
endpoints were independently adjudicated. Furthermore, there were no
patients missing from our intention-to-treat analysis for the primary
composite endpoints.

I would now like to review the main study results in order to emphasize
the internal consistencies and reliability across the multiple endpoints
and subgroups of the study.

RENAAL provides persuasive evidence that losartan delays the progression
of kidney disease in type II diabetic patients with proteinuria, as
demonstrated by the following results.

The primary composite endpoint of the time to the first event of
doubling of the serum creatinine, end-stage renal disease or death,
which revealed a risk reduction of 16 percent, with a p value of .02.

The clinical endpoint of end-stage renal disease, which revealed a very
robust risk reduction of nearly 29 percent. Again, I\'ll emphasize in
this particular clinical component, there were 147 events of end-stage
renal disease in the losartan group and 194 end-stage renal events that
we observed in the placebo group.

The clinical endpoint of end-stage renal disease or death, which also
showed a significant risk reduction of nearly 20 percent.

Our prespecified subgroup analyses, which included those performed for
age, gender, and a variety of other categories, demonstrated that
losartan provided renal protection across a wide range of patient
subgroups.

Dr. Shahinfar has already reviewed with you that we stratified patients
by baseline proteinuria, either those below 2,000 milligrams of albumin
per gram of creatinine, or above 2,000 milligrams of albumin per gram of
creatinine.

Despite this, we observed an imbalance in the distribution of baseline
proteinuria values between the treatment groups, particularly within the
higher proteinuria stratum. That is, in those patients that had a urine
albumin to creatinine ratio of greater than 2,000 milligrams per gram of
creatinine.

Given that baseline proteinuria was a strong predictor of the risk of
subsequent renal events for patients in both treatment groups, and the
risk dramatically rises for patients with high levels of baseline
proteinuria, it seemed particularly appropriate to adjust for this
observed imbalance.

As you can see in the right-hand column, when we adjusted for baseline
proteinuria as a continuous covariate, these post hoc analyses showed
that the risk reduction for the primary composite endpoint of doubling
of serum creatinine, end-stage renal disease or death improved now to
some 22 percent, with a p value of .001.

The risk reduction for end-stage renal disease improved to nearly 37
percent, and the risk reduction for end-stage renal disease or death
improved to greater than 25 percent.

Thus, these analyses reinforce the conclusions of our primary analyses.

It is critical to emphasize the importance of effective blood pressure
control in patients with type II diabetes and proteinuria. It is well
recognized that patients with type II diabetes and nephropathy either
have hypertension at the time they begin to develop nephropathy or
become hypertensive by the time they reach one of the clinical endpoints
defined in our RENAAL study.

In the RENAAL study aggressive treatment of blood pressure was specified
in the protocol, and as Dr. Shahinfar has shared with you today, the
majority of patients were well controlled in both groups. The
differences in blood pressure between the treatment arms were small, and
our prespecified analysis for the small 2 millimeter differences in mean
arterial pressure did not substantially alter the treatment effect on
the various renal endpoints. This supports the overall conclusion that
the benefits of losartan treatment in this population are not
attributable to blood pressure control alone.

There were additional secondary renal endpoints in the study. These also
provide consistent and persuasive evidence of the treatment benefit of
losartan in this patient population. Compared to placebo, losartan
showed a significant 18 percent reduction in the rate of progressive
loss of kidney function, as estimated by the reciprocal of the serum
creatinine. In addition, we found that, compared to placebo, losartan
also had a significant 34 percent reduction in proteinuria.

Although RENAAL was designed specifically as a renal protection study,
because of the recognized increased risk of cardiovascular events in the
RENAAL patient population, we prespecified the composite endpoint of
cardiovascular morbidity and mortality as an important endpoint. This
composite endpoint included all-cause cardiovascular death, myocardial
infarction, strokes, time to first hospitalization for heart failure,
and time to first hospitalization for angina, and all revascularization
procedures, both within the coronary vasculature as well as in the
peripheral vasculature.

There was no treatment effect demonstrated for the cardiovascular
composite endpoint overall. An examination of the individual components
revealed the expected fluctuations ‑‑ some positive, some negative ‑‑
that led to the nonsignificant p value for the cardiovascular composite
endpoint.

While Dr. Shahinfar has already reviewed these findings in detail and we
have discussed them also in detail, I simply really wish to emphasize
that the benefits of losartan treatment on our renal endpoints did not
come at the expense of an increased risk of cardiovascular events in the
losartan arm. This is probably best illustrated by our post hoc analysis
on the bottom portion of this slide which demonstrated the combined
endpoint of end-stage renal disease, myocardial infarction, stroke, or
death, and this showed a 21 percent risk reduction with losartan.

In conclusion, for patients with type II diabetes and proteinuria, the
specter of inexorable progression to end-stage renal disease requiring
renal replacement therapy is a frightening prospect. Those of us that
have cared for these patients recognize the enormity of disease burden
that is borne by these individuals. In my view, the sum evidence of our
analysis for the RENAAL data that we have shown you today demonstrate
robust, reliable, and clinically relevant evidence that is applicable to
a broad population of type II diabetic patients.

In addition, our data confirm that the safety profile of losartan in
this population is consistent with the U.S. prescribing information for
losartan.

Finally, in patients with type II diabetes and proteinuria, the
treatment effects of losartan across multiple endpoints in the RENAAL
study provide persuasive evidence for the renal protective effects of
losartan. Indeed, we estimated that over a 3-and-a-half year time period
for every 16 patients treated, 1 case of end-stage renal disease will be
prevented. RENAAL provides new data that support the role of the
renin-angiotensin system blockade for renal protection in diabetes and
kidney disease.

Thank you very much for your time and attention.

Mr. Chairman, I was going to just take the liberty, because there were a
number of questions that had come up during the presentation that we
thought we could provide some answers to.

DR. BORER: That would be helpful, but I think on your behalf really we
have some more questions from the committee that may require that you
gather some more data, and it might be nice for you to have the break to
do that. So, let me take the last few minutes before the lunch break to
go to some of these questions. You may be able to answer them now, you
may not. If you can\'t, then you\'ll have a few minutes to get the
information together and we\'ll go back over all the questions after
lunch.

Dr. Nissen, you had some concerns?

DR. NISSEN: Obviously, we\'re all very cautious about subgroup analyses,
but there were, I think, a lot of questions that I had about the
subgroups in the study. I would hope maybe somebody could put of table
14 from the Merck briefing document. That\'s on page 63 for those of you
on the panel that want to look at it. I assume you have a slide with
that because I think there are some issues that it brings up about who
in fact benefits from this therapy. Is that possible?

DR. KEANE: I don\'t have a slide of that directly, but we\'ll get maybe
an overhead.

DR. NISSEN: All right. Well, let me just prime you then with the
questions. When I look at this, what I see is, just in terms of counting
events ‑‑ I understand what we\'re looking at is time to event, but just
counting events ‑‑ there were 78 in the losartan group and 80 in the
placebo group, virtually an identical number, in Latin America. For
Europe, there were 58 in the losartan group and 51 in the placebo group.
There were more events in the losartan group in Europe. In North
America, there were 142 in losartan and 150 in placebo. So, if you look
at the Asia group, the 250 patients in Asia provided virtually all of
the endpoint differences in the trial. I mean, it is very, very
striking.

And I recognize the hazards of subgroup analysis, but it\'s so striking
that I went and I looked at the racial background, which is also in
table 14, and you see exactly the same thing: 40 percent event rate
among African American or black; Hispanic, 55 and 54; white, 40.5 and
43; and then a huge difference in the 250 Asians. So, it does speak to
the heterogeneity of the response and the robustness of the findings.

It looks to me, when I look at these subgroups, that it\'s all driven by
those 250 Asian patients, and I need to understand that better to
understand whether this is, in fact, an effect of this drug that\'s
applicable in the patients that come in my clinic and that we see with
the disorder.

Similarly, if you look at the creatinine data, there\'s also this very
striking disparity where, in fact, there\'s a higher event rate in the
losartan group for those with a creatinine of less than 2, which is by
the way the vast majority of patients, and for the somewhat smaller
subgroup, about a third of patients where the creatinine is elevated,
there\'s a very striking difference.

So, again, not necessarily now, but I really need to understand this
very striking heterogeneity, which I recognize does not rise to the
level of statistical significance with the exception of region, which
does reach statistical significance. But in terms of the point
estimates, it\'s really a striking difference, and I really need to
understand that better.

DR. LINDENFELD: Just to emphasize that, I wonder if maybe you could show
us the creatinine and proteinuria in the Asian region group compared to
the others.

DR. KEANE: If you have time now, I can sort of begin to address some of
these issues because they are obviously important and we obviously
recognize that region, and the equivalence of region and race I think we
need to recognize is different because region is a geographic area that
is quite larger than what actually the ethnicity or racial backgrounds
would be.

DR. NISSEN: But it appears in both columns.

DR. KEANE: Let me then, for purposes of what I think is really sort of
more consistent, look at race at this point in time. We can always go
back to region per se, but I think the racial differences are important
for us to understand because I believe that\'s applicable then
regionally when we start looking at that.

So, let me first reiterate your point, that this was a subgroup
analysis, and we in fact had 18 subgroups, and that in and of itself
creates a set of problems.

The second thing that I would like to actually address is the fact that
there are differences between races and between regions. Specifically
there are differences between our regions or races. Let me have slide
624.

As you recall, when we looked at proteinuria and showed you the risk
that proteinuria has in terms of predicting subsequent events, as you
increase your degree of proteinuria, the amount of hazard or the risk
for a primary event and also the primary events that occur in the
highest group of proteinuria patients dramatically increase. It\'s in
many ways like the old adage that we have in clinical medicine, that is,
10 percent of the people have 80 percent of the events. So, this appears
to be in the area of proteinuria as well.

And this was an important analysis going into the trial that we
recognized. In terms of recognizing, the risk was part of a larger
component of things in terms of risk that we actually prespecified.
It\'s called the risk score, and I\'d be more than happy to get into
that in a moment or two. But we had prespecified our analyses based upon
risks that we thought were important in the patients with type II
diabetes.

We also recognized that proteinuria was one of the most important
drivers of the overall risk, so that we focused on proteinuria because
it\'s a clinically relevant measure. It\'s simple to do.

And already, as you see within this particular slide, there are
ethnic/racial differences within this important risk factor ‑‑ this
progression promoter, as it\'s called ‑‑ between Asians, the black
patients, the Hispanics, and the whites. In fact, the Asian population
had one of the highest rates or highest levels of urine protein
excretion rate, so pushing them, if you will, up the slope of risk for a
renal event.

Now, within the different groups, as Dr. Shahinfar has already alluded
to, there were imbalances in terms of stratification to losartan versus
placebo that also occurred within the trial. So, this is one big issue.

The second big issue that I think is important for us to recognize ‑‑

DR. FLEMING: Before we leave this big issue ‑‑

DR. KEANE: Yes.

DR. FLEMING: Slide 624. Just to interpret, this is at a certain level
relevant. What we\'re seeing is that the Hispanic population, the Asian
population had higher baseline proteinuria. That would lead me to think
that they should have had a higher rate of events.

So, if we go back to page 63, table 14, that explains the relationship
of the events within the placebo arm by country. It explains why the
Hispanics and the Asians in the placebo arm had the higher rate. That
explains that region would be a predictor of rate of outcome.

It tells us nothing, though, about why region should be an effect
modifier, so it doesn\'t answer Steve\'s question unless you want to go
one step further, unless you want to make the statement that not only is
proteinuria a predictor, but it\'s also an effect modifier so that we
would expect higher rates in Asia and Hispanics and we expect a bigger
effect. But those don\'t logically follow to me because they are
different concepts.

DR. BORER: Not only that, we didn\'t see it.

DR. TEMPLE: Yes, you did. If you look at the results by various
underlying factors, almost the entire effect is in the people with
proteinuria over 2 grams. You did see that before. It would be equally
true for 4 grams I\'m sure.

DR. NISSEN: Yes, but Bob, the 277 patients in the Hispanic group who
have the highest proteinuria, there\'s no treatment effect. So, this
doesn\'t make any sense to me. One of the high groups, the Asians, has
all the benefit and a group that\'s even higher with proteinuria has
actually a hazard ratio that\'s worse in the losartan group. So, this
doesn\'t explain anything.

DR. TEMPLE: Well, you have to see how these break down by region as
well. This is not broken down by region because some people in each
region are both. But you did actually see ‑‑ I thought it was fairly
striking ‑‑ that if you look at the hazard ratios, essentially all of
the effect was in the people who were above 2 grams, which could have
something to do with that.

DR. KEANE: Can I go on? Because I think that\'s an important set of
issues here. But I do have, beyond this, some specific, I think,
explanations that we need to see to interpret actually what we\'re
talking about right now.

May I have the next slide? This really then underscores the second
feature that is present that is different amongst Asians or different, I
should say, amongst ethnic groups, racial groups, as well different
amongst the different regions.

But here displayed are really the racial events. As you can see, there
are different levels of discontinuation that are occurring prior to the
first event, so prior to our primary event. Within the Asian group,
there are highly compliant groups of individuals while we have in
caucasian and Hispanics somewhat less compliance or utilization of the
drug. Now, this has an impact, and let me show you the next slide
please, and that should be 627.

If one takes our primary endpoint and just does the evaluation ‑‑ this
is the primary composite endpoint indicated in the dark lines here, the
solid lines with the circle point estimates ‑‑ as you look at those
point estimates and confidence intervals, and then you adjust for those
patients who are on treatment who actually took the drug, and then you
adjust for those patients who were on treatment that had a change in
urine protein excretion rate, as you can see, the point estimates for
the Asians, the blacks, Hispanics, and whites gradually evolve to the
left-hand side of the line of 0, supporting at least the importance of
both proteinuria, as well as being on therapy as modifying this primary
composite endpoint across all races.

This is, again, supported by our overall look at there was no
interaction between races and treatment arms. So, I think this is
supportive and consistent data that shows that we can actually benefit
these renal outcomes in all of our patients of these different ethnic
and racial backgrounds.

DR. BORER: Rather than go on to any other issues ‑‑ I think these were
important slides, and you may have some more that you will want to show
us after the break. Having been stung by the criticism of lack of break
last week and since it is now exactly 12 o\'clock and it says on the
schedule that you can go to lunch at 12 o\'clock, including the FDA
people, 12 o\'clock it is and lunchtime it is, and we\'ll get back
together at 1:00.

(Whereupon, at 12:00 p.m., the committee was recessed, to reconvene at
1:00 p.m., this same day.)

AFTERNOON SESSION

(1:00 p.m.)

DR. BORER: Okay. It\'s 1 o\'clock and 30 seconds, so we\'re a little
late starting here.

At this point there are several unanswered questions and, as yet,
unasked questions from the committee that we\'d like to raise, and I
want to say for all of us to the sponsor that, especially since we\'re
going to move into a period where the questions may become more intense
and the discussion may become more intense, all of us appreciate the
efficiency and completeness with which the sponsor has presented the
data. I know you\'ll have additional information for us, and we
appreciate the superb consultants you brought along to help answer the
questions. So, with that having been said, let\'s move right along here.

Dr. Nissen, you were in the middle of your questions and then we have
several more that I marked down to go back to from other committee
members, and there may be some additional ones as well. Steve, why
don\'t you start?

DR. NISSEN: Thanks very much, Jeff.

I want to continue with this regional and ethnic imbalance and see if I
can explore this a little bit more. But actually before I do, we really
do have a problem here with the FDA data and the company data not
agreeing. Tom, I particularly think I need your help with this.

If you look at the table on region, you see that there are 58 events in
your table in the losartan group and 51 in the placebo group, and the
hazard ratio is .943. Now, I assume that that\'s the case because, even
though there are more events, the time to events would presumably have
been much shorter in the placebo group.

But the same number of events in the FDA analysis on page 22 of the
briefing document gives a completely different hazard ratio. It\'s 1.05.
That\'s a pretty big difference, and I don\'t get it, Tom. Or to the
company, I don\'t understand why they don\'t agree.

DR. BAIN: Yes. This was one of the housecleaning activities that I was
going to come back to.

We went back and looked at the FDA background document versus the Merck
background document. Let me point out that in the Merck background
document, as prespecified in our protocol and data analysis plan,
whenever we do a subgroup analysis, we also adjust for the baseline
proteinuria category or stratum. And when we do that in our analysis,
which is the prespecified analysis, we get our results.

We went back and confirmed that if you eliminate that baseline
proteinuria as a covariate in the analysis, you get the FDA results. So,
theirs is completely unadjusted. Ours is adjusted for what we randomized
on, which was a prestratification factor, which was baseline proteinuria
less than 2/greater than 2.

DR. NISSEN: That helps me a lot.

Again, we can argue about how robust the effect is, but clearly those
250 patients that were in Asia, that are either defined racially as
Asians or geographically as Asians, provided almost all the treatment
effect in the study. That\'s obviously an extremely striking finding.
So, in exploring your data, I was looking for an explanation for that.

I\'d like to ask you if you could show by region the rate of
discontinuation of medication. I have it from the FDA briefing document
on page 16 for the panel members. What is very interesting here is that
there is a huge imbalance between placebo and losartan in drug
discontinuation in the Asian group but not in the other groups. So, I
think potentially this is a smoking gun that explains why there\'s such
a big difference here.

If you look at this, fully 45 percent of the placebo discontinued and 26
percent of the losartan group discontinued; whereas, in the other
regions, there\'s very little difference in discontinuation rate. I\'d
sure like an explanation for that because, again, it\'s a very striking
finding. I think it could explain all of this because if a patient
discontinues, they obviously get less intense follow-up, and I\'m
worried that those discontinued patients had their blood pressures going
out of control and that\'s why we see this. So, many more of the
patients in the placebo arm were discontinued in Asia than in the
treatment arm.

Can you help me with this?

DR. KEANE: Maybe I can. Let me just jump back a little bit to sort of
set the stage. Again, these are all a result of our subgroup analyses
that were done. I want to emphasize two points.

One is the fact that these patients did have differences in proteinuria,
and I did want to emphasize the point that we have differences in
discontinuations, as you\'ve already alluded to.

Now, probably the most important point, in terms of us now looking at
this, will be to look at what, in fact, happened to end-stage renal
disease and death because that\'s where we have captured 100 percent of
all of the events in all of the patients. So, this is very, very, I
think, powerful data for us to look at.

I can show you I think both by region, as well as by race ‑‑ and
recognizing we have these differences in terms of the geography, as well
as compared to ethnicity. So, let me just show slide 629, if I may.

I think as you can see here, this is for end-stage renal disease or
death, which I think we have been discussing this morning as, in fact,
being the hard outcome that is of particular relevance in any kind of
renal protection trial. I think across the board, as you can see in the
solid line, which is our primary analysis, and then as we look at
on-treatment, that is the patients who sustained therapy throughout the
trial, as well as then those patients who were on treatment who had an
adjustment for proteinuria, again this being an important risk for
progression of kidney disease, our point estimates for the different
ethnic groups, again, move slightly to the left of the 0 line, again
favoring losartan. Now, this is by race.

Let me just show you then by region, and I think that\'s slide 850.

DR. NISSEN: You already showed this to us I think before lunch, didn\'t
you? This is the same slide?

DR. KEANE: No, no.

This is ESRD. This is 829. This is ESRD or death. Again, I think the
same events are evident in here, with these adjustments that I\'ve just
gone through, on-treatment, on-treatment, and adjusted.

Now, if we go by region, again by Asia, Europe, Latin America, and North
America, again we believe that there is a shift of the point estimate
more or less to the left, again favoring losartan in all the different
regions.

So, I think that at least gives us confidence in these exploratory
analyses that in fact the direction that we\'re going is correct. It\'s
applicable across multiple groups, multiple ethnic groups, and in fact
across this region that we prespecified as one of our prespecified
subanalyses.

DR. BORER: Dr. Brem?

DR. FLEMING: Can we comment on this before we take off?

DR. BORER: We can, sure. Is this about this particular issue?

DR. FLEMING: Yes.

DR. KEANE: Yes. I was just turning to my colleague now because I think
part of Dr. Nissen\'s question had been related to what happens if you
do the analysis with or without different countries or different
regions, and I was going to ask Dr. Bain to actually address that
specifically because we have done that.

DR. NISSEN: I do want to see it for the unadjusted because I really want
to see the raw data. I want to see the data without all that proteinuria
adjustment and all that. I just want to understand it with the raw data.

DR. BAIN: In that primary analysis up there, the only adjustment was for
what we prespecified in the data analysis plan as being our primary.
It\'s just the adjustment for baseline proteinuria strata, two strata,
and the region.

Now, what Dr. Keane alluded to was the issue that Dr. Nissen brought up
about, gee, all the effect seems to be going away if, for example, you
looked in the regions other than Asia. We were, obviously, interested in
exploring that issue also. Unfortunately, I\'m going to have to put an
overhead slide up here, which is going to be pretty difficult to read,
but let me do that.

What we\'re doing here is we\'re looking for influential either regions
or countries within a region, and I\'ll explain this. I actually have
hard copies for the committee.

Now, what I\'m focusing on there is the composite endpoint of ESRD or
death by the intention-to-treat analysis. And if you remember from the
main presentation, the risk reduction for this particular outcome, ESRD
or death by intention-to-treat, was 20 percent overall.

Now, if you look within a region ‑‑ and those regions are highlighted
with brackets around them ‑‑ Asia, Europe, Latin America, North America
‑‑ what this table shows you is when you eliminate that country or
region that\'s on the left-hand column, if you go across to the third
column, it has a risk reduction. That tells you what the resulting risk
reduction is. So, for example, if you were to eliminate the region Asia
from the analysis, the risk reduction goes from 20 percent down to 13
percent. If you eliminate Europe, 21.9; Latin America, 21.6; North
America, 23.3. Now, that\'s by region.

Now, what has been alluded to earlier is we prespecified region and the
countries that went into that region, but that\'s just geographic. But
now, look at the countries within Asia. The countries are Hong Kong,
Israel, Japan, Malaysia, Singapore. What this shows is if you eliminate
them one at a time ‑‑ for example, if you eliminate Hong Kong, the risk
reduction goes from 20 percent to 16.5. If you eliminate Israel, it goes
to 16.8. So, you see within Asia, it ranges from 16 to 21.

As a matter of fact, if you do that one-country elimination at a time ‑‑
without eliminating any countries it was a 20 percent reduction. And now
if you eliminate one country at a time, it ranges anywhere from 16.5 to
23 is the number I\'m picking out, which is roughly around that 20
percent. So, what we\'re doing here is an analysis to try to figure out
if there are influential countries.

DR. NISSEN: This is for the double endpoint.

DR. BAIN: This is ESRD or death.

DR. NISSEN: Do you have it for the triple endpoint? Because that was
your primary efficacy parameter.

DR. BAIN: Now, this one, the overall result was 16 percent when we did
the triple endpoint, 16 percent reduction. Again, when you eliminate a
whole region, it has a major impact: 7.1 percent in Asia, which is a
pretty big impact. But if you actually go in and eliminate one country
at a time, now we\'re talking about a range from 13 to 23 in a risk
reduction.

DR. NISSEN: Right, but what happens when those 257 patients from Asia
are eliminated out of the 1,500, the statistical significance is lost
completely. Now the confidence intervals overlap no benefit.

DR. BAIN: I would agree that eliminating a whole region is going to have
an impact here, but what we\'re interested in looking at, we\'re looking
at the countries within a region. So, when you look at eliminating one
country at a time, within Asia it\'s 13 to 16.

DR. TEMPLE: But to be fair, it\'s not eliminating a whole region that\'s
the problem. It\'s eliminating Asia. If you eliminate the other regions,
nothing happens at all. In fact, the whole thing gets better. If you
eliminate North America, and all of a sudden you\'re up to 22.4 percent,
so that\'s a big improvement. So, it\'s that Asia drives the triple
endpoint.

DR. ZEGER: My name is Scott Zeger.

DR. TEMPLE: What that means is hard to say, but it\'s true.

DR. NISSEN: I\'m not passing judgment on what we do with that
information, but I guess what I wanted to drill down on is the fact that
if you take the 257 patients out of the 1,500 in Asia, the study loses
any statistical significance for the triple endpoint.

DR. FLEMING: Could I maybe add a little bit to this? There have at least
maybe three issues put on the table as we\'ve been trying to explore and
understand this better.

One is that these analyses are being done by the stratification factor
for baseline proteinuria, and I would strongly agree that\'s the right
thing to do. As your primary analysis, you ought to be at analysis
accounting for structure you imposed at randomization. So, what the
sponsor is doing here in this stratification seems appropriate.

The explanation, given a couple slides back on what happens when you
look at the on-study or per-protocol treatment, I\'m less persuaded by
because that\'s not preserving the randomization. And to defend the
sponsor, they weren\'t putting that forward as their primary analysis
either, but I don\'t see that as being particularly persuasive.

The third issue, though, is they are looking at this issue as it relates
not only to the triple endpoint but also the double endpoint. Again, it
may be my perspective coming through again that I believe that double
endpoint is, A, the most clinically relevant and, B, the most
interpretable because I\'m not exactly sure what impact it has when we
stop following some 267 people in the course of the study for changes in
doubling in creatinine times.

As a result, if either you look at this slide or you go back to the
previous slide that shows these results of the impact of taking out
region, looking at this ‑‑ actually in fact maybe what I\'m really
looking at ‑‑ well, this is fine. I wanted to actually look at the
overhead slide as well, but this is fine.

Essentially what we\'re seeing, when we take out Asia, is a reduction in
the estimate here that would have been 19.9 percent down to 13 percent,
and for the triple endpoint, it was a reduction from 16.1 down to 7. So,
taking out Asia has a bigger relative effect here in the robustness of
the triple endpoint, taking it from 16 down to 7; whereas for the double
endpoint, it takes it down from 19.9 to 13.1, and it\'s almost
significant.

And in fact, to be fair to the data, if we eye the data and we find the
worst region or the region that accounts for most of the effect, and we
pull that out and say, gee, does the remainder still achieve statistical
significance, there are two problems with that. One is there\'s less
data, so you weren\'t necessarily powered to show significance, and
secondly, it\'s data dredging in the reverse direction where you\'re
taking out the best results and hoping that it stands.

So, Steve, your issues are relevant. I think it\'s very important to do
the probing that you\'re doing so that we can get a sense because we\'re
going to be asked later on, does a single study stand, and we\'re going
to be asked to address this particular kind of issue. Is there
robustness when you look at issues such as subgroups?

My own sense about this, though, is I find it reinforcing that when I
look at the double endpoint, the amount of the effect that\'s being
accounted for by Asia to me seems to be less. I\'m more confident that
these data seem robust through this issue on the double endpoint than on
the triple endpoint.

DR. NISSEN: Although you would have to agree, Tom, that the primary
prespecified efficacy parameter was the triple endpoint. So, I would
tend to focus on what was prespecified up front, and what happens, when
you take out the Asian population, is it\'s no longer significant.

DR. BORER: But to be entirely fair, the prespecified endpoint didn\'t
include a subanalysis by region.

Did you have a ‑‑

DR. ZEGER: I could never have made the point as eloquently as Dr.
Fleming.

(Laughter.)

DR. KEANE: I wonder if we could just continue along this vein because I
think there have been some other issues that came up, Mr. Chairman, that
I think are important for us to answer to help further clarify some of
the relationships between proteinuria and some of the endpoints that we
looked at.

Specifically, I think the question this morning of end-stage renal
disease and whether or not proteinuria was a useful parameter or risk to
actually predict end-stage renal disease in this whole setting, and I
think that would be an important component to our discussion, if I may.

DR. BORER: Before you do, Dr. Brem had a question earlier. Go ahead.

DR. BREM: I wanted to ask whether two issues might have impacted your
information that you\'ve presented.

One is in the stratification, you had patients who received 50
milligrams and another group of people who got 100 milligrams. And is
there a dose dependency in this, and did one group perhaps in Asia get
50 milligrams or 100 milligrams and others get 50? Was there a
difference by dose?

And then the other question I had ‑‑ and perhaps you may not be able to
answer this ‑‑ is these patients were older and could certainly have
acquired other forms of preexistent renal disease on top of their
diabetes. And since we do know that IgA nephropathy tends to occur in
significant amounts in Asian populations, could these patients have two
processes that would perhaps both benefit from treatment with an ACE
inhibitor or an ARB?

DR. KEANE: Let me respond to the initial question first in terms of
actually the amount of drug that was used. Over 70 percent of our
patients actually were utilizing 100 milligrams of losartan per day. In
fact, the way we utilized losartan was to titrate it up based upon blood
pressure. Really, that\'s the fairest way to look at this. If we were
going to do something, did we see a dose dependency, in terms of any
effect, I think we would have had to look at a totally different design
for our clinical trial. So, we haven\'t really addressed that within the
RENAAL trial as a specific endpoint.

The second issue is that the diagnoses that were made here in terms of
the clinical diagnosis of type II diabetes and nephropathy, one would
have to recognize that this was a clinical diagnosis. It was made in
clinic. In fact, it was made by experienced clinical investigators, mind
you, and experienced nephrologists and endocrinologists used to dealing
with this patient population. So, while we did not, and were not able to
by the design of the study, ascertain whether or not there was something
else going on, all of these patients had clinical characteristics, as
you already saw today, that were consistent with the diagnosis of type
II diabetes, as best we\'re able to do in a clinical trial of this
nature.

So, if that helps to answer your questions.

DR. BREM: Yes.

The second point I just raise out of curiosity, not that you\'d have the
answer.

The first point, however, the dose dependence. Is there any information
that you\'ve been able to put together that looked, at least, at whether
50 milligrams in that 30 percent of patients had an effect? Was there
any effect at all?

DR. KEANE: I think the fairest answer in that was that we have not
looked and we didn\'t plan to look in terms of whether or not there was
any dose dependency in terms of the effect. We were again titrating
towards blood pressure and achieving the blood pressure that we have
already talked about this afternoon.

DR. ARMSTRONG: I was going to wait, but since the issue of dose has been
raised, Mr. Chairman, first a comment and then a question.

I\'m persuaded that in the Asian subgroup that it wasn\'t so much the
discontinuation of placebo, which is comparable, but as has been said by
the sponsor, compliance. In fact, they complied with losartan far better
than any other subgroup. So, if there is a plausibility associated with
this, I think it probably is driven by that.

But do I understand correctly that the sponsor is not in a position to
address the issue of dose response and efficacy? If that\'s correct,
fine. Are they in a position to address the issue of safety? Because it
took about 6 months to get the 70 percent of the population up to 100
milligrams and although we\'ve seen the Kaplan-Meier curves on efficacy,
we\'ve seen the safety data not presented according to its time
dependency. And it would be of interest and I think relevance to the
label and to advice to practitioners for me to understand, in
relationship to the final ascertainment, about the issues of safety and
dose and time course.

DR. KEANE: Again, I don\'t think we have a specifically evaluated dose
and time and safety related issues. What I can say clearly is that
overall throughout the entire conduct of the study, the adverse events
that we saw, both clinical and laboratory, were relatively small. Dr.
Shahinfar has already presented that information to you today.

Again, I\'ll go back to my answer previously. We really didn\'t look at
any kind of dose dependency with regards to any of the responses that we
saw in these patients.

Finally, I\'ll make the point that you have to remember that all of
these patients, in large part, have progressive loss of kidney function,
and at any time interval throughout their course, they\'re going to have
different clinical manifestations of their disease. Their blood pressure
may be more difficult to control. They may have differences in levels of
proteinuria when you look at the disease itself. So, I think that should
answer, I believe, your questions in terms of differences in the drug
utilization.

DR. ARMSTRONG: With respect, Mr. Chairman, the notion of safety and
issues that were relatively small, as I understood it, 1 out of 4
patients with losartan had an adverse event characterized by
hyperkalemia and 1 out of 10 had hyperkalemia in excess of 6. So, as a
non-nephrologist, I wouldn\'t characterize that as a small frequency of
adverse events. I think it\'s a genuine issue and I was simply asking
whether there was a time course relevant to the appearance of
hyperkalemia, which is a clinically relevant event.

DR. BAIN: I\'ll let Dr. Keane respond to that clinical question, but let
me first go back to your desire to want to look at dose effect. This
particular study design was not a forced titration. Patients were
titrated based on their response to blood pressure. So, it\'s very
difficult to do any type of a \"randomized comparison\" between dosages
when they\'re being up-dosed based on how they\'re responding to
therapy.

DR. BREM: So, you essentially, in asking for approval, would recommend
what dose? The 100 milligrams or the 50 milligrams?

DR. KEANE: As the trial was designed, it was an up-titration to blood
pressure. So, we\'re starting at 50 and then moving up to 100 to
satisfactorily control blood pressure at 140 over 75, which is what was
achieved in this clinical trial.

Let me go back to address some of the other issues regarding the
clinical aspects of this. All of these patients are sick patients, as
you know. This is a group of individuals with advanced renal dysfunction
that frequently have problems with hyperkalemia, and so the fact that we
only saw 1 in 10, for me as somebody who has been in the practice of
nephrology, is almost routine. We know these kinds of abnormalities are
happening. We actually aggressively treat for them and manage these
patients such that hyperkalemia or related potassium issues are not seen
very frequently in this patient population. So, I think that is part the
management of patients with more advanced renal dysfunction and the
problems of hyperkalemia are not uncommon.

DR. BORER: Dr. Hirsch?

DR. HIRSCH: Dr. Keane, I want to go back, nevertheless, and beat on the
dose-response question one more time because I\'m still intrigued by
moving from preclinical pathophysiology to human disease. Although there
wasn\'t a real effort to be able to evaluate the actual drug dose and
response, nevertheless there is a blood pressure effect.

So, you must have had the opportunity to look at the change in blood
pressure in cohorts or in tertiles of blood pressure lowering to outcome
because they aren\'t identical between the losartan and the placebo
groups. So, one might get some information. In other words ‑‑ you know
where I\'m going with this.

DR. KEANE: Yes. I think the issue with us is that you have to recognize
that, again, blood pressure was difficult to treat in these patients. We
required about three-and-a-half additional medicines on average to
actually control blood pressure. So, to actually interpret any dose
titration that might be occurring ‑‑ are any of these drugs going down,
are they being upped ‑‑ is virtually impossible for us I think to get at
this point in time any reasonable explanation or reasonable data
regarding dose titration because there are so many things consistently
going on within an individual patient because our goal was to lower the
blood pressure and we were using three-and-a-half plus drugs to achieve
that.

DR. HIRSCH: I know it\'s difficult but perhaps that can explain some of
the regional heterogeneity. Obviously, blood pressure lowering is a key
determinant of the renal outcome. So, I\'m still curious.

DR. KEANE: We can probably look into that, Dr. Hirsch, and see if
there\'s any data that we can pull out to satisfy your inquiry.

But I will emphasize again that we were trying to control blood
pressure, not looking at dose-response curves, and if we wished to do
that, we would have done a different trial. That\'s something maybe in
the future that we can do. I think that\'s something that\'s
interesting.

DR. TEMPLE: Are you asking about the relationship of outcome to success
in controlling blood pressure or to dose?

DR. HIRSCH: The former, the success in controlling blood pressure as
being a means to determine and achieving that clinical outcome
regardless of how difficult it was to get there.

And that gets back in a sense to the earlier discussion of how we make
adjustments, adjusting over a group mean ‑‑ I want to do a regression
and say, well, on balance, the whole population had a benefit that\'s
independent of the blood pressure. But it may really well be that those
patients treated with whatever combination drugs, losartan achieved the
greater blood pressure lowering in those that had a clinical benefit.

And it has impact on how I translate this in my patients if this drug
were to achieve approval. Overall, if I can achieve the blood pressure
lowering, one way or the other, with compliance in any region, I may
achieve a comparable benefit. Blood pressure is important here.

DR. TEMPLE: So, you might do this by ‑‑ that is, compare people who got
below systolic of 140 with people who didn\'t, things like that?

DR. HIRSCH: You can look at those who achieved target. You could do it
by tertiles. You could do an actual regression within each of the
treatment groups. A change in the relationship between the two treatment
groups in a regression would satisfy me. A different outcome in the two
treatment groups for comparable blood pressure, getting rid of that
delta, would satisfy me. That would tell me it\'s the drug not the
pressure.

DR. KEANE: We do have some data in terms of actually trying to address
the issue, Alan. It is confounded by the fact that all these things are
going on.

DR. HIRSCH: I know how difficult it is. I really realize that there are
many things going on here. But nevertheless, if I had to look at one
factor, other than region, compliance, et cetera, it would be blood
pressure in a hypertensive diabetic population.

DR. KEANE: Yes, and I think clearly this gives you the ranges of blood
pressure that actually we achieved in the overall trial. So, it\'s hard
actually. It doesn\'t answer precisely your question in terms of how we
got there, but I think, as you can see, in amongst the different
regions, blood pressure was reasonably ‑‑ and this is the mean arterial
pressure ‑‑ controlled.

Do we have a stratification by achieved blood pressure?

DR. BORER: While you\'re finding that, just to get back to Paul\'s
issue, I wonder if you have some information about the distribution of
adverse events in the treated group over time. Forget about the relation
to when they were titrated up or titrated down. If you saw that the rate
of adverse event occurrence was approximately similar across the
duration of the trial, then that would give you some confidence that
you\'re not seeing something happen because more drug is being given
over time. So, while you\'re looking for the data to answer Alan\'s
question, maybe you can see if you have that as well.

DR. KEANE: Fine.

DR. BAIN: Dr. Borer, related to that issue of adverse events, we
prespecified in the protocol ‑‑ I think there were ‑‑ six prespecified
adverse events, which we looked at specifically, and what we did in that
analysis was a time to the first event of that prespecified adverse
event. Do we have that slide?

Now, just to confuse you, we have hazard rates here rather than risk
reductions, but essentially to get the risk reduction, you just take 1
minus that hazard rate and multiply by 100. So, for each one of these,
we looked at was there a difference between the two treatment groups in
the time to the first occurrence of the adverse event that we
prespecified. And as you go down the list, which was already introduced
in the main core presentation, we did find a difference in hyperkalemia
and also hypokalemia.

DR. BORER: Thank you, Ray.

And with regard to Alan\'s question?

DR. KEANE: We\'ll have to look at the database in greater detail to see
if we can ferret or tease out some of that information.

DR. BORER: Okay.

DR. KEANE: Would you like me to actually try to clean up some of the
issues that we addressed while we get this answer for you?

DR. BORER: That would be fine. Before we leave this regional issue,
though, which we\'ve had a lot of discussion about, the FDA reviewed
this data. We have a medical reviewer. We have two statistical
reviewers, Dr. Hung and Dr. Chi, and they saw all these things and
didn\'t flag these as being show stoppers. I\'d like to just hear from
the FDA about the FDA reviewers\' conclusions about the issue of
differences among regions and differences among races. Dr. Hung, are you
back there?

DR. HUNG: Basically I did some analyses and tried to explain potential
differences between the Asian region and the other regions. I seem to
feel that for some reason the Asian people have higher baseline
proteinuria levels. So, I kind of got the impression that that probably
at least partially explains the differences among this potential
heterogeneity. Other than that, I really cannot conclude anything else.
That\'s my best explanation.

DR. BORER: But you didn\'t find that the outcome, skewed as it might
have been in terms of subanalysis by region, precluded the ultimate
conclusion that the drug worked and that it was reasonable to infer that
the drug worked. Is that correct?

DR. HUNG: Yes.

DR. BORER: You just didn\'t think the regional issue was a show stopper.

DR. HUNG: Right. I don\'t think the regional issue is sort of a killer
for the evidence. But I feel that all the evidence is not strong,
although I realize that because the triple endpoint has ‑‑ remember,
this is a loss of information about creatinine in some patients. So, the
current analysis, which is an intent-to-treat analysis, may dilute some
of the potential signal. That\'s my feeling. I cannot say one way or the
other.

DR. BORER: Bob?

DR. TEMPLE: Well, I don\'t have to tell you or anybody on this committee
that this is one of the big conundrums in analyzing trials, and we\'ve
had some of those before this committee. There\'s a strong bias
supported by strongly worded papers that instruct you that if you do
subset analyses, you\'re some kind of idiot. Yet, the plausibility and
the interestingness of them is overwhelming in the other direction. They
seem very hard to ignore. It\'s perfectly obvious that if you take the
triple endpoint and remove Asia, you\'ve got very little left. Well, as
I think Paul Meyer wrote in a paper, if you take the strongest anything
out of a trial, it always looks weaker. Of course, from the other end,
people like to drop the worst clinic because it was obviously a bunch of
shoddy practitioners and you shouldn\'t leave them in. And then the
study always gets stronger.

So, we\'re tormented by this constantly. I don\'t know how much
attention people have paid to it, but the MERIT study of metoprolol in
heart failure had a strong finding overall on the combined endpoint of
hospitalization and death and a very strong finding everywhere in the
world but in the U.S. on death alone, a nearly 50 percent reduction in
mortality in the rest of the world and a 0 percent effect essentially in
the United States.

So, we said in the label very carefully, this may be true, may be not
true, and have been abused all up and down the world since then for
relying on a subset analysis, which everybody knows is stupid because
Richard Peto shows that you can use adiacal signs and make convincing
arguments and stuff like that.

In some sense, there\'s no really perfect answer to this, which is why
you\'re looking at all these other subsets. You\'re looking at the
double endpoint. It\'s not as strong there. That makes some sense. But
there is no perfect answer to these questions. You make the observation.
If there\'s an obvious explanation, then everybody is happy, but there
never is.

I think our overall impression is that you should make major decisions
based on subgroups like that very cautiously. I won\'t say never. I
think sometimes they\'re so overwhelming you can\'t sensibly ignore
them, but you do it with the greatest possible care and you try to think
of everything that might explain it and look in other places and do your
best. But nobody can give you a yes or no answer. Therefore, we never
do.

DR. NISSEN: If I can just comment very briefly, I think that was
obviously wise advice. I try to restrain myself from looking at those
too. When a study is very powerful, a strong p value, robust findings, I
tend to look a little harder if something is marginal. I suspect that
this committee in the past ‑‑ I have only been on here a year or two ‑‑
I think probably has done that. So, where we begin to take more credence
in those groups is when we have an effect that\'s kind of marginal and
now we\'re trying to understand why is it marginal. That is why I probed
this area. I would never have probed this area if the treatment effect
had been substantially larger and the p value a lot stronger.

DR. TEMPLE: Before you leave that, it\'s also true that if they\'re
really, really strong, you can almost never make them go away by looking
at a set. Well, so there\'s a certain tautology in that. It\'s true.
When the p value is .02, all kinds of things can make it go away. It\'s
not that hard. There we sit stuck on this pin.

DR. BORER: Before we go on to this next issue, Tom, you wanted to make a
point?

DR. FLEMING: I\'d just add a little more philosophy to this. As both
Steve and Bob have acknowledged, this is an issue that is extremely
difficult. It\'s an art.

We all recognize that in all likelihood the efficacy and safety of
treatments probably do differ by various patient characteristics, and
yet our trials are barely powered to be able to reliably determine
treatment effect in the aggregate. So, when you start breaking down into
subgroups, you\'re inevitably going to be underpowered to be able to
really reliably detect the signal when there really is a difference, so
you have false negatives. But you also have a great risk of false
positives, because you\'re testing inherently so many different
hypotheses by looking in all these subgroups, that you may see something
that looks like it\'s an effect modifier and it\'s spurious.

My own sense is that doesn\'t mean we shouldn\'t look at subgroups and
have some general sense of whether or not this is giving us greater
confidence or lesser confidence about the reliability of the results.
But most would argue in most settings, if we see something that is in
fact evidence of effect modification, it\'s generally an hypothesis
generation that needs some kind of external validation.

In fact, I\'ve always argued when I look at subgroups there are three
fundamental things I look for. One is what is the overall strength of
evidence here that we have. How strong is the statistical evidence. And
one of the many ways of looking at this are tests for interaction. The
tests for interaction on a region is a .04.

I suspect when you take into context all of the subgroups that were
looked at here, the probability that you\'re going to see something of
this order of magnitude by chance alone is not negligible.

At the same time, the reason it concerns me a little bit is I care the
most about the U.S. at this point because we\'re an advisory committee
for a regulatory authority looking at U.S. applications, and the U.S.
population does certainly show less effect than the average. But
basically from a strength of evidence here, this isn\'t a show stopper
as I see it.

The second criterion is biological plausibility. How plausible is it
that there really is effect modification? The example I always use is
herceptin. Herceptin is an intervention that was developed based on the
concept of Her-2/neu overexpression. So, if I see effect modification by
level of Her-2/neu overexpression in an advanced breast cancer patient,
I\'m not surprised. That\'s highly biologically plausible.

So, a lot of the probing you\'ve been doing, Steve, I think is very
appropriate here. Is there some rationale here that explains this just
beyond statistical association? Right now, from what I\'ve seen, I
don\'t see a smoking a gun. That doesn\'t mean that it\'s not true, but
I don\'t see anything that\'s truly substantially establishing
plausibility.

The third criterion is independent confirmation. There needs to be some
independent confirmation. My own sense about this is looking at region,
it\'s in most trials likely that what Peto would say or Salim Yusef or
many others who\'ve written on this, their advice is wise. Most of these
signals are, in fact, spurious. We need confirmation.

My only twinge of reservation here is it seems like we\'ve seen quite a
few studies coming before us where the North American or the U.S.
population shows less effect, and that just may be a spurious
observation on my part. But it would be interesting to go back and look
more globally. I don\'t generally trust the results in a single trial
that there\'s a region effect modification, but might there be more here
that if we looked more widely, as the FDA can do with its benefits of
seeing so much of what\'s happening in research ‑‑ and of course, this
is an answer that I don\'t want to see be proven because we really do
want to be able to rely on international results, and yet we do need to
also know what the truth is.

So, my own sense, in terms of confirmation, is we have this single
study, and one of the limitations is it doesn\'t give us an ability to
confirm whether there\'s a region effect modification for losartan in
this indication. But it would be of interest to see whether, in a
broader sense, other studies that are at least in related classes might
show any evidence of region effect modification.

DR. NISSEN: Tom, I\'m sorry. One quick follow-on. I really wasn\'t
probing the concept necessarily that this group had some modification of
effect, but I was terribly struck by the fact that so many more patients
in the placebo arm in Asia discontinued than in the treatment arm. And I
wondered if the behavior of the practice patterns, the clinicians, how
patients got in and out of the trial, was somehow different in this
region and that that\'s driving some of this.

DR. FLEMING: Well, I think what we\'re seeing, as you astutely pointed
out, for the differences I think is that so many on losartan in Asia
didn\'t discontinue. What was really distinguishing was the Asian
population on losartan had a very low rate of discontinuation. Now, that
might, in fact, influence enhanced efficacy if higher levels of
adherence implies higher levels of efficacy.

Also though, as you pointed out, a valid concern is if, therefore, there
is particular adherence in the Asian population to losartan and more so
than in the placebo Asian patients, does that in any way reflect on or
influence the level of follow-up for outcome. I haven\'t heard anything
on end-stage renal disease/death outcomes, but it might for the triple
endpoint. But for me, I\'m not so worried about that because I\'m going
to look at the double endpoint.

DR. NISSEN: Right, and the reason I was probing that, Tom, is why should
they be so much more compliant with losartan in Asia than they were with
placebo? It\'s a very, very striking difference.

DR. BORER: Everybody was more compliant with losartan than placebo,
according to the data. The magnitude varied but everybody was, I think.

There was one, to me, striking point that came out of your regional
blood pressure data that will lead into Alan Hirsch\'s question that
I\'ll let him present himself. In the Asian group, the blood pressure
effect of treatment was, to me, importantly less than in the other
regions; that is, in fact, although we get into the mean arterial versus
systolic versus whatever issue that we raised earlier, the mean arterial
pressure for the last few years in the Asian group was actually higher
on losartan than on placebo. So, the fact that the effect was seen in
that group as strongly as it was, despite the fact that the blood
pressure was higher on the putatively active agent, is an interesting
piece of confirmatory evidence to me about the blood pressure.

But Alan raised another question about the relation of change in blood
pressure to outcome, and perhaps you want to ask that directly.

DR. HIRSCH: It\'s not easy to sit between these two sides of the table
and get a point out.

Just to make one more philosophical point before leading into the data,
we\'re obviously looking for biologic reality not for differences only
in practice standards or in how we defined end-stage renal disease. I
hope. Because biologic reality is if the molecule works, hopefully, more
or less genomically similar, that it will work everywhere in the world.
At least I am going to make that assumption for the moment.

So, to link the two arguments here for a minute, my worry is that
something is happening. There\'s something we\'re seeing in this signal
in whichever countries comprise Asia whereby this is a group that has ‑‑
and here\'s my hypothesis ‑‑ a higher baseline protein excretion,
perhaps again a higher placebo discontinuation rate, hitherto
unexplained, and perhaps ‑‑ because we really were not sure ‑‑ a lesser
blood pressure lowering effect, and therefore the losartan group looks
better there. I don\'t know if that\'s true or not, but I was trying to
make a chain of biologic causality.

So, what I was trying to come up with ‑‑ I think angiotensin II is
potentially a toxic agent, but this is a drug approved for blood
pressure lowering in a trial that was designed to lower blood pressure.
I came up with two analyses that I thought might work again.

One again is since you\'re titrating the target blood pressure, could we
see data that simply segregates all the patients in the trial into those
that achieved their target and those that did not achieve their target
and then look at the effect on ESRD or any event rate by achievement of
target blood pressure. If all those patients that achieve target blood
pressure have the same outcome, regardless of treatment allocation, then
it\'s not the molecule. It\'s the blood pressure. Everybody with me?

Or another way of looking at it is to create, again, a regression or a
slope. The y axis, for example, might be a risk or a hazard ratio, and
the x axis, for example, might be again a change in blood pressure
because you do have sequential clinic visits every 3 or 4 months, and
again a change in the slope there would also indicate an effect of the
drug versus placebo.

DR. BAIN: We have not done the analysis which looks at only those people
who achieved their blood pressure and then what the outcomes are because
essentially we\'re getting into this area of two outcomes and adjusting
one outcome for the other and not really doing a randomized comparison.
So, it\'s very difficult and complex. We can do the analysis. It\'s the
interpretation that becomes extremely difficult.

DR. HIRSCH: I realize I may be asking for something more than can occur,
but nevertheless, I\'m making an effort and I\'ll look to my other
colleagues for support or not.

DR. TEMPLE: In his discussion of this, Salim distinguishes between sort
of good things to adjust for and look at and bad things to adjust for.
The good things are all baseline characteristics because those are at
least randomly assigned or at least you\'re pretty sure they are.
Adjusting for outcome variables is very treacherous business because one
factor can have different effects on both. So, as was just explained,
they tend not to do those kinds of things. It doesn\'t mean you can\'t
do them, but you\'ve got to be careful and think hard about it.

DR. BORER: With that having been said, we have several more questions
still unanswered, and I think, Dr. Keane, you were going to move on to
clean up some of those and we\'ll see if you go down the whole list
here.

DR. KEANE: Let me just bring back up Dr. Bain. I think this is a very
important issue related to the outcomes in relationship with proteinuria
and looking at end-stage renal disease as the endpoint. I think Ray has
provided us with that information now so that you can take a look at it.
It really is, I think, a very important relationship.

DR. BAIN: A little housecleaning first. Table 1 on page 8, where we were
discussing earlier looking at the median time, and it looked like
losartan was 13.3, 1303, and placebo was 1373. Essentially what was done
in this table was they went to the median on the y axis, drew a line
across until they hit the two curves, and then dropped the line down to
estimate the median time. It turns out that these numbers are flipped.
We confirmed that losartan is actually 1373 and placebo was 1303, and
you can confirm that yourself by going to that figure of our triple
endpoint and drawing a line for yourself and dropping it down. You\'ll
see that you hit the placebo cumulative incidence curve first and you
drop down to 1303.

DR. THROCKMORTON: What page?

DR. BAIN: Page 8 in the FDA, table 1, statistical review.

DR. BORER: Yes. Where it shows a 70-day difference, the 70-day
difference is in favor of losartan.

DR. BAIN: So, that\'s number one.

Going back to ‑‑ it seems a very long time ago ‑‑ a conversation, where
Tom nicely laid out the different types of adjustments that are
typically done. We talked about a baseline predictor, and then we talked
about an effect modifier. I want to take the first one first, and we\'re
back to the overhead.

This is a request where, remember, in the main presentation we showed
the baseline prediction of the triple endpoint, and then there were a
lot of requests for the prediction of ESRD, the prediction of
ESRD/death, and Dr. Temple wanted a prediction of doubling ESRD.

That\'s what we showed in the main presentation. Remember when we got
out to about 16, we drew a line over, it was like 12, 15. Here, this one
is the doubling ESRD, so there\'s a steeper curve so that baseline
proteinuria is actually very predictive of ESRD doubling, and it\'s most
predictive of end-stage renal disease. Again, remember, that\'s baseline
proteinuria. So, that\'s the answer to that question.

DR. KOPP: Just one other point. That\'s proteinuria defined as
milligrams of albumin per gram of creatinine.

DR. BAIN: Yes. Urinary albumin to creatinine.

So, that was our baseline predictor analysis. The next one that you
requested was the effect modifier analysis to see whether or not the
risk reduction varied across the categories of baseline proteinuria.
Slide 605.

So, what we\'re doing here is we have five categories of baseline
proteinuria. We have the total sample size of individuals within each
one of those categories. And the last column is the risk reduction. Now,
remember, this is the risk reduction for the primary composite.
Remember, overall the primary outcome was 16 percent. So, you can see
that when you\'re less than 1,000, it\'s a risk reduction of 4.6. It
goes up to 15 when you\'re in 1,000, and then 2,000, it\'s up to 17, all
the way up, and when you\'re greater than 4,000, with 163 patients
distributed between the two groups, you\'re at about 20 percent. So,
that\'s the risk reduction as a function of baseline proteinuria
category. So, that\'s housecleaning number two.

Now, one last thing that I\'d like to do is something that we talked
about much earlier today, which was the prespecified analysis for what
we called the baseline risk score. Could I see slide 1339?

This is just a little paragraph from our data analysis plan that
indicates what this analysis is. So, we were looking at the treatment
effect comparing losartan to placebo, adjusted by various baseline
covariates, and this analysis was done in two steps. The first thing we
did was we developed a risk score. What we did was we took pooled data.
We pooled the placebo and losartan data, and formulated a baseline risk
score for our primary composite endpoint. Then after we did that, we
took that risk score and estimated the treatment effect when we
controlled for this baseline risk score.

1340, please. We prespecified in the DAP a total of 15 baseline risk
factors that we would be interested in evaluating in this manner, and
they are listed there.

1341\. Essentially what we did for our primary composite outcome, the
baseline risk score was defined as a linear combination of those
covariates that were significantly selected among the covariates. The
way we did that was we just did a stepwise selection procedure using the
Cox regression model without treatment effect in the model, meaning we
were pooling the placebo and treatment groups. Then the treatment effect
was determined by performing this model with terms, including the
treatment effect and the baseline score. So, that was the second part.
And then we reported the results with a p value and 95 percent
confidence interval.

Now, we\'re on to 1135.

DR. FLEMING: If you go back a slide for a second.

DR. BAIN: Okay. So, urine albumin to urine creatinine ratio. That was
our prespecified stratum. So, those are the 15 characteristics, some of
them continuous, some of them categorical.

DR. FLEMING: So, certainly key ones would be systolic blood pressure
based on what we\'ve seen. You\'re going to be identifying those that
are predictive of outcome and independently predictive, and that\'s a
very rational thing to do. At the same time, what guides some of our
interest as well is whether factors are imbalanced, and one that\'s not
as strongly predictive, if it\'s imbalanced, really is key. So,
hematuria and systolic blood pressure would be two that we would think
that there\'s interest in.

DR. BAIN: Okay. So, we\'ll take a look at those.

So, now we\'re on to slide 1135. So, in summary, we used the
multivariate Cox regression model, pooled the treatment groups, and
looked at the primary composite endpoint as a dependent variable, and
selected significant predictors by a stepwise procedure. Then we
calculated the risk score as a sum of the products of the significant
predictors based on their regression coefficients from those that
remained in the Cox regression model after the stepwise procedure.

Next slide. Now, this is two slides, but what I\'m going to show you
here is these are the two groups. Although we did the analysis pooled,
I\'m going right back to our baseline slide where, remember, we had a
slight imbalance in the mean proteinuria between the two groups, and
that\'s still there. And you can see serum albumin, serum creatinine,
hemoglobin, sitting systolic blood pressure. So, on this slide you have
five of the ones that remain in the risk factor model.

What I put on the right-hand side is kind of an indicator of the
strength of an individual variable and its relationship with the risk
score. It turns out that the strongest of our baseline risk score
factors was urine albumin to creatinine ratio.

The next slide will give you the rest of the covariates that were in
this model. It turns out that Latin American, yes/no, insulin use, and
at the bottom here you see what I was alluding to earlier, the linear
score of significant factors. The more negative that value is, the
higher your risk. So, you can see that, when you do a linear combination
of these risk factors, you tend to see that the placebo group is ‑‑ I\'m
sorry. The other way around. The more negative, the less at risk you
are. Therefore, what\'s shown up here is the losartan group has a higher
risk when you look across not just one factor, but all seven of those
factors.

Next slide. So, then what we did was we took it to step two which was
take that risk factor score, which is a single score for each individual
and enter that into our original model, which was our primary results
model, which was where we showed that 16 percent reduction. And if we
now adjust for their baseline risk score, the risk reduction goes from
16.1 to 23.9.

Graphically it\'s shown on the next slide. There\'s our primary outcome
above, and when we adjust it, a stronger treatment effect, less than
.001.

Although we developed the risk factor score based on the triple
endpoint, we actually used that risk factor score to see what effect it
had on our other clinical endpoints, and that\'s on the next slide. You
can see that you see that same effect. For ESRD, the treatment effect
got stronger, and for end-stage renal disease or death, the adjustment
made it slightly stronger.

DR. BORER: Ray, can I just ask about the factors you used? It seems that
all of them are reasonable except perhaps for region. That sort of begs
the issue. Did you sort of look at this? Latin America, yes/no, probably
was down on the list.

DR. BAIN: Well, no, the original list had all regions. It just turns out
that that particular region of the four ‑‑

DR. BORER: No. I understand. But you ultimately used Latin America,
yes/no, in the model that you used for adjustment. Wrong?

DR. BAIN: No. Latin America went into the risk factor score. It was one
of the things that you multiplied by in order to come out with a single
number for a patient.

DR. BORER: Right. That\'s what I mean. So, it was used to adjust for
risk.

DR. BAIN: Correct.

DR. BORER: And all I wanted here is that if you took Latin America out
of there, you\'ve still got a directionally similar movement ‑‑

DR. BAIN: We would have to run that analysis. We just did? The same.

DR. FLEMING: It should be.

It\'s certainly relevant to know that we didn\'t just look at
proteinuria, but what\'s apparent from this is that when you look at
those covariates that are going to fall out of a variable selection
model, the one that\'s dominating here is proteinuria. It\'s very
predictive of outcome, and it\'s the one that is influencing outcome
effect because there\'s also this imbalance in the tail. So, this is
certainly a reassuring analysis to say it\'s not just that we\'re
looking at proteinuria because we could see that it had this imbalance.

It would be relevant, though ‑‑ at least for me. I\'d like to see the
analysis that simply adjusts simultaneously for baseline systolic blood
pressure because the differences that we see over time were largely
already apparent at baseline. And Bob Temple is right. One has to be
really careful when you\'re using post-baseline values of covariates and
how you interpret the results. But some of the blood pressure difference
was already apparent at baseline. So, even if it doesn\'t show up in
your variable selection model, it could be an influential factor as a
confounder because of that imbalance.

My suspicion is that the most significant confounder here is
proteinuria. It\'s increasing the estimate of effect from 16 to 23
percent or 22 percent, and systolic blood pressure at baseline I\'m
guessing will correct that back 1 or 2 points, and in the end you\'ll
still have a net increase but not quite as much when you just look at
proteinuria, which is more or less what\'s showing up out of that
analysis.

DR. BAIN: So, we\'ll do that.

DR. BORER: While you\'re doing that, JoAnn, you had several questions
related to looking at the double endpoint, and perhaps you want to
restate them if they haven\'t been answered already.

DR. LINDENFELD: No. I think I\'ve gotten an answer to those in this
data.

DR. BORER: Blase, I think you had asked about the time to event when you
looked at the double endpoint as an outcome, the average time to event
rather than the triple endpoint. I\'d like to hear that too, if you
happen to have that, understanding, as we all do, that it\'s a poor
man\'s way of looking at anything; that is, the average time to event
among those people who had events when the event was the real hard
endpoint.

DR. BAIN: You wanted it for ESRD only, Jeff?

DR. BORER: ESRD or death.

DR. BAIN: Okay. So, why don\'t you put up the ESRD slide from the core
presentation, or whatever one.

Now, of course, in this particular outcome, we don\'t get to 50 percent
of events on the y axis, so we can\'t talk about the median time. But we
can talk about, for example, the time to 20 percent of the patients
reaching their endpoint. Therefore, you just draw a line over from 20
and drop it down. So, it\'s about 2-and-a-half years for placebo and 3
years for ‑‑ so, about a 6-month difference.

DR. BORER: How about if you do the same thing since that\'s obviously a
reasonable way to get a gestalt of the number we asked for. If you look
at the post hoc analysis curves where you accounted for MI, stroke,
cardiovascular endpoints, so we\'re seeing a net effect.

DR. TEMPLE: What are you asking, Jeffrey? They saw no difference in
those.

DR. BORER: No, no. What they did was to combine ESRD, death, myocardial
infarction, and stroke in one analysis.

DR. BAIN: So, Jeffrey, let me make sure I understand. Which endpoint?

DR. BORER: There it is.

DR. BAIN: Now, here you could probably maybe go up to 40 percent,
although it\'s getting pretty thin up there. But again, you would do the
same thing. You could draw a line from either 40 or 30 around, and
you\'re going to see that there\'s a difference in the time to the
events.

DR. BORER: Yes. We\'re still talking about 6 months.

DR. BAIN: 6 months.

DR. BORER: Beverly?

DR. LORELL: I think the other way, Tom Fleming\'s comments
notwithstanding, that both Blase and I were interested in getting a feel
for is among those patients who had a major heart event, what was the
average time to that event.

DR. BORER: These are the people who had endpoints. So, that\'s about the
best we\'re going to do, but it looks like it\'s about 6 months.

DR. FLEMING: Before we leave this, could I comment on these two slides,
379 and 73, maybe going to 397 first?

From a renal perspective, this is what one might expect to be the
component of a composite endpoint when you look at the clinical
endpoints, the component that would be presumably most specifically
being targeted, prevention of end-stage renal disease. It\'s
interesting, when one is doing studies such as these that there\'s a lot
of wisdom for not doing a study that would have 2 years of median
follow-up. And this study, in essence, has information predominantly
through 3 years, a limited amount of information out to 4 years.

Just to follow up on some previous discussion, this estimate is a 28.6
percent relative reduction in the rate of failure. That\'s based on a
weighted average of what the true reduction is at all points over time.
The true reduction in the first 18 months is 0. The curves are
overlapping through the first 18 months, which means that the true
reduction between 18 months and about 42, when you have most of your
data, is probably about 40 to 45 percent, meaning that if you do a study
like this and you use the log rank and the Cox regression methods and
get relative risk reductions, those estimates are a weighted average
over time of what truly isn\'t a truly constant reduction over time. The
reduction in the first 18 months is 0; in the last 18 months is 40.

So, if you had done this study with one less year of follow-up, you
would be weighting much more proportionally on the 0 rather than the 40,
and your estimate would have been 20 percent. If they had done another
year of this trial, and these curves represent truth, the estimate would
have been even greater than 28.6.

So, it\'s interesting to look at these curves and understand what these
relative risk estimates mean, in particular when there\'s evidence such
as this that the reduction isn\'t constant over time.

The second point on the next slide, if you look at slide 73, you see the
same basic phenomenon. One of my questions here is this is in fact an
endpoint that some of us in January had really wanted to focus on if we
wanted to focus on clinical measures that were combining both the renal
as well as cardiovascular elements. In the renal, we were saying
end-stage renal disease/death; in the cardiovascular, were
cardiovascular death, MI, and stroke. So, I\'m delighted the sponsor
presented this.

Essentially what we\'re looking at is this is made up of 47 fewer
end-stage renal disease events, 18 fewer MIs, 3 fewer strokes, and 3
excess deaths, which are made up of 11 excess cardiovascular deaths, but
8 fewer of the non-cardiovascular deaths. That\'s a net difference of 65
events, although I can\'t tell how many people that is. I\'m assuming
it\'s probably about 40 to 55 fewer people have at least one of these
events because this is a time to the first of those types of events
analysis. Can the sponsor clarify what that is?

DR. KEANE: We\'re just looking, Dr. Fleming.

DR. FLEMING: You can tell me later after you have a chance to look.

DR. KEANE: It is.

DR. FLEMING: What\'s the answer?

DR. KEANE: Time to event.

DR. FLEMING: I can add up and see there are 65 fewer events, but I
can\'t tell how many fewer people had at least one event. That\'s what
this analysis is looking at. It\'s time to the first of those types of
events. I\'m guessing it\'s 40 to 55.

DR. KEANE: We\'re in the process, as I said, to get the number of
patients that were involved with this.

DR. BAIN: One more housecleaning chore. Tom asked when you go and do the
Cox proportional hazards regression on the triple endpoint, remember it
was a 16 percent reduction. When you adjust for baseline systolic blood
pressure, it goes to 21.6 in addition to baseline proteinuria stratum.

DR. BORER: My list of questions is exhausted but yours may not be. Did
you have some other clarifications you wanted to give us?

DR. KEANE: Yes. If you will just give us a couple of more seconds,
we\'ll give the response to Dr. Fleming\'s question in terms of the
number of patients that the event curves actually encompassed.

DR. BORER: While you\'re doing that, what we\'ll move on to next, as
soon as you have that answer, is the questions, and we\'ll structure the
rest of the discussion around those.

DR. KOPP: One additional question.

DR. BORER: Two. I think JoAnn has one there also.

DR. KOPP: To return to the issue of how you define end-stage renal
disease, it was suggested during the break that one additional analysis
would be to ask what was the final creatinine before somebody went on
dialysis and did it differ between the two groups.

DR. BAIN: Now, I believe the question was that and by region for serum
creatinine. At least, that\'s what I have here.

Let me tell you by region these are median serum creatinines. I\'m going
to give you losartan then placebo. In Asia, it\'s 7.0 and 6.2. In
Europe, it\'s 4.9 and 5.3. In Latin America, it\'s 5.2 and 6.6. In North
America, it\'s 4.4 and 4.9.

Now, the interesting thing about those numbers is you\'ll probably
notice that they tend to be lower in Europe and North America. Well, it
turns out that the time from the serum creatinine to end-stage renal
disease is actually higher in those two groups, probably driven by study
drug discontinuation and then some of those patients going into
telephone follow-up. So, therefore, you\'re not getting serum
creatinines very close to their ESRD events.

DR. BORER: It seems clear, if I heard the presentation correctly that
you just made, that the creatinines at endpoint were systematically
higher in people on placebo than on losartan. Is that correct? Did I
hear that right?

DR. BAIN: No. They go back and forth. It\'s true in Asia. It\'s not true
in EU. It\'s not true in Latin America, and it\'s not true in North
America. So, in Asia it tends to be a little higher.

But now, remember, we\'re talking about in Asia a total of 60 events; in
EU, a total of 40; 60 in Latin America; and North America ‑‑ you know.
So, the numbers are pretty small here. Remember, these are only people
who actually had the event of end-stage renal disease.

DR. BORER: Right. Is there any reason that there should be a discrepancy
as large as 1 milligram percent of creatinine between those groups? Does
that have to do with timing of checking ‑‑

DR. BAIN: I\'ll put out a possibility there. These are people who are
going to end-stage renal disease. So, it really is probably a function
of exactly where you\'re picking them up relative to their end-stage
renal disease. That\'s a guess.

DR. BORER: It\'s probably an unanswerable question.

JoAnn?

DR. LINDENFELD: I have two questions about secondary endpoints. The
first is we\'ve seen that there\'s a nice reduction in proteinuria.
Could you tell me if the reduction in proteinuria correlates with the
doubling of serum creatinine or end-stage renal disease? Just in terms
of how we use these drugs, I\'m interested in knowing if the change in
proteinuria correlates with the other endpoints.

DR. KEANE: It does.

DR. LINDENFELD: Strongly?

DR. KEANE: Strongly.

DR. LINDENFELD: Good.

Then in terms of cardiovascular endpoints, I know this is a difficult
issue, but I\'d like to hear your discussion. The study was stopped
prematurely because of data with ACE inhibitors and cardiovascular
mortality. Here we see very little signal for cardiovascular mortality.
I understand there\'s a little bit shorter follow-up here and fewer
numbers, but we see very little signal there. I wondered if you could
just tell me your thoughts about why there doesn\'t appear to be much
effect on cardiovascular mortality.

DR. KEANE: There are a number of things that I think are clinically
relevant. First of all is the RENAAL trial is a renal protection study.
It wasn\'t a study of cardioprotection. So, we had a smaller group of
patients, 1,500. Usually when you look at a cardioprotective study,
it\'s substantively larger. So, that was one set of issues.

And number two is actually the duration of the trial was relatively
shorter as compared to most cardioprotection studies.

When we look at the type of patient we had in our study, we made a very
concerted effort to not have patients that had a lot of cardiovascular
disease antecedent to our randomization process for the RENAAL trial, so
that we had lower cardiovascular disease manifestations or disease
history. We had a smaller group of patients. We were looking at
specifically enriching our population for renal events. So, I think when
you look at all of that, I think that explains, at least in part, the
reason why we didn\'t see a major difference in cardiovascular
endpoints.

Again, our composite, I\'ll just underscore, was almost a 10 percent
risk reduction for the composite. So, it was in the right direction, and
as I showed in my concluding slide, there was some noise around the 0
line in terms of the point estimates for each of the components of the
overall. So, I think that\'s most likely, as best I\'m able to look at,
the explanation for why there wasn\'t more robust changes in
cardiovascular disease endpoints.

DR. BORER: We\'ll go on to the ‑‑ I\'m sorry. Blase?

DR. CARABELLO: But from a functional standpoint, the fact of the matter
is, the Data and Safety Monitoring Board said these patients should not
be precluded from being on an ACE inhibitor, or maybe you could even
take that as a recommendation that they should be on an ACE inhibitor.
I\'ve got a sea of folks in my hospital who are diabetics and already on
an ACE inhibitor. We don\'t have any data about that interaction. What
are we supposed to do?

DR. KEANE: I\'m not sure I completely understand what question you\'re
asking me.

DR. LORELL: May I help?

DR. KEANE: Yes.

DR. LORELL: I think I know what Dr. Carabello is getting at. I think
it\'s a very difficult issue here.

The issue of use of an ACE inhibitor was raised in two ways in this
trial. It was raised in study design by prohibition of use of an ACE
inhibitor during the trial and a washout period. Secondly, it was
raised, as Dr. Carabello pointed out, by the Steering Committee
prematurely stopping this trial because of the issue of cardioprotection
in multiple arenas of the use of an ACE inhibitor.

We\'ve seen data presented here, very elegantly, of really an
extraordinary tight link in this patient population of renal events and
cardiovascular events. If my numbers are correct, 1 out of 5 of the
patients in this study died, and in the losartan group, 57 percent of
those were cardiovascular events. So, this is a major clinical issue for
Dr. Carabello\'s patients and most of us around the table.

So, I think one of the real dilemmas here that was part of design and
part of trial stoppage is the issue of how you think about this drug for
renal protection in the absence of demonstration of a cardioprotective
effect, which is what kills many of these patients. And it\'s very
problematic. We don\'t have any data here in this population about
combined use of ACE inhibitor and ARB.

So, I think what Dr. Carabello and I might like to hear is your thoughts
in industry, were this drug to be approved, as to how you would
recommend the use of this drug relative to the absence of a demonstrated
cardioprotective effect as your secondary endpoint and the ethical issue
that was raised by the Steering Committee in stopping this trial of
potential ethical need to use an ACE inhibitor.

DR. BORER: While you\'re answering that, just clarify for me. I believe
you had 100 patients who actually were on ACE inhibitor because the ACE
inhibitor prohibition was by amendment after the trial had started, if
I\'m not mistaken. So, you may actually have some data that are
relevant.

DR. KEANE: Actually that is not correct. All the patients prior to
randomization had their ACE inhibitor or ARB stopped. Let me just make
some points and then we can have some additional discussion.

We did look at interactions, as you saw, between prior ACE use, prior
ARB use, and either the renal or cardiovascular endpoints, and there was
no interaction, as best we could see, in that data set. So, it didn\'t
look like prior utilization of ACEs or ARB impacted any of the results
that we had.

Number three is that in terms of the Steering Committee\'s decision to
stop the trial, obviously we didn\'t know what the recommendations were
at that point in time. Dr. Brenner is here, if you\'d like to have this
discussion in greater detail. What our concern was, in a more global
perspective, is that we had a placebo group of patients that were not on
any AII blockade. With the Mann data that came out in the Annals last
year, that raised at least a concern for us in terms of continuing the
trial. And that was really what I think our issue was. It wasn\'t that
we weren\'t seeing any other benefits for ARB, but the issue was that we
had half of the trial that was not on any AII blockade.

Then finally, let me just make the point that you have to take our data
in the context of what the study was. This was a study that was done in
patients with advanced renal functional declines, type II diabetics with
proteinuria, and all had fairly advanced disease. All of the other ACE
data that is out there is not in this population. So, it does present us
with a bit of a difficulty in terms of what should be done on an
individual patient basis, but our focus really was in the patients with
advanced renal disease, with proteinuria, and looking at renal outcome.
So, we didn\'t have that data at that point in time when we stopped our
trials.

DR. BORER: Steve and then Bob.

DR. NISSEN: Yes. I think we\'re all saying about the same thing. Let me
see if I can be very precise here.

Our diabetic hypertensive patients with renal insufficiency are, by and
large, all on ACE inhibitors, and they\'re on them for two reasons I
think. One is that there\'s some pretty good evidence of cardiovascular
protection that I think most people would generally accept, and many
individuals have extrapolated from the type I data and said, well, if it
works in type I nephropathy, it probably works in type II even though
the agency never approved it. So, now we\'re confronted with if the
agency approves losartan for this indication, clinicians are faced with
a really big dilemma. Do you take the patient off the ACE inhibitor and
switch them over to losartan? Do you add losartan to an ACE inhibitor?

I think what people are getting at and I would like to be very specific
about is our fear that for patients that are stable and doing well on
ACE inhibitors, because of a label change, someone is going to say to
the physicians, here\'s the only labeled drug for renal protection in
type II diabetes. Let\'s have you take your patient off of your ACE
inhibitor and put them on losartan. Then we don\'t know whether the
cardioprotective benefits of ARBs are comparable to ACEs or not. We
don\'t know that.

So, this creates a huge dilemma and that dilemma was manifest by the
Steering Committee of this trial feeling like they couldn\'t go on with
the trial because they couldn\'t withhold ACE inhibitors from these
patients. So, we\'re really on the horns of a terrible dilemma as a
consequence of that.

DR. KEANE: Let me just call on Peter for a second here.

DR. BORER: Just before you do, Bob, did you have a comment to make
first? Then, Peter, maybe you can comment.

DR. TEMPLE: I just thought it would be very helpful to pin down exactly
which treatments are because we\'re analogizing and doing our best and
which treatments are really well documented. The only data comes from
HOPE. Right? Not the same population. No renal disease, but they did
have macroalbuminuria. Right. So, it\'s those people you\'d be worried
about, people who are being put on some ACE inhibitor or other on the
basis of HOPE or ramipril itself, which is the only one that was
actually studied. So, that\'s the group that you\'re worried about. What
do you do with those people now? If they turn out to have a little
elevation of creatinine, do you now ignore those results and switch or
things like that? Good questions.

DR. BORER: Peter?

DR. KOWEY: Let me just address this. Peter Kowey, paid consultant for
Merck.

Blase, let me put this in some perspective because it\'s a question
that\'s come up repeatedly in looking at this information. A lot of
people have already asked this question. And the answer is that from my
perspective as a cardiologist, we frequently have patients that have
competing risks and have competing diseases for whom there are some
therapies that actually overlap. There are situations where we have to
make a value judgment as to how important the cardiovascular end of
things are going to be in this scenario versus how important is the
renal end of this disease in this scenario. Because you\'re right. We do
not have data on combined use of these two drugs. So, we can\'t advocate
that.

As a cardiologist, my answer is that the more I\'m concerned about these
patients being disposed to a renal endpoint from the point of view of
how they look, vis-a-vis the patients that were enrolled in the trial,
the more likely I am to use an ARB, and the more likely they are to look
to me like a cardiovascular patient, the more likely I am to use an ACE
inhibitor. But it\'s a judgment that needs to be made on a
patient-to-patient basis.

I think it\'s a little tiny bit unreasonable to expect a trial like this
to answer every question that can be asked about cardiovascular disease.
It can\'t. There are data on both sides of the question for ARBs and ACE
inhibitors even within this realm.

So, I understand your question but I don\'t think that approving this
drug for this indication necessarily places patients at risk. It places
doctors in a position where they have to make a clinical judgment, but
you do that all the time anyway. So, that\'s where I think this sits.

DR. BORER: I\'d like to weigh in here just for a minute because this is
a drug approvability panel, advisory panel. I think that we have to
consider what the FDA does and what it doesn\'t do, and as Bob pointed
out, what the data that we\'re weighing in against are.

My understanding of the HOPE trial is it involved individuals who were
greater than 55 years of age with known coronary disease and at least
one other risk factor and that risk factor could have been diabetes. It
could have been hypercholesterolemia. It could have been hypertension.
And one drug was used. Actually two, if you include vitamin E, but that
didn\'t work. So, that\'s the database. That\'s it.

Having said that, the FDA doesn\'t establish medical practice. Sorry,
Bob. I know that bothers you.

(Laughter.)

DR. BORER: No, the FDA doesn\'t mandate medical practice. It may
indirectly, but that\'s not what it does. So, in a sense this issue is
not a primary FDA concern. The medical practice is determined by
consensus, by advisory panels, which I\'m not too happy with, and by the
courts based on what evidence you can bring to bear if something goes
wrong and somebody says it\'s your fault that it did.

Ultimately there aren\'t the data to draw the firm conclusions that
people might draw about should you be on an ARB, should you be on an ACE
inhibitor, just as Peter said. The data aren\'t there. You have to make
your best judgment based on the data that exist.

I would like to suggest, therefore, just so we can take this issue off
the table and not make it an approvability issue, when I don\'t think it
really primarily ought to be, but it\'s worth a great deal of thought
because it\'s a very important issue because people do act on the basis
of just what Steve said and Beverly said ‑‑ that is, if the indication
is there, then it may be malpractice not to do this ‑‑ that perhaps the
FDA should consider, if everybody on the panel agrees to this, something
in labeling that says what we know and what we don\'t know and that
anything that\'s said about this drug shouldn\'t be construed to suggest
that the approval, if it happens to be approved for this indication,
should be construed as a mandate that it must be used, that indeed
competing risks, individual patient, et cetera. This is a drug that can
do certain things or maybe can\'t. If we find that it can, then it can.

I think that this is something that we\'ve never considered before in a
formal way, and I think considering the possibility of putting something
into the label about it might help. But I think that fundamentally we
shouldn\'t make approvability decisions based on this because the data
aren\'t there to allow us to do it. So, I throw that out for discussion
so we can get rid of it before we go on.

Bob?

DR. TEMPLE: It\'s an interesting thought. We occasionally do say what is
now known about something although we don\'t we do it very often. It
gets very, very difficult. For example, I\'m sure most people think that
ACE inhibitors should be used in the population that was studied in
HOPE. The fact is only one drug of that class has been studied. There
isn\'t a second study. The result was dramatic and, incidentally, not so
impressive in the United States.

(Laughter.)

DR. TEMPLE: For what you will choose to make of that.

Well, if you really wanted to set the whole stage, you\'d have to write
a little essay describing all those things and say what you should when
one member of a class does something. How much should you believe about
all the others? And then by the time you\'re done talking about people
with other risks ‑‑ for example, if you have a little heart failure,
well, there\'s a lot more data on ACE inhibitors than there is about AII
blockers. So, that might influence you.

This is not an easy thing to write. I think you should write a chapter.
But we would certainly consider trying to provide some perspective as
best we can. But our trouble is we\'re not supposed to infer things too
much. We\'re supposed to be even more data-dependent than you guys are,
and that really means you can\'t speculate at all in labeling. So, it\'s
a problem.

DR. BORER: Steve?

DR. NISSEN: The reason we have this dilemma, of course, is that a
therapy, ACE inhibitors, in this population became virtually the gold
standard without ever coming before the FDA for approval. That is to
say, ACE inhibitors for renal protection. If you talk to diabetologists
and to nephrologists ‑‑ you guys correct me if I\'m wrong ‑‑ but for
many a year everybody has put these patients on ACE inhibitors for their
renal protective effects. That\'s reality and we have not changed that.
So, you see the reason it\'s a little bit different than some other
circumstances is not so much a question of competing risks, it\'s also a
question of are ARBs as good, even though ACE inhibitors were never
approved, so that what will the public policy implications be of
approving under those circumstances.

DR. TEMPLE: It\'s not not approved. They weren\'t studied.

DR. NISSEN: I understand.

DR. TEMPLE: It\'s not the same thing.

DR. NISSEN: Okay, I understand.

But I\'m saying a therapy that was neither studied nor approved has
become the gold standard. So, now you\'ve got this gold standard that\'s
actually made of bronze, and now what we\'re looking at is what evidence
do we require in order to set the conditions in motion for people
changing that practice.

DR. TEMPLE: I will say something about that. This comes up when we try
to think about how something compares to \"available therapy.\" Well,
what does available therapy mean? What people do or what we\'ve actually
written up? We actually have just put out a final guidance on this. This
is important because it determines whether you\'re a priority drug or
not and other things that you probably don\'t care that much about.

What we have is a strong bias toward available therapy, meaning
something that has been through our review. You might think we would
think that and you wouldn\'t be surprised. But it means someone has
bothered to pull the data together and put it forth, and you get extra
credit for having done that. Our inclination is to think that approvals
and things like that should take into account what has been well
documented, but probably shouldn\'t worry too much ‑‑ you may choose to
worry about it; that\'s your privilege ‑‑ about what might be true but
nobody has ever bothered to study or been able to study. It would be
hard to study those things now. That\'s probably the reason nobody does
it.

In labeling and other places, we do tend to focus most on what\'s
actually known and studied and been before us and been reviewed by
expert committees and less on things that might be true but haven\'t
been studied.

DR. BORER: Dr. Haffner, did you have a comment before Paul and Beverly?

DR. HAFFNER: Yes. First of all, I understand I have been active in the
ADA in professional practice, and this is a very difficult issue. In
fact, the ADA came out with new recommendations on their professional
practice recommendations in January and they disagree in different
position papers. The hypertension paper said that ARBs and ACEs were
both first line partially because we hedged our bets for the
cardiovascular issue. The nephropathy guidelines said that ARBs were
first line and ACEs were a second choice. And this is actually the same
professional organization.

I should mention that the entire thing is driven by HOPE data, and the
HOPE study, as you know, didn\'t actually examine this issue. There is
no ACE data in people with advanced renal failure. And if you go back to
the two years before HOPE came out, in fact many people thought that ACE
inhibitors might not be so great on the basis of the UK PDS data. So,
HOPE isn\'t the only study in diabetics. The UK PDS data compared this
relative to atenolol and actually atenolol did a little bit better than
an ACE inhibitor in spite of the fact the ACE inhibitor is better
tolerated.

So, I agree. I think ACEs are a good therapy. I don\'t think they have
been well established in progression of renal disease, but I don\'t
frankly know in these sorts of patients whether ACEs are better than
ARBs. We don\'t actually have that sort of comparison, and my guess is
we\'ll never actually have that comparison. So, I think there is some
general uncertainty and you have to look beyond the most recent study.
There is a long history there with some real questions involved in it.

DR. BORER: Thank you. I should point out too that the issue of approval
of ramipril for the renoprotective effect that was putatively seen in
HOPE was voted against by this panel when it came up a couple of years
ago.

Paul and then Beverly.

DR. ARMSTRONG: In responding to your challenge, Mr. Chairman, which I
think is were this drug to be approved, what would the label look like,
my own view would be that it does work in a very specific population
that we\'ve heard about today and does not cause harm relative to some
other issues that we would be concerned about that coexist in these
patients and indeed in the broader population that we all see. So, I
think crafting a label, to the extent that we know what it does or we
think we know what it does in a fairly select population where a number
of issues that patients receive ACE inhibitors for are not present,
would be prudent. We obviously wish to avoid the issue that Dr.
Carabello has raised which would be that a broad number of patients at
risk to cardiovascular disease who are receiving ACE therapy now for
good indications and evidence-based medicine would not be switched off
them because they have co-existent renal disease.

DR. BORER: Beverly?

DR. LORELL: Thank you. Well, that really underscores a concern that I
had along this issue. I think that if cardiovascular events were defined
not as a retrospective, ad hoc look but as a clear secondary endpoint in
this trial ‑‑ and I think one of the concerns in my mind, just as was
pointed out in the presentation earlier today, is the data on
cardiovascular events were inconsistent in this trial. They didn\'t all
go the right way. The cardiovascular death event ‑‑ and cardiovascular
death was 57 percent of all deaths in the losartan arm ‑‑ in fact, went
the wrong way. So, I think it\'s an added source of some unease in this
discussion that the cardiovascular death, in fact, looked to go the
wrong way. The data were not internally consistent in sitting on the
left of the line, and this committee really wrestled with that issue as
a component of our decision regarding a different ARB for the same
indication not too long ago. So, it is problematic.

DR. BORER: Yes. It\'s a problem. Clearly, again, the cardioprotective
studies didn\'t involve people with near end-stage renal disease and
whatever. So, it\'s hard to get to. But that\'s why I think, at the end
of the day, we may have to suggest to the FDA that it do some label
crafting.

Bob?

DR. TEMPLE: Remind me. But except for HOPE, most of the cardioprotective
effects of ACE inhibitors have been shown in people with ventricular
dysfunction. Somebody needs to correct me if this is wrong, and that\'s
not true of HOPE. So, these people didn\'t have that. The only figure
that related to heart failure actually was going the appropriate way.
So, I\'m not so sure, except for HOPE, which I do find inspiring ‑‑
it\'s not quite clear what the effects of ACE inhibitors are in all
those other settings in the absence of ventricular dysfunction. I think
that\'s true.

DR. BORER: Yes, that\'s true, and I think you would have said HOPE is
hopeful, had you the facility with words that Dr. Konstam does.

(Laughter.)

DR. TEMPLE: Of course, as someone who lives in the United States, I\'m
not sure I know about that statement.

DR. BORER: Why don\'t we move ahead to the questions.

But before we do that, I\'m going to have to ask a point of information.
It says on here that there is to be a break at 3 o\'clock. Now, it\'s a
quarter of 3:00. I\'m wondering if we\'re mandated to take that break?
We\'re not? We\'re not. Okay.

Oh, excuse me. One thing I\'ve forgotten to do that I should have done
is I didn\'t ask if there was any public comment. The meeting should
have been open at 1 o\'clock for public hearing. We didn\'t have any
formal requests, but was there anyone who came here to make a public
statement?

(No response.)

DR. BORER: No. The record should show that there was no request for
public comment.

Now let\'s go on to the questions here. The Cardio-Renal Advisory
Committee is asked to opine on the benefits and risks of losartan, an
angiotensin II receptor antagonist, for the treatment of nephropathy in
type II diabetes. Reviews of chemistry, pharmacology, toxicology,
biopharmaceutics, biometrics, and clinical safety present no apparent
barriers to its approval.

The committee is asked if it believes the strength of evidence for a
treatment benefit supports approval.

The direct evidence is derived from one study. RENAAL enrolled 1,513
subjects with type II diabetes, hypertension, proteinuria, albumin to
creatinine ratio greater than or equal to 300 milligrams per gram, and
serum creatinine between 1.5 and 3 milligrams per deciliter. Subjects
were randomized to placebo or losartan, titrated as tolerated from 50
milligrams to 100 milligrams, and followed for a mean of 2.4 years. The
primary endpoint was a time-to-first-event comparison of losartan and
placebo for death, end-stage renal disease, or doubling of serum
creatinine. The result was an estimated risk reduction of 16 percent, p
equals .022, with treatment groups diverging after about 6 months.

So, our first question. There were 686 total endpoint events in the
placebo and losartan groups, 32 fewer in the losartan group than on
placebo. One of the characteristics of a none-too-small p value is that
the result is sensitive to the handling of subjects with incomplete
data. And Tom actually got into that in some detail earlier. In RENAAL,
there were no subjects randomized but not treated, no subjects with
questioned event adjudication, and no subjects lost to follow-up for
end-stage renal disease or mortality.

So, 463 subjects discontinued the drug. How were they handled? How
should they have been handled? And what effect did the sponsor\'s rules
for handling dropouts have on the credibility of the principal findings?

We can deal, I think, with all of those together. Tom, do you want to
start off?

DR. FLEMING: How were the patients who discontinued drug handled? My
understanding is they were all followed from that point forward. All of
them were followed for the end-stage renal disease/death endpoints. As I
understand, 40 percent of the person-years of follow-up subsequent to
that time, though, patients were not followed for the change in doubling
in creatinine time. As a result, the procedure used by the sponsor to
handling those patients who discontinued was fully appropriate, giving
us complete follow-up information about end-stage renal disease and
death.

There is, however, a problematic issue arising with the 267 patients who
did, in fact, have discontinuation of their follow-up of doubling in
serum creatinine time prior to having any of the elements of the triple
endpoint. While those people did, in fact, have subsequent follow-up for
end-stage renal disease/death, it makes the triple endpoint analysis a
bit more difficult to interpret, but the double endpoint, end-stage
renal disease/death, analysis is fully free of any of that concern.

DR. BORER: JoAnn, you were the committee reviewer. Do you have any other
issues?

DR. LINDENFELD: No. I have nothing to add to that. I agree.

DR. BORER: Does anybody around the table disagree with those
conclusions?

(No response.)

DR. BORER: No? Great.

We will move on to number 2. Of the 686 primary endpoint events on
placebo or losartan, 52 percent were creatinine elevation and 48 percent
were death or need for dialysis. All of the treatment difference was the
effect on creatinine. Was this a statistical anomaly? Was this because
there were just so few clinical outcome events? Was this because the
effect on clinical outcome would not be expected over 54 months? Was
this because an effect on serum creatinine is a poor predictor of
clinical outcome?

Why don\'t we stop there, and JoAnn, why don\'t you take those four
together? Then we\'ll go on to number 5.

DR. LINDENFELD: Let me start off with was this a statistical anomaly. I
don\'t believe so, and I don\'t believe that this was just that there
were so few outcome events. I believe that the serum creatinine is a
predictor of clinical outcome. I think when we look at the combination
of end-stage renal disease and death, that\'s positive. So, I would say
that, to just phrase this a little bit differently, we did see the
double endpoint of end-stage renal disease and death was positive, and I
think the creatinine is predictive of that. So, let me answer that that
way rather than these specific questions.

DR. BORER: Okay. With that having been said, what we saw I think was
that when you looked at time to first event, in fact, all the action was
here, but when you looked beyond that to death or end-stage renal
disease, bad things happen maybe because the disease progressed, which I
think is what you\'re saying.

DR. LINDENFELD: Exactly.

DR. BORER: Bob?

DR. TEMPLE: It still seems strange and not fully explained although, for
the reasons you just gave, not worrisome. When the first thing that
happens is end-stage renal disease, somehow that\'s not influenced. When
end-stage renal disease follows creatinine doubling, which in some sense
it always must, then it turns out to be okay. There must be something in
the analysis that led to that conclusion because it all doesn\'t make
sense, but maybe it doesn\'t matter for the reasons you just gave.
There\'s something odd about it.

DR. BORER: Statistical anomaly.

Before we go on to 2.5, does anybody on the committee have a different
view of 1 through 4? Steve?

DR. NISSEN: I just would say if it\'s a statistical anomaly, if I\'m not
mistaken, the same thing was seen in the previous trial, the IDNT trial.
So, there\'s obviously something biologically going on here, and I worry
about these people who didn\'t have creatinine measured, whether somehow
that\'s influencing it. How do you get to have end-stage renal disease
before doubling your creatinine? Well, one of the ways to get there is
nobody has your creatinine in hand, and so they don\'t know. Maybe
that\'s what\'s going on here, Bob. That would be one of my guesses.

DR. TEMPLE: But you\'d still expect it to be influenced. If there\'s an
overall delay, there ought to be an overall delay on end-stage renal
disease where you didn\'t get a creatinine just as much as where you
did.

DR. NISSEN: I hear you.

DR. TEMPLE: There\'s something wrong with the analysis here that we
haven\'t been smart enough to figure out. That\'s what I think.

DR. BORER: Tom, are you smart enough to figure it out?

DR. FLEMING: Well, I just want to take the burden off the statisticians
and put it back on the clinicians here.

(Laughter.)

DR. FLEMING: I can figure it out statistically, but I don\'t know what
the true clinical answer is.

Look at figure 379. You can\'t but just remember when you did look at
figure 379, which is the figure that showed what was the time to
end-stage renal disease distribution. Remember we were saying those
curves overlapped in the first 18 months and then separated thereafter.
So, statistically part of the reason that we are seeing the numbers of
people who have end-stage renal disease as their first event not being
different between arms isn\'t surprising when I look at this curve.

Now, I\'m going to ask my clinical colleagues the harder question. Why
is it, if there\'s an effect, that it doesn\'t show up at all for the
first 18 months and then emerges thereafter?

DR. BORER: Yes. I will try to answer that even though I\'m not a
nephrologist.

DR. FLEMING: Before you answer it, because I really do want you to, one
other aspect of this that does a bit to complicate things when we look
at the triple endpoint is when you look at doubling first and then
you\'re not necessarily following time to doubling in all people, quite
frankly I have a lot of trouble understanding the triple endpoint when
we have 267 people who aren\'t followed for one element for a
significant period of time. So, I prefer to look at the double endpoint
or the single endpoint here, ESRD, and in this endpoint the question I
would ask you clinically is, is there an explanation that you have for
why you don\'t prevent events in the first 18 months and then you do
thereafter?

DR. BORER: The entry criteria for this study, as I understand them, was
a creatinine of 1.5 to 3. Renal failure nominally is a creatinine of 6.
So, nobody entered even close to renal failure and they had to at least
double their creatinine to make it, and it takes some time to do that.
So, I\'m not at all bothered by the fact that there was a period of no
effect when you look at the ESRD as the endpoint.

Bob?

DR. TEMPLE: I guess one explanation is let\'s hypothesize that there\'s
a delay before you accomplish much with this therapy. That means the
end-stage renal disease endpoints that turned up as initial endpoints
were people who turned up with that problem very early. The die had been
cast, if you like, and wasn\'t as influenceable as later end-stage renal
disease. That makes some sense. Maybe we can model that or something.

DR. NISSEN: But the data was to the contrary, though, because the higher
your creatinine at the beginning, the more likely you were to see a
benefit. If you look at the subgroups of creatinine less than 2 and
greater than 2, almost all the benefit was in the people who started out
greater than 2.

DR. BORER: Ray, would you like to weigh in here?

DR. BAIN: Yes. We did look at those 64 and 65 end-stage renal disease
events that occurred without a doubling, and we looked at a number of
factors to try to understand why this occurs. One of the things that was
curious was you remember that the average baseline serum creatinine
across all groups was 1.9. If you look at those 64 and 65 patients who
went to dialysis without doubling, they had a higher serum creatinine.
So, they were worse off coming into the trial and maybe had a different
trajectory.

DR. BORER: Let\'s go on to 2.5. Is everybody else satisfied with this
discussion so far?

Let\'s go on to 2.5. Subjects who experienced doubling of serum
creatinine could later have end-stage renal disease or die. When these
events are counted, the relative risk of death on losartan was 1.02 and
the risk of needing dialysis .71. Are these data supportive of an effect
on clinical outcome?

I think we just answered that one.

3\. In RENAAL, the mean blood pressure was significantly lower in the
losartan group than in the placebo group. How does one know that blood
pressure alone was not responsible for losartan\'s treatment effects?
And 3.2, is the mechanism of the treatment effect relevant to the
description of trial outcomes?

JoAnn?

DR. LINDENFELD: I\'m not sure we absolutely know that this wasn\'t a
blood pressure effect, but we saw the data corrected for differences in
systolic blood pressure, pulse pressure, which made more of a difference
than the mean blood pressure. Although the effect was somewhat less, the
effect was still present. I feel relatively assured, based on this and
other data comparing amlodipine that we\'ve reviewed previously, that
this wasn\'t all a blood pressure effect.

DR. BORER: JoAnn has added a new wrinkle to the discussion that we\'ll
come back to later. Are there any other comments about that? Steve?

DR. NISSEN: Yes. I basically agree.

The difficulty I have is estimating the magnitude. Again, the reason it
becomes relevant here is this issue of a relatively marginal statistical
significance for the overall trial. When you\'ve got a marginal result,
then this analysis becomes very important. So, I think it\'s very
difficult to estimate the effect of blood pressure here. They made their
best guess at it. It was very reasonable and so on. But if it were a
larger effect due to blood pressure, then that marginal p value becomes
even more marginal. So, it becomes relevant in the context of a very
subtle drug effect.

DR. BORER: Dr. Brem?

DR. BREM: Well, I\'d like to come back to the dose issue again. The
design of the study was to titrate the medication up to dose effect and
then there seems to be a paradox that, once you\'ve done that, there\'s
no effect of blood pressure on renal preservation. I\'m still having
trouble grappling with the separation.

If the blood pressure isn\'t important, why didn\'t everybody get 100
milligrams and then you titrate the blood pressure so that you know 100
milligrams works or it doesn\'t work. Now, we have a third of the
patients who had 50 milligrams. Again, in reference to a prior study
that we reviewed in January, there was a dose dependence. So, I still
come back to separating the direct effects on the kidney from those that
are directly related to blood pressure.

DR. BORER: Yes, that\'s a toughy. For myself, I\'d come back to the
Asian data that we saw. The effect on outcome events was biggest and the
effect on blood pressure was negligible, if any, which would be
consistent.

Blase, was that your light on or Alan?

DR. CARABELLO: The blood pressure in the Asians was a little higher.

DR. BORER: But the treatment effect was less. The effect of losartan
relative to placebo was the least on blood pressure.

Alan, were you going to say something?

DR. HIRSCH: I was just going to repeat my same point. I feel like I\'ve
gained some support here. Just that I think it\'s hard to know the blood
pressure effect simply using adjustments within the study regressions.
This committee has often looked at this issue and determined that in
different populations one can predict different effects of a net blood
pressure difference. I would simply say for the record I don\'t think we
know.

DR. KEANE: And if I may just underscore the fact that we actually
titrated or up-dosed the losartan to achieve a blood pressure effect. We
weren\'t looking at the reverse of that. There were at least
three-and-a-half additional agents that these patients were on at any
given time interval. So, it makes it very difficult to tease out what
actually is going on with the effect of the drug as you change the dose.

DR. BORER: Tom?

DR. FLEMING: Just maybe to draw another distinction here and follow up
on what Alan is saying. There are at least two ways to look at
adjustments for the blood pressure. As I see it, the particular
differences are in the systolic blood pressure. Those are apparent at
baseline as well as over time. The imbalances at baseline we can handle
through a traditional covariate adjustment, and both that factor and
proteinuria are imbalanced at baseline. As the analyses that have been
presented to us show, the particular influential covariate there is
proteinuria, much more so than the imbalance in baseline of systolic
blood pressure.

But they started off, I think, at 153 versus 150, and over time they
ended up at 142 or 143 against 140. So, the separation was maintained.

So, the other question to ask, beyond whether there was confounding
because of baseline imbalance, is to what extent is the effect of
treatment mediated through the changes or differences that are seen over
time in blood pressure. Bob was talking earlier about the caution one
has to have when you\'re using time varying covariates to essentially
try to address the question, is the effect of a treatment on outcome
entirely mediated through a marker, in this case blood pressure over
time.

One classical approach statistically to do that is to use what\'s called
a time varying covariate, not just to adjust for differences in that
covariate at baseline, but differences in that covariate over time, so
that at the time of any event, you take into account what the person\'s
blood pressure was at that particular time.

The caution one has to have is that the way you interpret that, if
there\'s no difference after adjusting for that covariate, isn\'t that
treatment is not influencing the outcome, but the entire effect of
treatment seems to be accounted for by the effect of treatment on that
covariate, on that marker.

When this is done here, some of the effect is accounted for by the
differences in blood pressure, although it looks like, from what I\'ve
seen, the majority of this effect is still there even when you adjust
for the time varying covariate of blood pressure over time.

I agree with Alan\'s point about, however, as sophisticated as these
analyses are, you\'ve got to interpret them with great caution. For
example, that analysis is basically assuming that if the time varying
blood pressure is, in fact, influencing risk of outcome, it\'s
specifically mediated through what that exact last measured value was.
Maybe it isn\'t. Maybe it has more to do with what the value was over a
period of 6 months before that time or a combination of that blood
pressure and any other things, such as diastolic blood pressure or other
factors.

So, it\'s statistically the best approach I can think of doing. It\'s
what the sponsor did. It gives you a clue about whether or not the
effect of treatment is at least partially mediated through these
differences in blood pressure, but it\'s only a clue and one has to
interpret it very cautiously.

DR. BORER: We\'ve said a lot of things here and I\'m going to try to
summarize them just to make sure everybody agrees so that the FDA has a
clear statement.

With regard to 3.1, how does one know that blood pressure alone was not
responsible for losartan\'s treatment effects? I think the general
consensus is we don\'t know, but we think it probably didn\'t because of
all the things that people have said here.

And is the mechanism of the treatment effect relevant to the description
of trial outcomes? Well, we don\'t really know that either, but we think
that the outcome is not solely based on the effect on blood pressure,
but we can\'t say that rigorously.

Does everybody accept that? Okay. FDA you\'ve just heard it.

Comment on other secondary endpoint in RENAAL. There was a prespecified
analysis of time to first cardiovascular death, nonfatal MI,
hospitalization for CHF or unstable angina, stroke, or coronary or
peripheral revascularization. There were 515 such events with no
significant difference in the distribution between groups. Is this
evidence of a lack of clinical benefit? Is it comforting that there was
a lack of apparent harm? Were there simply too few events to show a
meaningful effect?

JoAnn, why don\'t you go ahead on 4.1?

DR. LINDENFELD: I think that there are too few events here, too short a
period of time, and a population that does not have as high a
cardiovascular risk as we might expect. So, I would say that this is not
necessarily lack of clinical benefit, it also makes it difficult to say
that there\'s lack of harm. We see very little difference. I\'m
comforted that there\'s no trend here toward harm. I think we\'d have to
follow these patients longer to see evidence of clinical benefit. I\'m
not disturbed, from what I\'ve heard, by the lack of clinical benefit. I
think that we just would have to follow more patients for a more
prolonged period of time.

DR. BORER: Is everybody in agreement with that? Are there any other
comments? Tom?

DR. FLEMING: Just to maybe refine, I agree with JoAnn, just to add a bit
to it in the spirit of what we also said three months ago in January.

It\'s very relevant to assess these cardiovascular events. Clearly, a
major portion of what\'s happening to these patients clinically that\'s
very important goes beyond the specific renal events into the
cardiovascular arena.

If one looks at the aggregation of these six components, one sees an
estimate of about a 9 percent decrease. If one had expected to have had
sensitivity, I guess I would have to say to you clinically how big does
the study have to be, and the answer to that depends on whether you
would require a 30 percent relative reduction or a 10 percent relative
reduction or a 5. If you actually required a 10 percent relative
reduction to be clinically meaningful, which is consistent with what the
point estimate is here, we would have needed to do a study of about
10,000 to 15,000 people. With 10,000 to 15,000 people, instead of 1,500
people, we would have been adequately powered to discern the difference
between a 10 percent reduction and no reduction.

So, I would disagree with the sponsor who, at one point, said these data
show no effect on these endpoints. I think these data suggest a 10
percent reduction, and it\'s not possible to discern whether or not
that\'s reliable evidence of a reduction or consistent with random
variability with no true reduction at all.

I also, though, break this down a little bit further to say, as we said
three months ago, not all of these are equally important, and we wanted
in particular three months ago to focus on cardiovascular events, MI,
and stroke. When I look at those sub-elements, it\'s about a 5 percent
relative reduction if we wanted high sensitivity. If you view a 5
percent relative reduction to be clinically relevant, you want to
distinguish that from no reduction, it would take 50,000 people.

So, my overall sense here is these data are suggestive a reduction of 10
percent. That\'s consistent with none. At least we can rule out that
there\'s not a 30 percent reduction. So, if you say that\'s what we
need, then this study is conclusively ruling out the kind of benefit you
would expect or you would want to see. I suspect that we wouldn\'t say
there has to be a 30 percent reduction. On the other hand, we could rule
out that there\'s harm by 10 percent.

Now, one of the comments that came up is look at cardiovascular death
though. That\'s going in the wrong direction. That\'s 90 versus 79, 10
percent in the wrong direction. That is something to think about. That
is, in fact ‑‑ and I will maybe discuss this more ‑‑ a signal that there
might be an increase, but in that small subgroup, that\'s entirely
consistent with worse than a 10 percent, maybe a 30 percent, reduction
or entirely consistent with no reduction at all to a 10 percent benefit.

So, in the same sense that I would caution against looking at 50 against
68 nonfatal MIs, saying, ah, we\'ve clearly prevented nonfatal MIs, I
would caution against looking at cardiovascular deaths of 90 versus 79,
saying we\'ve done something bad there. When we start subdividing these
into these sub-elements of the six, we really push the data beyond the
limits of what they can reliably be telling us.

So, my overall view of this is an extension of what JoAnn has said. This
study clearly should have, as it did, look at cardiovascular events.
It\'s suggesting a 10 percent reduction, but it would have had to be 5-
to 10-fold larger to be able to reliably discern whether that\'s truth
or whether that\'s in fact random variability off of no difference at
all.

DR. BORER: Is everybody in agreement with Tom? Are there any concerns?
Paul?

DR. ARMSTRONG: Are we going to have a chance to talk about the potential
for harm at some other point in the questioning sequence? I don\'t see
it, and if you want to reserve it to the end, that\'s fine.

DR. BORER: We will in the very next question.

DR. ARMSTRONG: I\'ll keep my powder dry.

(Laughter.)

DR. BORER: Actually the one after 4.2. Once we get to 5, we get into the
meat of the issue here. I\'m sorry about that. We\'re talking about
proteinuria, and I said the \"meat\" of the issue. Sorry.

(Laughter.)

DR. BORER: 4.2. Proteinuria, assessed as milligram per gram of
creatinine was lower on losartan at all times after baseline.
Additionally, the rate of loss of renal function, assessed by the slope
of reciprocal of the serum creatinine over time, was significantly lower
by about 13 percent in the losartan group. What did these results
contribute to the confidence one has in the clinical benefits of
losartan in RENAAL?

DR. LINDENFELD: These add confidence to the benefits we\'ve seen. I
think these are all consistent based on what we think the
pathophysiology of this disease is, to see a reduction in proteinuria
and a decrease in the slope of creatinine, and the fact that also that
the decrease in proteinuria correlates with the outcome. So, I think
these are all consistent and add somewhat to the confidence of the
results.

DR. BORER: Are we all okay with that? Okay.

Number 5. I\'m sorry, Paul, I misspoke. We\'ll get to the issue that you
raised somewhere in here, but not quite with this one because the focus
of number 5 is a little different.

Are the results of RENAAL alone an adequate basis for approval of
losartan for the treatment of type II diabetic nephropathy?

A drug with a related mechanism of action, captopril ‑‑ oh, sorry. I\'m
moving on here.

Are the results alone an adequate basis for approval?

DR. FLEMING: Just for clarification, you were right when you told Paul
that it\'s question 5. I assume in question 5 we now bring everything
together, including safety.

DR. BORER: Yes, okay. Paul, did you want to say something about that?

DR. ARMSTRONG: Well, I wanted to reflect on the fact that in the safety
presentation ‑‑ first of all, I\'m convinced this drug is effective.
I\'m also convinced that it has the potential for harm and that in
understanding that, a better appreciation of some of the issues around
hyperkalemia in particular seems to me to be germane.

So, where I\'m going with this, Mr. Chairman, is that the sponsor in the
safety presentation suggested that there were no deaths attributable to
adverse events. Yet, we saw data on two or three patients who died
suddenly who had potassiums of 7 and 6 as the last measured biochemical
indicators, which to me, while not establishing cause and effect,
nonetheless we\'re not able to dismiss that the sudden deaths in those
patients were not attributable to those potassiums.

Although we\'ve heard from elegant and sophisticated consultants about
the fact that hyperkalemia is common with these patients and therefore
we can expect that 1 out of 4 or 1 out of 10 might have either
hyperkalemia or potassiums greater than 6, many physicians treating
these patients will not be as sophisticated as those in this room. So,
the issue around how to balance that and to weigh it into a label and a
caution is the issue I wanted to bring forward because I was
uncomfortable that we have had adequate discussion around that. And I
say that still with the notion that this is an effective drug.

DR. BORER: We ought to have a little bit of discussion about that. I
think that we have to remember, in the context of that discussion, that
in talking about risk, we have to consider risk in the context of its
acceptability for the intended use, and the sponsor did give us an
all-cause mortality, all-cause horror show, risk versus benefit
relationship analysis. So, ultimately we\'re really talking about the
relation of benefit to risk.

Having said that, this is an issue that we didn\'t really get into in
any major way. Perhaps we ought to talk about that a little bit.

Bob, did you want to say something?

DR. TEMPLE: Yes. It may not be obvious from the question, but recall in
January in a similar situation the issue was whether a single study with
a p value in the neighborhood of .02 was sufficient evidence. So, this
is intended to introduce that ‑‑

DR. BORER: Yes. We\'ll get to that.

DR. TEMPLE: I just wanted to be sure.

DR. BORER: It hit me over the head like a sledgehammer that that\'s
where we were going here, but let\'s get the safety issue off the table
first. Beverly?

DR. LORELL: Well, the discussion today has raised an issue that I
hadn\'t thought about previously, and that deals with the time course of
apparent benefit that Tom Fleming brought up where one must wait for
about 18 months to see the curves begin to diverge.

We\'ve also seen some evidence which is suggestive. Although the trial
was not designed to look at this, there are some very elegant data
suggesting that the likelihood of benefit is greatest in those patients
who have a more severe degree of renal dysfunction, whether as estimated
as a marker using serum creatinine or magnitude of proteinuria.

So, I think the risk of hyperkalemia for the general public is a weighty
one in that the issue comes up, do we know whether or not we are
exposing a population that is going to have much less relative benefit
in terms of renal protection to a risk of hyperkalemia. I guess that
here what I think we didn\'t quite ever see that I think Dr. Hirsch
brought up is it would have been nice to see sort of the time course of
time to hyperkalemia to understand whether or not the time course of
exposure to risk of an event that is at minimum a huge hassle for the
clinician and the patient and at worst life-threatening, follows a
similar time course of benefit or whether there\'s a discrepancy there.
I\'m not sure if said that clearly.

DR. BORER: No, you did. It sounds as if we don\'t, at first glance, have
the data to answer the question rigorously.

But before Dr. Kopp weighs in here, Paul specifically raised this issue
in the context of a labeling discussion, and I would ask you whether you
think that your concern here is one that rises to the level of
approvability or is this something that really requires a big bold
caution in the label because we just don\'t know and we\'re not sure
exactly what subgroup really benefits? And obviously hyperkalemia kills.
So, is this a labeling issue? Is this an approvability issue? What do
you think?

DR. LORELL: I\'m not sure about it. I think in looking at the numbers
that I\'ve written down during the day, there was a sizeable number of
patients who had hyperkalemia of a magnitude that would, at minimum,
warrant getting the patient to the emergency room to give an
anti-hyperkalemic therapy. It looks like the development of even a
single hyperkalemic 6.0 or higher event was somewhat predictive of
death. So, I guess I would welcome discussion among others on the panel
on this.

DR. BORER: Dr. Kopp?

DR. KOPP: My comment was actually not so much about hyperkalemia. I
don\'t know if it\'s going to be off target, but it relates to this
issue of clinical benefit and who benefits the most. It\'s true if the
outcome is not seeing dialysis, not going on dialysis during the course
of the study, the greatest benefit was in those who had the highest
levels of creatinine. But if we understand this drug as slowing the rate
of decline of renal function, then you can argue that the person who
starts it earlier with a lower creatinine will enjoy more days of not
having dialysis because their rate has slowed. So, they might enjoy 1 or
2 years of being dialysis-free, whereas the patient who begins it late
with a creatinine of 3 or 4 has fewer months or years of benefit.

DR. BORER: Bob?

DR. TEMPLE: Is it a fair presumption that the people most likely ‑‑
maybe it\'s known from the data ‑‑ to become hyperkalemic are the people
who were more impaired? I ask that because these drugs are already
approved for the treatment of hypertension, irrespective of whether they
prevent renal dysfunction, and they, ACE inhibitors, and beta blockers
all increase the rate of hyperkalemia. We know that. It\'s in the label
and there are warnings about it.

So, are we looking at something that\'s worse than usual, and if it is
worse than usual, is it in the people who you think get the most benefit
or is it in everybody, including the people who don\'t seem to benefit
very much; that is, the people who aren\'t as impaired?

The company may have data on this.

DR. BORER: Yes. Do we have an answer to that question, Dr. Keane?

DR. KEANE: Yes. I was just going to show, first of all, one of the
slides to show the overall magnitude of the potassium levels throughout
the entire trial to reemphasize the fact that potassium is in the range,
throughout most of the trial, in the upper 4 milliequivalents so that
we\'re really not seeing a huge degree of hyperkalemia in this patient
population overall.

DR. ARMSTRONG: Mr. Chairman, 1 out of 4 patients were hyperkalemic with
losartan. So, when you say you were not seeing a lot of patients, for me
1 out of 4 is a substantial number. I\'m sorry.

DR. NISSEN: This slide is not relevant here.

DR. BORER: Yes. The average values may not speak to the point.

DR. NISSEN: They don\'t speak at all to it.

DR. KEANE: This is the percent of patients with an event described as
hyperkalemia in the losartan group over time compared to the placebo
group.

DR. HIRSCH: So that is a fourth. I think our concern is not the mean but
obviously those patients who lie near the limits would be at risk.

DR. TEMPLE: Is that a percent or a fraction? What is on the y axis?

DR. KEANE: That\'s percent of patients with an event.

DR. BORER: So, it\'s .2 percent.

DR. TEMPLE: Is it 3 percent, not 30 percent?

DR. KEANE: 25 percent.

DR. TEMPLE: So, it isn\'t the percent. It\'s the fraction.

DR. BORER: Beverly?

DR. LORELL: I\'m not sure I know what to do with this. But I think it\'s
of interest in thinking about this because the time course of
accumulating severe hyperkalemic events starts early and progresses. So,
we have, in terms of thinking about risk benefit, a period that goes for
many months where there\'s no difference between placebo and
intervention up against a period of enhanced risk. I think all would
agree, relative to your question, Bob, that this is a different level of
risk of hyperkalemia than is seen in the hypertension trials. In fact,
the hypertension trials would have excluded many of the patients, not
all but many of the patients, in this study.

DR. BORER: In all fairness, though, and without wanting to advocate one
position or another, when you look at the mortality curves, they\'re
spot on too during that period. So, it\'s a risk, but people weren\'t
dropping like flies because they incurred that risk. Obviously, whoever
was managing them saw the problem and dealt with it adequately. Again, I
think we have to consider ‑‑ maybe we just have to keep it in mind for
subsequent points on this list of questions ‑‑ that this is an open
issue. Should this be an approvability issue or should it be a labeling
issue?

Let\'s get to the intent of question number 5. This is a single study.

DR. KEANE: Can I just add so that we\'re clear about what the potassium
values were? I think as you look at the distribution of K levels between
5.5 and up to 7, the distribution that is occurring within the vast
majority of these is weighted at the lower levels, i.e., 5.5 to 6 and 6
to 6.4, towards losartan. But as you get into the higher potassium
levels that we were able to determine, they\'re fairly comparable both
in the losartan group and in the placebo group. So, I think that should
be taken into consideration when one talks about what the potassium
values are in these patients that are going to have hyperkalemia.

DR. BORER: Okay, thank you.

Well, the intent of number 5 really is whether a single trial is
adequate as a basis for approval. We have this study alone. We saw a
study in a related compound or a pair of studies in a related compound
with at least some similar pharmacologic effects three months ago.
We\'ve heard about data, and this committee when it was differently
constructed, considered other data that might be related having to do
with a compound that has some effects on the same system, the
renin-angiotensin system.

So, the question is do we have enough information from this one trial
alone, and if we don\'t, is there sufficient information available from
other sources that we have enough information in aggregate to draw a
conclusion about approvability.

With that in mind, we were all sent ‑‑

DR. THROCKMORTON: Jeff, I think I\'d like to break those up just a bit.
Let\'s stay focused on are the results from RENAAL alone an adequate
basis without taking into account any other data that you might want to.
You\'ll have chances in later questions to do that.

DR. BORER: Okay. Well, then let\'s just do that since that\'s what the
FDA wishes us to do.

Are the results of RENAAL alone an adequate basis for approval of
losartan for the treatment of type II diabetic nephropathy? JoAnn?

DR. LINDENFELD: RENAAL, taken in isolation, I don\'t think would make
this an approvable drug. I think the p value was not what we would
usually consider for one multicenter trial. We saw that as the primary
time to first endpoint, this was primarily a doubling of creatinine. My
answer to this would be no.

DR. BORER: Does anybody else have any comment about that? Does anyone
disagree with it? Steve?

DR. NISSEN: I don\'t disagree, but I want to make sure I say why I
don\'t think it\'s adequate.

First of all, it is a single trial. That alone is not a bar if the
single trial is very robust, but it\'s a single trial with a fairly
marginal p value.

Tom, in all deference to your comments, I have to use the triple
endpoint here. That was the prespecified endpoint. So, I focus a lot of
my thinking on you get one chance up front to choose your endpoint and
this is what they chose. Right or wrong, it\'s pretty marginal.

Then I\'ve got all these confounders to deal with. I\'ve got the problem
that if you take out the 250 patients from Asia from either the triple
or the double endpoint, it no longer is statistically significant. Now,
that does not meet my standard for a robust effect when it seems so
clear that it\'s being driven by a very small population. Similarly,
there are other confounders here, like the blood pressure difference.

So, when you take a marginal p value for the principal endpoint of the
trial and then you erode it with these other factors, then it doesn\'t
rise to that level of evidence that we\'ve typically required for
approval. So, alone RENAAL doesn\'t meet the standard from my
perspective.

DR. BORER: Does anybody else want to state an opinion about this?
Beverly?

DR. LORELL: I would like to. I spent some time actually reviewing the
criteria that the FDA itself has put out for a single trial because we
wrestled with this issue very recently.

I think that there was very compelling data presented both from this
study and in aggregate for many studies supporting a role of the
renin-angiotensin system in accelerating progression of diabetic renal
disease. And I doubt any around the table would disagree with that
biology.

But if one looks at the guidelines from the FDA itself to both industry
and those of us as reviewers for evidence of effectiveness from a single
study, there are several concerns, and I agree with JoAnn.

First, with regard to the endpoints that were presented to us in trial
design, there is not evidence of a highly statistically persuasive
outcome. The statistical outcome for the predefined primary endpoint was
marginal.

Secondly, we\'re advised to look at consistency across subgroups. Here I
think the issue of the gnarly problem of the data from Asia is very
problematic and really counts as a point of concern about consistency.

Third, very explicitly, we are advised to look in a single trial as to
whether or not there is evidence of efficacy in multiple endpoints
involving different events. The example that\'s given in the publication
from the FDA is quite helpful here. In this trial, the different events
that we are given to look at are end-stage renal disease and all-cause
mortality. I think one could argue very strongly that doubling of
creatinine and end-stage renal disease are highly coupled, and we know
that because the median time from going on to end-stage renal disease
after doubling of creatinine is only 30 days. So, if we look at the
criteria of different endpoints regarding clearly different events, this
trial does not quite make that criteria. There was not an effect on
all-cause mortality, nor was there an effect on a very important
predefined secondary endpoint of major cardiovascular events.

Finally, I am influenced by the concerns that the Steering Committee of
this trial itself had regarding the use of this drug in the context of
albeit insufficient data regarding ACE inhibitors in cardioprotection.

So, I think with the criteria that the FDA itself provides to its
advisors for thinking about efficacy in a single study, it doesn\'t
quite reach the burden.

DR. BORER: I\'m going to ask in a minute whether everybody agrees with
this, which I think we do. But I want to just ask for a little
clarification about the last statement. What I heard ‑‑ and we have the
person here who can tell us about it ‑‑ was not that the Steering
Committee was concerned about people not taking ACE inhibitors, but they
were concerned about half the patients not taking any drug that impacted
on the renin-angiotensin system. I think we don\'t want to
over-interpret what they did based on something they didn\'t mean. So,
can we just have a clarification about that?

DR. BRENNER: My name is Barry Brenner. I had the pleasure as serving as
the PI and the chairman of the Steering Committee.

You\'re correct. The late January \'01 meeting of the DSMB issued a
directive based on their review not only of HOPE but of another
publication that was soon to be printed, the Mann paper, which was a
substudy of HOPE dealing with patients who had renal disease. In that
study there was cardiovascular protection with ramipril. That was the
first time that a population akin to the RENAAL trial showed a benefit
in a clinical trial with interruption of the renin-angiotensin system.
That was late January.

Our committee convened on 10 February, very soon after learning of the
concern of the DSMB. And we were blinded, although they were not of
course. And we voted unanimously to terminate the trial a year before it
was scheduled to be terminated because our concern was that in the
placebo group there was no renin-angiotensin system blockade.

The decision was based on increasing evidence from HOPE to some extent
but much more compellingly from the Mann paper, not yet published, but
which we had in manuscript form, that in patients with renal disease ACE
inhibitors may be effective in reducing cardiovascular events, as I say,
in patients who had cardiovascular risk factors. So, it was because the
placebo group had not received and could not in the trial receive
blockade of the renin-angiotensin system.

Recall that when the trial began, there was virtually no evidence about
protective effect on the heart, cardiovascular system, with ACE
inhibitors. And the first paper that was compelling in this regard in
diabetics was the substudy of HOPE, and that was in the year 2000, five
years after we began. So, once we had now additional evidence, obviously
only coming from HOPE ‑‑ but that\'s all there was ‑‑ dealing with renal
disease and showing a cardiovascular protective effect, that drove us as
an independent body to terminate the trial.

DR. BORER: Thank you. I\'ve just learned that the FDA would like a
formal vote on this question.

DR. FLEMING: Could we have further comment first?

DR. BORER: We sure can.

DR. FLEMING: I\'d like to just add a little bit to this. This certainly
to me is the most critical question on the agenda.

As my colleagues have pointed out, great emphasis should be given to the
primary endpoint of the trial. There certainly is evidence of benefit
here. The p value was .02 on that primary endpoint. When we saw a
similar phenomenon or a similar strength of evidence in January, some of
us judged that as consistent with one positive trial but not two
positive trials.

Going beyond that, as has been pointed out, there are some safety issues
here, most discernably or notably the hyperkalemia. There are some
concerns about subgroups. As the FDA has asked us to look at consistency
across subgroups, we see within the Asian population an apparent
dominance in terms of where much of the positive signal is. And as has
been pointed out, there are some issues to address relating to the ACE
inhibitors and their efficacy and how does that complicate this. These
are all areas of concern.

Having acknowledged those areas of concern, though, I think there are a
number of really critical issues to consider. I\'d like to turn in
particular to the specific criteria the FDA has asked us to consider
about whether a single study is adequate.

We, in fact, have a large multicenter trial. That\'s the easy part.

Going beyond that, though, of real critical importance are the criteria,
are there multiple endpoints that essentially reinforce our sense of
strength of evidence, and are these results statistically very
persuasive findings. My own sense about that, even though it\'s
subjective, is something I\'ve always attributed to Ray Lipicky although
he denies it\'s his, but I always think of .025 squared times 2 as a
two-sided significance level that might be viewed as what you need to
see in order to be consistent with the strength of evidence from two
adequate and well-controlled trials. That\'s a p value of .00125.

When I look at these data and probe further, I acknowledge that ‑‑ and
I\'m very reluctant to move away from a prespecified primary endpoint
except in those very settings where I have a philosophical strong
concern about the appropriateness of the choice of that endpoint. To my
way of thinking, what we\'re looking at here is a combination of loss of
renal function and death, and we\'re trying to best characterize that.
I\'m at a loss for knowing why we have to use the component doubling in
creatinine time when it doesn\'t take that long to follow people, if it
really is going to translate into end-stage renal disease, to end-stage
renal disease. Hence, as some of us at least argued last January, we
were questioning the persuasiveness of the triple endpoint.

If this study had had a triple endpoint of four 0\'s and a 1, and the
double endpoint of end-stage renal disease/death had been a .03 to .06,
I would have called that at best a study that translates into the
strength of evidence of a single positive study. I.e., I would have
discounted the surrogate.

As a result, I think it\'s logically inconsistent for me, even though
I\'m a strong believer in adhering to the primary endpoint, that if I
would not have given credence to that primary endpoint, I should focus
on what it is that really matters, particularly in a setting such as
this where I can\'t interpret the primary endpoint because they didn\'t
follow 267 people to the triple endpoint. They did, to their credit,
fortunately from my perspective, followed everybody to what really to me
matters from a renal perspective, end-stage renal disease/death. When
you look at that endpoint, one gets significance levels on the order of
.002. That\'s for end-stage renal disease; .009 for end-stage renal
disease/death.

That\'s not, by the way, what we saw in January. When we looked away
from the triple endpoint into these elements last January, we were
seeing less strength of evidence, which for some of us was the concern.
Here we\'re seeing much more strength of evidence.

Furthermore, we asked, looking at a different domain, last January
please don\'t just show us the clinically important renal endpoints.
Also show us the most important, clinically important cardiovascular
endpoints, which before I ever looked at these data, we had specified as
end-stage renal disease, MI, stroke, and death.

When you look at those specific endpoints for stroke and death ‑‑
granted, cardiovascular deaths are notable as having 11 in excess in the
wrong direction ‑‑ strokes and non-cardiovascular deaths are 11 in the
right direction. So, overall, there\'s no difference. I\'m not claiming
as a result that I know that there\'s any benefit here on anything
related specifically to mortality, but over and above those measures are
the 47 excess deaths prevented on end-stage renal disease and the 18
events prevented on MI, which is a total of 65 events, which
statistically is at the .003 level.

So, now I\'m looking at what in January we called the clinically most
important events which, by the way, are the ones we can interpret
because that\'s where they had complete follow-up. What we see are
significance levels on the order of .002, .009, .003 before there\'s any
adjustment for an issue of baseline imbalances, which is another area
that causes many of us to be greatly cautious. Nevertheless, I\'ve been
persuaded that there\'s something here of real relevance, and when
adjusts for imbalances in proteinuria, there\'s another log reduction in
these significance levels.

Now, is there persuasive data here when you start subdividing into two
groups? Well, let\'s subdivide the Asian into the non-Asian populations.
Now, that\'s in a certain sense not particularly optimal for this
intervention because we did so specifically having seen the greatest
signal coming from the Asian population.

But when we do so, if you go with me for the moment to what\'s the most
important endpoint, which I don\'t believe is the triple endpoint ‑‑
it\'s the double endpoint ‑‑ when you look at the double endpoint and
you adjust for proteinuria, it must be significant. Clearly the Asian
subgroup is significant even without adjusting for proteinuria. The
sponsor showed us the double endpoint in the non-Asian patients had a
lower confidence interval. It was very close to 0 even before adjusting
for proteinuria.

So, if you focus on what really matters, end-stage renal disease and
death, and account for what is a pretty strong case for an imbalance at
baseline adjusting for that, even if you simultaneously also adjust for
the systolic blood pressure differences, you\'ll find subgroups in the
Asians and the non-Asians that I strongly suspect and can ask the FDA to
validate will, in fact, be significant in both of those groups.

So, as I look through these criteria, I am seeing statistically
persuasive findings that are on the level of .00125, and we are seeing,
across the endpoints that really matter, the renal endpoints alone or
the renal and cardiovascular endpoints that last January we designated
as the most important, there\'s a significant difference there as well.

What about the consistency across subgroups? That is certainly a
relevant concern. There are some uncertainties, but the analysis that I
was just giving of the Asian/non-Asian on the dual endpoint I think does
show that there\'s benefit across both groups.

What about hyperkalemia? It\'s harder for me to assess that. We\'re
seeing, over 3 to 4 years, a difference in 10 to 12 percent against 25
percent. But unless you would believe that that would translate into
influencing negatively these hard clinical endpoints long term and, if
anything, if we\'re going to project out long term, I\'m thinking we
have every reason to think the effects here are going to be even
greater. These curves are diverging. I hate to put emphasis on what we
haven\'t seen, but if we\'re going to extrapolate what the adverse
effects of hyperkalemia may be that we haven\'t yet seen, and if you\'re
going to take the liberty to do that extrapolation, you should take the
liberty to extrapolate what these effects are. They\'re growing over
time. The separation between these curves in ESRD-free survival are
actually growing over time.

The last issue is the issue of how to address the ACE inhibitor. At
least my understanding is if we assumed that we knew the ACE inhibitor
was effective and we have a placebo-controlled trial and if in fact you
look at these data and say that this is establishing that losartan is
effective, it seems to me the question isn\'t whether you approve
losartan. The question is can we motivate the conduct of a trial
following the approval of losartan that would allow us to establish
whether we should be using an ACE inhibitor or an ARB or the combination
thereof. That seems to me the relevant follow-up question if there is in
fact some uncertainty.

So, when I look at these FDA criteria, I find very strong evidence to
suggest that what we are looking at as those factors that need to be met
for this study to be viewed as adequate for approval are in fact met.

DR. BORER: Since we\'ve been asked for a vote, let me translate that
into simple terms. Is RENAAL alone an adequate basis for approval of
losartan? Tom?

DR. FLEMING: Do you want my vote?

DR. BORER: Yes.

DR. FLEMING: Yes.

DR. BORER: Let\'s start at the other end of the table because we
haven\'t given them too much of a chance, and then we\'ll come back
around. Yes or no and give a reason.

DR. BREM: I guess yes, after that compelling discussion.

(Laughter.)

DR. BREM: I was going to say it\'s equivocal, but I\'ve been certainly
swayed by your arguments. So, I vote yes.

DR. BORER: Dr. Kopp?

DR. KOPP: Yes, I have a problem here too that I was of the belief that
the great sin was to do other than what was laid out initially, and I
think coming from a statistician, what you have said has been swaying
me. I actually would have preferred to vote last and see what other
people were saying.

(Laughter.)

DR. KOPP: But since I\'m going at this point, I would have to say yes.
And I guess the reason is because I am swayed that ESRD is important,
that there was a significant difference.

DR. BORER: Bob?

DR. TEMPLE: Well, just to be sure. I\'m certainly not trying to
influence the answer. But alternative analyses are always persuasive to
the people who like them. It\'s just worth remembering. I think Tom is
very sensible, but he\'s presenting you an analysis that he finds
persuasive for reasons that he gave. But subgroup analyses and
alternative analyses and covariate analyses that we see all the time are
always persuasive. Just don\'t forget that.

(Laughter.)

DR. BORER: Paul, are you persuaded?

DR. ARMSTRONG: I\'m not allowed to vote with the knowledge of the field
and taking other things into account. It\'s only on this data. And if I
knew nothing else about the field, I would be optimistic but reserved
and would probably vote no.

DR. BORER: Do you want to state for the record a couple of reasons?

DR. ARMSTRONG: Just the strength of the analysis and the fact that it\'s
a positive trial, and I think it\'s effective. But it\'s one trial and
the evidence isn\'t of the usual standard. But clearly we haven\'t heard
the end of this discussion today.

DR. BORER: Beverly, I think you already gave all your reasons, but if
you have any more to add, go ahead and give your vote.

DR. LORELL: I would still vote no. I think Tom Fleming\'s discussion is
very persuasive, but nonetheless, it\'s not our job to redesign the
trial and the primary and secondary endpoints that were predefined. So,
using the predefined endpoints of this trial, I would vote no.

DR. BORER: Susanna?

DR. CUNNINGHAM: Well, I\'ve been challenged all day as I\'ve listened to
all the discussion and been going back and forth and thinking about what
does this mean to the person who has renal disease and what does this
mean to the person who is going to be developing renal failure. I think
after listening to Tom\'s very persuasive presentation and thinking
about what it would mean perhaps to have 6 months less of renal failure,
I would say yes in this case.

DR. BORER: Steve?

DR. NISSEN: I think I\'ve already stated my reasons, and actually, Tom,
although you are very persuasive, I was not persuaded.

(Laughter.)

DR. NISSEN: A lot of what I know you taught me, and I still think to go
beyond the primary prespecified endpoint of the trial, you\'ve got to
have very compelling reasons to look at what you\'re looking at.

I do also agree with what Bob Temple said, which is I can take data and
I can contort it almost any way I want and come to a conclusion.

But I look at the primary efficacy endpoint, and I really believe that
it was marginal and that it was really troubling to see that it all came
basically from one subgroup. I just don\'t think that\'s the compelling
evidence that a single trial needs to have. And the word is
\"compelling,\" and it\'s just clearly to me not there from this single
trial. And I reserve the right to vote otherwise based upon other
information today, but on this trial alone, I don\'t think it comes even
close.

DR. BORER: I would vote no also. I think that these are very suggestive
data, that it\'s a positive trial, but I\'m concerned about the lack of
robustness as judged by the different results across different groups.
Things tend to go the same way, but the magnitude is highly variable.
There are a lot of confounders that I can\'t interpret fully. There are
inadequate data to draw firm conclusions about cardiovascular events,
although that is not a show stopper, and there are some concerns about
safety that also aren\'t show stoppers but I would like to see some
confirmatory evidence before I would vote yes. So, I will vote no for
this trial as a single trial to be sufficient for approvability.

Alan?

DR. HIRSCH: The last three speakers have mostly summarized most of my
reasons for voting no.

But having the microphone on, this really was a visionary trial design
when it was created. It\'s landmark in its ability to show a definitive,
clear change in ESRD in this particular population studied.

But I really do believe it\'s important for us to stick to the true
trial, high significance design with no homogeneities that are evident
with robust, overlapping positive outcomes, especially ‑‑ and I\'m bring
to the table another issue ‑‑ in an era when I think all of us are
seeing an effort for us to reach to molecules and to study them in a
global design, bringing in multiple countries in a way that ultimately
that, besides our USA mandate, will be used for global marketing.

When we have a single trial of what I think is sort of borderline
significance, I think the standard has to be very high, and I\'d like to
caution all of us not to lean on single trials, ignoring everything else
that we might know about ARBs and ACE inhibitors, before we set a new de
facto standard. These standards should have the very highest level of
knowledge. We\'re not there with a single trial.

DR. BORER: Blase?

DR. CARABELLO: Yes, I agree. I think that we\'ve made mistakes based on
single small trials. If this were 30,000 patients, that might be one
thing, but I do agree that single trials are dangerous. But my major
reason for voting no here is I can\'t get away from the fact that almost
the entire benefit was concentrated in a tiny subsection of the study
without even a trend in the other subpopulations.

DR. BORER: JoAnn, as our committee reviewer, you have the last word.

DR. LINDENFELD: I would say again no for the reasons that have been
stated. I think this study by itself is not quite convincing enough.
Also, by itself I don\'t think it gives us as much assurance that this
isn\'t just a blood pressure effect.

DR. BORER: So that means we can go on to the subsequent questions.

A drug with a related mechanism of action, captopril, has an indication
for diabetic nephropathy in patients with type I diabetes. The primary
basis of that approval was the demonstration in a 409-subject, 2-year
study, of 51 percent reduction (p equals .004) in risk of doubling of
serum creatinine alone, and a 50 percent reduction (p equals .006) in
risk of mortality or end-stage renal disease. Both effects were manifest
in the first few months of treatment. Captopril also reduces the
progression of microalbuminuria to overt proteinuria.

Are the results with captopril germane to a discussion of losartan? In
particular, 6.1, is nephropathy in type I diabetes enough like type II
diabetes? 6.2, are the pharmacological effects of captopril and losartan
adequately similar?

JoAnn?

DR. LINDENFELD: We discussed this in January with the same question, and
I think at that time we felt that the nephropathies in these two were
very similar. The patients are more different perhaps than the
nephropathies in some of their other covariates.

And the pharmacologic effects, while not the same, are similar.

DR. BORER: So, then you think the results of captopril are germane to
the discussion.

DR. LINDENFELD: Yes. Sorry. I do.

DR. BORER: Does anybody disagree with that? Steve?

DR. NISSEN: Yes, I guess I don\'t agree. While the drugs affect the same
enzyme system, they attack it at different points. Gosh, I could give
you innumerable examples of drugs. Even within a class, it\'s tough to
know whether an effect is held across the class. There are some very
good examples of drugs where one drug in the class actually is effective
and the other drug isn\'t.

Now we\'re asked to look across two classes of drugs. The minute you
broaden it to that point, I think it\'s a terribly slippery slope. I\'ve
had a lot of time to think about this since January, and I feel more
strongly than ever that you can\'t extrapolate ACE inhibitor data to
ARBs and you can extrapolate ARB data to ACE inhibitors. And you really
shouldn\'t try. Even in the ACE inhibitors, there are issues of tissue
selectivity, et cetera. We don\'t know if they\'re important or not,
Bob, but the point is that\'s even within an individual class, let alone
across two classes. So, I really do think this is dangerous.

DR. BORER: Paul?

DR. ARMSTRONG: In the same way that I\'m unable to transfer the effects
of ACE inhibitors to ARBs in cardiovascular disease, which I know more
about than this subject, I would not be prepared to do it with the
subject matter at hand.

DR. BORER: Dr. Brem?

DR. BREM: I would say the question before us really, is there some
similarity and can you draw from that similarity ‑‑ I don\'t pretend to
say that they\'re equivalent and I don\'t thinks that\'s the question
before us. We\'re just asked is there some relevance from one to the
other, and I think the answer to that is probably yes, there is. They do
have some potential common modes of action.

And diabetic pathology, the actual structural changes and so on are
quite similar from one to another. Many of the pathologic mechanisms
involving glycosylated end-stage products and proteins and so forth are
quite similar.

So, I think there is a similarity, but it\'s not equivalence. I think we
should recognize that.

DR. BORER: That\'s with regard to type I and type II diabetes.

DR. BREM: And the captopril and losartan, that there are similarities
that you might be able to draw upon, but they\'re not equivalent.

DR. BORER: I\'d like to comment on that too. I agree with those who
would not accept the captopril data as particularly germane. That is, I
agree with Dr. Brem that there is something there. We are affecting the
same system, and therefore at the very least, the effects of captopril
would, for me, support the generation of a hypothesis that ARBs work in
patients with diabetes to protect the kidneys. But beyond that, I\'d
have a hard time going because there are, I think, potentially important
differences in pharmacologic effects between the two classes.

I agree absolutely with Steve. Among the molecules within a class, I
think we\'ve seen many examples of different pharmacologic effects
besides the primary ones that we think about and therefore I would want
to see more information than merely the captopril information to support
losartan effectiveness.

On the other hand, I say again that I agree with Dr. Brem, that there\'s
something here that supports at least the hypothesis that ARBs work, and
then we have to study them.

Alan.

DR. HIRSCH: One more extrapolation of that. Obviously, there are
relationships between these drug classes that let us form hypotheses to
lead to new clinical trials and there are similar effects. Let\'s ask
the question. How would we all know on this panel or how would we know
designing if they were similar or not? What it would take would be
comparative trial data in humans. So far, what we\'re doing on this
panel I think is taking monotherapy versus placebo in trials from
different populations and different investigators and then trying to
make comparisons. That\'s not how we\'ll decide if they\'re similar or
not.

DR. BORER: Beverly?

DR. LORELL: I agree, Jeff, with your summary on this issue.

DR. BORER: Tom?

DR. FLEMING: I largely agree as well, Jeff. The FDA in a number of
instances in the past, as I understand, has followed a strategy that I
think makes a lot of sense. If they\'re working with the sponsor in
setting up a development program and recognizing that we need
confirmatory studies that a strategy has been at times to have two
studies of the agent done in pathophysiologically related settings and
if the studies are both positive, they reinforce each other and we
obtain the confirmatory evidence in that manner.

If one level of germaneness would be is this in fact a study of that
nature that could reinforce the RENAAL study ‑‑ and my sense is not at
all ‑‑ in fact, if we believed that the captopril study provided
evidence that was that relevant, I would wonder why this committee or
the FDA in general hasn\'t approved captopril in type II diabetes, step
one.

Step two is it\'s a different class, as has already been mentioned by my
colleagues, and my clinical colleagues can address this much better than
I.

So, my own sense is at a certain level it is germane, but I would
consider it a pretty modest level because it is in fact a related, but
still different, setting with a different class.

DR. TEMPLE: Jeffrey?

DR. BORER: Bob.

DR. TEMPLE: Just to be clear, we anticipated that people might find the
single study standing on its own not a million miles away from
sufficient but fairly close. This was an invitation to think about
whether something in a closely related pharmacologic class tipped you
over.

DR. BORER: And you\'ve heard that it wasn\'t so far.

DR. TEMPLE: Yes. This was to offer you that opportunity.

DR. BORER: On the remaining four questions, we need to have a formal
vote with reasons.

First, if the results with captopril are relevant to losartan, are the
results on ‑‑ well, we\'ve actually said what we needed to say. Do you
want a formal vote on 7 now?

DR. THROCKMORTON: 7 has been answered to our satisfaction. If you would
just go to 8, that would be terrific.

DR. BORER: Let\'s go to 8. Are the results of RENAAL and prior
expectations derived from the captopril database an adequate basis for
approval of losartan for the treatment of ‑‑ I think we\'ve answered
that one as well, but we can give a formal vote, if you like.

DR. THROCKMORTON: Yes, if you wouldn\'t mind.

DR. BORER: Okay. Why don\'t again we start at the far end of the table
here. Dr. Brem?

DR. BREM: Sticking my neck out first, yes, I would vote for approval. My
thinking is that while both classes are clearly different, I absolutely
agree with that, and there are perhaps subtle mechanisms of action which
may be different, and when we argue that type II diabetes and type I
diabetes aren\'t exactly the same either, there\'s enough supporting
evidence, in terms of direction and efficacy, that I would use those two
together to make a story that it\'s worth approval.

DR. BORER: Dr. Kopp?

DR. KOPP: Well, I earlier said that RENAAL alone was sufficient, so
obviously I have to say that A plus B are sufficient. I don\'t actually
find that the ACE inhibitor data adds much.

DR. BORER: Paul?

DR. ARMSTRONG: No.

DR. BORER: Beverly?

DR. LORELL: No.

DR. BORER: Susanna?

DR. CUNNINGHAM: Yes and no.

(Laughter.)

DR. BORER: We need a comment there.

DR. CUNNINGHAM: I already said yes for the first, so that\'s my
statement. But I don\'t believe that captopril is the same thing. I
believe it has a different action, so I can\'t say yes to the whole
thing.

DR. BORER: Steve?

DR. NISSEN: No.

DR. BORER: And I vote no.

Alan?

DR. HIRSCH: I\'d like to keep some suspense going here for a while.

The previous question was more theoretical, and I gave a very vigorous
theoretical answer. When we come to practical gestalt sense of things, I
am swung a bit, although I will tell you I haven\'t quite swung over, so
I\'m still a close no.

DR. BORER: Blase?

DR. CARABELLO: No.

DR. BORER: JoAnn?

DR. LINDENFELD: No.

DR. BORER: Tom?

DR. FLEMING: I\'ve already said yes based on RENAAL. I would agree.

DR. BORER: The record should show that Tom agreed to yes/no.

Okay, we\'re up to number 9. Let\'s go through number 9 and then I want
to ask a question. Number 9. In considering the approval of irbesartan
for diabetic nephropathy, the advisory committee expressed interest in
the program for losartan, which we did. The respective sponsors now have
reciprocal agreements allowing reference to IDNT and RENAAL in support
of one another\'s programs.

Do the findings of IDNT support the effectiveness of losartan for
diabetic nephropathy? Why don\'t we start with that and then we\'ll go
to 9.2 separately. JoAnn, do you want to start with that?

DR. LINDENFELD: I believe the IDNT results do support RENAAL, and I
think a doubling of creatinine was the primary finding there. But
doubling of creatinine in my own mind ‑‑ and we discussed this last time
‑‑ is more than just a surrogate. Doubling of creatinine is a real
result that I think we can see in the clinic that applies to patients.
Yes.

DR. BORER: Tom?

DR. THROCKMORTON: Jeff?

DR. BORER: I\'m sorry. Yes.

DR. THROCKMORTON: I wondered if we could maybe get just a little more
discussion around this question. Maybe it wasn\'t worded quite as well
as we could have. Part of this was what\'s your level of comfort about
thinking of two drugs from pharmacologically related classes as
supporting efficacy. You can imagine some people might be uncomfortable
doing that in the same sense that we heard some uncomfort about the ACE
inhibitor data informing your decisions about an ARB. Maybe that\'s a
foregone. Maybe that\'s easy. There\'s no question that it\'s
informative and could be supportive, but if there is anything short of
that, it would be interesting to hear some thoughts along those lines.

DR. BORER: Okay. I thought you wanted that in the context of 9.2, but
that\'s fine. Bob?

DR. TEMPLE: Whenever. This is a slightly radical concept for us. That\'s
why we sent you the evidence document which discussed it. Give me a
minute to just say something about that document.

One of the things it did was describe all the circumstances ‑‑ it was
our attempt to describe all the circumstances in which we would accept a
single study of a particular drug and a particular use as sufficient
evidence. You already referred to one. If it\'s really strong and the p
value is out to the end of your arm and there\'s internal consistency,
fine, we\'ve all done that, and that\'s fine.

We also defined a whole bunch of situations in which one would draw
further support from other controlled trials. Now, you can say that\'s a
Bayesian prior or you can say you really have another study and it
doesn\'t really matter. We give a whole list, studies of different
doses, other regimens. There is one thing toward the end of that list
that talks about pharmacologic and pathophysiologic endpoints.

Although the words aren\'t as clear about the present situation as one
might have liked, because we didn\'t really think of it, there is a
suggestion that when knowledge of the pharmacology, coupled with
clinical evidence that that pharmacology is relevant, is present, that
you might be able to rely on a single study, not no studies. We\'re not
talking about class labeling or anything like that.

The main difference between the past cases that we considered and this
one is what we had in mind when we wrote it is, oh, you\'ve got 12
studies of ACE inhibitors. Maybe now one more might do.

In this case, there isn\'t any approval of any of them. So, there\'s a
certain simultaneity that we hadn\'t really come to grips with. You\'re
thinking about one study is supporting a drug, coupled with another
study supporting another drug, and vice versa, sort of a crossover,
where there isn\'t any established track record, approved drug. But we
thought that was close enough to the situation we had contemplated to
invite you to think about it, and we\'re thinking about it internally
too.

It\'s something of a novelty, although as we\'ve pointed out when we
looked at it, we\'ve been approving new heart failure claims for ACE
inhibitors based on single studies with p values between .05 and .01
right along. We have not identified that as being based on the prior
experience, but there\'s no other good explanation. We have not insisted
on p values at .00125 or anything like that. So, we\'ve been engaging in
this without making it particularly explicit. So, this time we\'re
making it explicit and giving you hard work.

DR. BORER: Well, we\'re explicitizing here. I guess that given that
preamble, JoAnn, you may want to discuss 9.1 and 9.2 together.

DR. LINDENFELD: Yes. Again, I think the findings of IDNT do support the
effectiveness of losartan. The captopril helps just a tiny little bit I
think for several reasons. We\'ve seen a pathophysiology here and a
biologic plausibility that\'s consistent. We\'ve seen a doubling of
creatinine in both studies that\'s relatively similar, although we
didn\'t see the end-stage renal disease in IDNT I think we\'ve seen in
this, and for all the reasons Tom said, I think we see a consistency of
overall benefit here and no specific differences in the drugs that I can
see that make me concerned that we\'re dealing with some sort of
different mechanism among the single class of drugs. So, for all these
reasons, I do think that IDNT supports RENAAL.

DR. BORER: So, going to 9.2.1, are the findings of IDNT as persuasive
for losartan as would be a replication of RENAAL?

DR. LINDENFELD: No. I think a replication of the same study with the
same drug would be more persuasive, but a little bit more. I can\'t put
a number on that.

Let me just get the next one. A second study demonstrating losartan and
slows progression I don\'t think would be as persuasive as IDNT. We\'ve
said that proteinuria alone we\'re not willing to consider as an
endpoint in itself. So, 9.2.3, a study demonstrating progression to
microalbuminuria would not be as strong.

And beating an active control arm in RENAAL, I think I\'d have to
understand exactly what you meant by that.

DR. THROCKMORTON: That was a reference to the IDNT trial where, if you
remember, there was an active control arm.

DR. LINDENFELD: Yes. I think for all the reasons we said there, because
it\'s hard to tell if an active control arm might cause some problems,
that that would not be as strong either.

DR. BORER: So, it sounds as if ‑‑ I\'m trying to pin you down here so we
can move on to the next one with real confidence ‑‑ that IDNT is
supportive of RENAAL but not quite as supportive as a second trial would
have been.

DR. LINDENFELD: Right.

DR. BORER: And we\'ll get to the next question about whether it\'s
supportive enough.

Tom, what do you think about that?

DR. FLEMING: I think I largely agree point by point with JoAnn\'s
answers. My sense is clearly here what we\'re dealing with now is an
agent from the same class and a study in the exact same setting, which
adds to the relevance, but to my way of thinking clearly is not as
persuasive as if we had a second trial of losartan in type II diabetes.
So, it is certainly addressing some of the concerns that at least I had
in the previous question, but it\'s less persuasive than another trial
would be of losartan.

I think it\'s relevant here because at least some of us viewed that the
IDNT trial provided a strength of evidence consistent with, just barely,
one positive study. At least some of us argued that was one positive
study, just barely, but not the greater strength of evidence that we
would think you would have to have had to base an approval on that.

And the surrogate, microalbuminuria, study that was presented in that
setting, if it were presented in this setting, as JoAnn said, I would
view to be of relatively low persuasiveness. That\'s the type of study
that adds to the sense of biological plausibility, but I want to see it
confirmed with a clinical endpoint trial.

So, it\'s not necessarily symmetric here. Maybe I need to clarify that,
but in essence what I\'m viewing is that with RENAAL in hand and with
IDNT being viewed as a single positive trial, it doesn\'t really provide
the strength of evidence of a full separate trial, but it certainly is
relevant and provides some additional strength of evidence to RENAAL.

DR. BORER: Blase?

DR. CARABELLO: You\'re asking for comment or a vote?

DR. BORER: We\'re asking for a vote and a reason.

DR. CARABELLO: I would vote yes.

First of all, I want to point out that being from Philadelphia, I
thought IDNT was a word, like \"IDNT a nice day,\" using it in a
sentence.

(Laughter.)

DR. CARABELLO: I think these two agents are extremely close together. I
think they constitute two confirmatory trials, that they are effective
in type II diabetes, and I would vote yes for approval.

DR. BORER: It wasn\'t the approval issue.

(Laughter.)

DR. CARABELLO: I vote that they\'re complementary.

DR. BORER: Alan?

DR. HIRSCH: Can I make this simple? I think they are clearly
complementary, but as Tom has said, ultimately it would be nice to have
a single molecule studied definitively before we create a new precedent.
The reason for that is, again, that we tend in our pharmacologic era to
try to differentiate products even within the same class when that\'s to
our benefit, and now we\'re trying to lump them when it\'s to our
benefit. At some point, we need secure knowledge again. But they clearly
are supportive.

DR. BORER: I would vote that IDNT is certainly supportive of the
effectiveness of losartan. As JoAnn and Tom and everybody else said, I
find the persuasiveness somewhere short of replication of RENAAL and
forget about the other two. I\'ll tell you why.

There are some outstanding safety issues that we want resolved here, and
while I can accept IDNT as sufficiently supportive of efficacy of a drug
that does the things that both of these drugs do in common, so that
that\'s nicely supportive, the safety issues are harder for me to
understand. Small differences in pharmacologic effects based on
molecular structure might well alter the safety profile a little bit.
The magnitude of hyperkalemia that occurs, what have you.

Since those issues weren\'t really adequately resolved or completely
resolved ‑‑ I shouldn\'t say adequately ‑‑ for losartan in this one
trial, I am concerned that they\'re still not resolved when I have the
IDNT data. The cardiovascular protection issues remain again. Here too,
I\'m not sure that two drugs of the same class do exactly the same
thing.

So, if I were to, ultimately at the end of the day, say that the
concordance of evidence is sufficient so that we should approve losartan
for the indication that\'s being sought, I would write the label very
carefully to indicate what we don\'t know and what\'s left out here.

I think that I would reemphasize what I said earlier, particularly in
view of what I\'ve just said, that if we vote to approve the drug, that
the FDA should cause something to be written into the label that makes
it clear that we are not in any way suggesting the data are sufficient
to mandate that this drug should be used in preference, say, to ACE
inhibitors or whatever else we may be doing. That\'s hard to do. I
understand, but I think that that\'s important because of the paucity of
information we have.

And finally, I think it\'s very important that if we believe this as a
committee that we go on record saying that we do not believe that if we
choose to vote for approval, that we\'re suggesting in any way that that
mandates class labeling for ARBs. It may be that the FDA was never
thinking of that. I\'m sure the FDA never was thinking of that, but I
personally would like to say that I don\'t think that that would be
right.

DR. TEMPLE: Yes. I really wanted to make that clear. We\'re talking
about when a single study of ordinary persuasiveness as opposed to
superior persuasiveness would be enough. We\'re not talking about a
no-study standard. We\'re more risk-averse than that.

DR. BORER: Well, so having said that, again in summary, I believe that
IDNT supports losartan. I have concerns. I don\'t think it\'s the same
as a replication of RENAAL or a second study with losartan. Where we end
up on that depends on some of the ancillary issues about labeling that I
raised.

Steve?

DR. THROCKMORTON: Jeff, but what I\'m hearing is most of your concerns
have to do with safety exposure. And I heard some of the same things
from Alan. Is that what you\'re suggesting?

DR. BORER: Well, I am concerned about safety. Let me say also that with
regard to efficacy, I would prefer to have a second study of losartan.
However, I would be willing to accept the concordance of evidence from
IDNT and RENAAL as sufficiently demonstrating efficacy for diabetic
nephropathy. The issue of approvability, however, relates to efficacy as
related to safety, and there I have some concerns and I just want to
express those.

DR. THROCKMORTON: Yes, but the only reason I was saying that is here we
have a large safety database of the two compounds because they are
approved. You might imagine a place where two unapproved compounds ‑‑

DR. BORER: True. Well, the fact is we\'re talking here about people with
near end-stage renal disease, which changes the ball game a little bit,
and it may be that within the dossiers that have been submitted,
there\'s a lot of information about that. That may resolve the issue. I
don\'t know those data because they weren\'t presented.

DR. FLEMING: Just one more clarification before we go on.

DR. BORER: Tom.

DR. FLEMING: A comment that Bob just made I think, at least from my
perspective, it would be appropriate to just have a quick follow-up. I
think what Bob was pointing out was this is the type of consideration
that\'s especially relevant when you have a single study and it provides
‑‑ I think your words were ‑‑ an ordinary level of or what I would call
just an adequate level of strength of evidence to meet what we would
think of as the standard for this to be called a single positive trial.
And does this evidence reinforce it at a level that would lead you to
say, now we can approve, as opposed to where you might say you don\'t
need this if you viewed that that single trial was of the strength of
evidence of two positive studies.

I would just point out that I don\'t disagree with that. I would just
point out that those of us ‑‑ and some of us have said so, that we view
this IDNT trial as relevant but less than the strength of evidence that
you would have had by another study, technically speaking, would argue
that you could readily have a single positive trial of the agent in hand
that just barely is adequate to be judged as a single positive study
and, hence, a companion trial that together doesn\'t make it because the
second study is less than the same strength of evidence.

By the way, one last point is keeping this in mind, to be consistent, if
that other trial goes in the wrong direction, we would equally be
weighing that; i.e., if it\'s relevant, it\'s relevant whether it\'s
positively reinforcing or negatively reinforcing.

DR. TEMPLE: I think that\'s true.

We haven\'t asked you to compare the two studies here, but I just want
to remind you the other guys beat two drugs, including one where the
effect on blood pressure was almost the same. So, it has its own
strengths too, but each one has somewhat different strengths.

DR. BORER: It\'s interesting. I think, though, I want to add something
to what I said earlier in light of Tom\'s comment. I\'m persuaded by
IDNT in part because of my interpretation of RENAAL. Even though I
wouldn\'t have accepted it as a single study that is dispositive for
judgment or for approval, I do think it\'s better than the p equals .022
for the primary endpoint because I too am persuaded, as Tom is, that the
hard endpoints are more important.

So, I give a little bit higher bounce to RENAAL than it might have had
nominally and a little bit lower bounce to IDNT than anybody else might.
But you put the two together, and that makes me feel reasonably
comfortable about the effectiveness. And then I have the other issues
that I mentioned.

Steve?

DR. NISSEN: I don\'t think we should go here. I want to dissent a little
bit on what\'s been said, and let me see if I can articulate why.

First of all, I think there\'s a danger when looking across two
different trials involving two different drugs. I would just point out
to you there\'s a lot of precedent here. We have drugs, HMG CoA
reductase inhibitors. Everything looked like it was going to go in the
right direction, and it pops up that cerivastatin has a huge problem.
Nobody anticipated that.

DR. TEMPLE: Not an effectiveness problem.

DR. NISSEN: No, not an effectiveness problem, but a safety problem. I\'m
just pointing out that there are examples. There are many examples where
there is heterogeneity here.

DR. TEMPLE: No one would ever argue that you learn about the safety of a
member of a class from the previous members.

DR. NISSEN: I understand.

DR. TEMPLE: Beta blockers have been carcinogenic occasionally and done
other things. We don\'t think that for a minute.

DR. NISSEN: No. I understand.

But just to say that I think we set up a precedent here if we\'re not
careful that we may regret. I guess I want to be careful about that
precedent.

Let me point out something else. If you\'re going to combine the data in
your mind from IDNT and RENAAL, you have to combine all the data. And I
would point out to you that in RENAAL, there was about a 12 percent
excess of cardiovascular death, not significant, compared to placebo.
Isn\'t that right? Wasn\'t it 1.12?

DR. TEMPLE: In RENAAL.

DR. NISSEN: Yes, in RENAAL. And in IDNT, there was a 36 percent excess
in comparison to active control, in this case amlodipine. So, the
cardiovascular deaths went in the wrong direction in both trials. So, if
you\'re going to combine the two trials, you got to combine them on the
plus and on the minus side.

Again, what it does tell me is that the when you combine those two
trials, looking for cardiovascular benefit, you\'re now looking at
3,000, 4,000 patients. You\'re not looking at such a small study. So,
now we\'re sitting here in a post-HOPE era and with all the data we have
and now we\'ve got two trials, both of which failed to show the
cardiovascular events going in the right direction. In some cases like
IDNT, they went in the wrong direction for one of the arms. And now I\'m
troubled by it all.

I don\'t think you can combine it for the efficacy side without looking
at both the pluses and the minuses of combining the two trials, and I
really do think there\'s a lot of risk here in taking two different
drugs in the same class and saying, well, we\'ve got trials with each of
these, we\'re going to use them to support each other because it\'s
going to come up again and again, unless you really want to make the
standard a lot lower. So, that\'s my dissent.

DR. BORER: Susanna?

DR. CUNNINGHAM: I think a yes and a no. I think they could support each
other, but I don\'t think it\'s as good as replication. But I think all
the other points that have been made are good ones. So, it\'s not
exactly a real clear-cut picture.

DR. BORER: Beverly?

DR. LORELL: I think that having looked at these two trials very close
together is almost more troublesome than helpful. I think I agree more
with Steve. Let me see if I can articulate why that is true.

I think the evidence in aggregate from both of those trials and other
smaller studies compellingly argues that there is a biologic real effect
of interfering with the renin-angiotensin system on progression of renal
disease. However, I think there are a couple of problems when you
actually look at these two trials together, and I think we can\'t help
but do that on this panel.

One is that they are remarkably congruent in the modest nature of the
effect on the primary endpoint, and in fact they\'re quite congruent
that for the primary composite endpoint, the p value for both was .02.
So, if anything, that would suggest that the effect is a fairly modest
one and not a robust one.

If one tries to dissect and sort of redesign the trials, going back to
Tom\'s analysis of the hard endpoint of end-stage renal disease, here we
actually have a bit of a problem because in this trial, if one pulls
that out not as the primary endpoint, it looks highly significant. In
fact, if I recall my data notes correctly from a month ago, it was not
significant in the other trial.

DR. TEMPLE: They didn\'t have the same kind of follow-up here.

DR. LORELL: I agree.

DR. TEMPLE: Up to the time of the endpoint, the results were the same.

DR. LORELL: In fact, in pulling it together, we have somewhat discordant
data.

I share Steve\'s concern that we have two data sets with the very
worrisome hint of actually a negative effect on the hard endpoint of
cardiovascular death which was the major cause of all deaths in this
trial.

So, if anything, I think yes, it supports an effect on the biology, but
I think that putting them together actually is somewhat dissuasive for
approval of this for the endpoint.

DR. TEMPLE: Can I just ask? The previous study showed no difference
versus placebo on mortality, and there was a trend or maybe more than a
trend, favoring the calcium channel blocker. So, are you saying that
suggests a negative effect on mortality, or are you suggesting that
everybody ought to be on a calcium channel blocker?

DR. LORELL: No, I didn\'t say that at all. Far be it for me to suggest
that all these patients should be on calcium channel blockers.

DR. TEMPLE: I didn\'t think so.

DR. LORELL: That was not what I said. I agree with Steve\'s point that
there is a worrisome signal regarding an event that is of immense
clinical importance.

DR. THROCKMORTON: But it\'s just worth thinking so we understand. In the
IDNT trial ‑‑ and I can be corrected if I\'m wrong ‑‑ the irbesartan
mortality was, in fact, lower on irbesartan than it was on placebo, 16
percent versus 14.9 percent. You\'re right. Amlodipine had a point
estimate that was lower than irbesartan, but versus placebo, which was
the comparison we had today, in fact it trended in the correct and
better direction. So, it would be a wash if all you were doing was
adding the two of them up.

DR. FLEMING: Just as a quick statistical clarification, Steve and
Beverly, I think you raise very relevant issues about looking at each of
these components, and cardiovascular death certainly is a key component.
Just as a reminder, the 90 versus 79 deaths translates into an absolute
1.5 percent increase or a relative increase of about 14.5 percent, and
for an event that occurs at 10 to 12 percent in the population to be
able to detect that relative risk, i.e., to reliably sort out whether
this is a true 15 percent increase or it\'s purely noise, would take
20,000 to 25,000 people. It is more of a concern seeing it in two trials
of size 1,500 apiece, but even those two together are still one-eighth
of the size that we would need to say anything reliable about whether
that\'s a true increase or it\'s consistent with random variability.

DR. TEMPLE: Tom, let\'s be clear we\'ve got the facts right. We don\'t
think you do see it in the irbesartan trial. What you see is a
comparison with a different drug, but against placebo it was actually
slightly but irrelevantly better.

DR. LINDENFELD: Yes. I think just the placebo group was 16 percent in
IDNT and I think 14.9 in irbesartan and 14.1 in amlodipine.

DR. TEMPLE: So, that\'s not seeing the same thing twice.

DR. LINDENFELD: Overall deaths, total mortality.

DR. FLEMING: I thought what Beverly ‑‑

DR. LORELL: My concern was cardiovascular deaths explicitly.

DR. BORER: Let me ask before we go on to Paul, we want for the record,
Beverly, a vote on 9.1. Do the findings of IDNT support the
effectiveness of losartan for diabetic nephropathy. Forget out the
magnitude of the support which you\'ve already answered in detail. But
can you look at these data in looking for support for RENAAL?

DR. LORELL: I think they provide soft support in aggregate.

DR. BORER: Paul?

DR. ARMSTRONG: I side with JoAnn and I do so in the context of
reassurance about ARB versus placebo in a broader pattern of evidence
than what\'s been provided. So, when I take that into context, I\'m
comforted.

DR. BORER: Do you want to go to the specifics of 9.2 in addition to
having voted yes on 9.1?

DR. ARMSTRONG: Just to reiterate what JoAnn has said all the way down
the line.

DR. KOPP: Yes. I think the findings from IDNT are supportive.

I guess I\'d like to make a point about cardiovascular mortality to
remind ourselves that once somebody starts dialysis, the first-year
mortality is something like 20 to 25 percent and the two-year mortality
is something like 40 percent. So, if this drug is able to postpone
dialysis for even 6 months, it may gain more lives because people don\'t
start dialysis and die from cardiovascular death potentially caused
during that 6 months or 2 years of treatment.

DR. NISSEN: That\'s why I was so disturbed by the fact it didn\'t go in
the right direction. I would have expected that a drug that would delay
renal failure would have an effect on death, and the fact that it
didn\'t was very bothersome to me in both trials.

DR. KOPP: Yes, that\'s a fair point.

I guess one issue would be is the dialysis follow-up sufficient to see
the full benefit, but I take your point.

DR. BORER: Dr. Brem?

DR. BREM: To 9.1, I think they are supportive in several ways. One,
there is a dose dependence to the effect in the IDNT trial which we have
not been able to demonstrate in this trial. Also, the blood pressure was
more comparable in the IDNT trial. There was, in other words, less of a
difference. So, it would support the view that if you gave enough of a
sartan drug, that it would have some beneficial effect on the
progression of diabetic nephropathy.

The other point that I would make is I think that the irbesartan trials
now are more supportive in light of ancillary or perhaps less relevant
endpoints and that is the progression of proteinuria. In this particular
study, there is a clear demonstration that proteinuria is associated
with the progression of renal disease. That was not able to be
demonstrated on the IDNT trial satisfactorily. So, if one uses that
information in context, that\'s further information to me that would
support its beneficial effects.

So, yes, I think the two studies together are complementary. They
aren\'t additive, but they are complementary.

DR. BORER: Having said that, why don\'t we start with you again. I think
we know the vote because you\'ve already given it. Should losartan be
approved for the treatment of nephropathy in patients with type II
diabetes?

DR. KOPP: Yes.

DR. BORER: Do you need more reasoning given everything we\'ve heard, or
can he just vote yes?

DR. THROCKMORTON: No.

DR. BORER: Okay.

Dr. Kopp?

DR. KOPP: Yes.

DR. BORER: Paul?

DR. ARMSTRONG: Yes.

DR. BORER: Beverly?

DR. LORELL: No.

DR. BORER: Susanna?

DR. CUNNINGHAM: Yes.

DR. THROCKMORTON: Jeff, I\'m sorry. If for any reason that you don\'t ‑‑
well, no, that\'s fine. I take it back.

DR. BORER: Steve?

DR. NISSEN: No.

DR. BORER: I vote yes, but I want to expand a little bit. I think that
the drug should be approved for diabetic nephropathy in patients with
type II diabetes. I\'ve already talked about my views of RENAAL, that I
think it\'s a pretty good trial, better than the nominal p value on the
primary endpoint, but not as good as two. I thought IDNT supported it to
some extent, sufficient so that I\'m willing to accept the
effectiveness. But I\'ll say again I believe that there are multiple
safety issues that have to be dealt with in labeling, that the mandated
use of this drug has to be dealt with in labeling, the fact that it
shouldn\'t be mandated.

And I am concerned about cardiovascular death, but I\'m less concerned
than some of my colleagues because we haven\'t looked at this population
before, and I just don\'t know what happens to cardiovascular events in
people who have end-stage or near end-stage renal disease. So, I\'m
really not willing to delay the drug because of my concerns, which are
very real, about the cardiovascular event issue. I won\'t say
cardiovascular death because I agree with Dr. Kopp about the tradeoff
there.

Having said all that and having voted yes, I have to say that if another
ARB comes to this committee tomorrow for the same indication, I may say
no because I may not find the totality of data from all these trials
that we\'ve seen now ‑‑ that\'s two, RENAAL and IDNT ‑‑ together with
whatever is presented for the new molecule sufficient to weigh me in
favor of the new molecule even if the study turns out to be nominally
positive for the new molecule. So, this is not a precedent. This is a
specific issue.

Alan?

DR. HIRSCH: Well, I would vote no, but that\'s in the guise that I
don\'t believe a disapproval, if the committee goes that way, will
deprive a single patient with diabetic nephropathy of access to a
molecule that\'s available. However, if approval is recommended, then
like my colleague to my left, I believe that the safety issue ‑‑ yes,
sir?

DR. TEMPLE: Well, I guess we would hope, as a general matter, that you
not consider such practicalities.

DR. HIRSCH: Okay, I won\'t.

DR. TEMPLE: We want your answer and your answer is no.

DR. HIRSCH: It remains the same.

DR. TEMPLE: But if your answer would be different if somehow they
weren\'t available ‑‑

DR. HIRSCH: No. I hear you. My answer, Bob, is the same in the sense
that I\'ve been all day, including at the last meeting, trying to be
consistent between the two meetings, like Bev, trying to look at the
data from single trials, even the two trials together, and decide, fine,
if this weren\'t available, do I have adequate data at this point to
bring it to approval. I would like not to have to change my vote the
next time an ARB comes. I\'d like to make sure the evidentiary standard
persists.

DR. TEMPLE: But I guess we hope the votes will be as if it wasn\'t
available. Otherwise, it\'s sort of ‑‑

DR. HIRSCH: Well, I answered that. You may have to ask the others who
aren\'t here to revote.

DR. TEMPLE: No. You were the only one who indicated that was influencing
you. It\'s hard not to face reality and know that it doesn\'t really
matter whether we approve it or not. People can use it anyway because
they can read the New England Journal. But we like to try to do it
completely abstractly and on an evidentiary basis and not do that
because, you know, fair is fair.

DR. HIRSCH: Fair is fair.

DR. THROCKMORTON: Was your reason for raising the issue of it being
available your concern with the safety?

DR. HIRSCH: Yes. My hesitation is deep and long and I\'m not sure that
the whole room has to hear a rehash of what you\'ve heard, but it does
get attributed to what I would see if I were merging the two trials.
I\'d still believe there is a safety blip that is of some concern and
efficacy standards that are not quite achieved. So, it\'s that
risk/benefit analysis we always follow here on prima facie evidence.

DR. BORER: Blase?

DR. CARABELLO: I vote yes.

DR. BORER: I think you already gave your reasoning.

JoAnn?

DR. LINDENFELD: I vote yes. Just two quick comments.

Again, as has been said before, I think we need to try to say something
that this doesn\'t imply superiority over ACE inhibitors, just something
in there.

And the other thing in terms of safety is that I think we need to make
it clear that the risk of hyperkalemia is cumulative with this drug over
the course of the drug and probably always needs to be monitored ongoing
over time. That\'s a little bit different I think than in other
situations.

DR. TEMPLE: I do have to say commenting that it\'s not better than ACE
inhibitors or that that hasn\'t been studied would be a very unusual
thing for us to do when there\'s no data showing that ACE inhibitors
work in this setting.

DR. LINDENFELD: That\'s right.

DR. TEMPLE: That\'s tough to support.

DR. LINDENFELD: That is tough, but maybe we can think about that. But it
would be nice to not have this supplant the use of ACE inhibitors I
think or not have this be a reason to do that. Maybe that\'s not
possible, but I share that concern.

DR. TEMPLE: Also, if either of you have specific suggestions or little
phrases that you think will do this, please.

DR. BORER: Off-line we can do that. I think what JoAnn is saying is the
same thing that I am, that there has to be some kind of language that
says we are not saying that this is the be all and the end all. Now, how
to say that, I think we can figure out, make some suggestions, and you
can improve upon them, and something can be done.

DR. TEMPLE: Again, though, for reasons that are not known to us, no one
has bothered to study ACE inhibitors in this setting. I don\'t know why
that is. Maybe because they\'re all going to go off patent soon or
whatever the reason is, but nobody has studied it.

DR. BORER: Right. No, I\'m not suggesting that we can say anything about
the relation to ACE inhibitors. What I\'m saying is we must say that we
don\'t know what the story is with cardiovascular morbidity and
mortality here, and therefore we can\'t say that this is necessarily the
way that one must go in the individual patient.

DR. TEMPLE: We would certainly give the results that show no benefit on
those endpoints. That would be part of the trial.

DR. BORER: Okay, well, I don\'t want to take up everybody\'s time, but
we can write down some suggestions.

Tom?

DR. LORELL: Mr. Chair, are we really giving two votes here? One is a
yes/no vote if we get to have a conditional labeling, and one is a
yes/no vote if we don\'t have any influence on labeling?

DR. BORER: No. I think we\'re saying we think that the drug should be
approved or it shouldn\'t be approved and then we\'re giving caveats
about how we think that ought to happen. We\'re only an advisory
committee and the law is sitting across the table from us.

DR. TEMPLE: No, but suggestions on what you\'re thinking of are welcome.
I\'m just trying to signal that saying something like we don\'t know
whether you\'re better than ACE inhibitors, when they don\'t even have
that claim, would be very difficult to support against ‑‑ well, it would
be difficult to convince me to do that, much less the company.

DR. BORER: I was going to make the suggestion off-line, but sometimes we
have meetings or sections of meetings about issues rather than about
drugs. I think this issue in so many areas may have risen to the point
of needing some kind of open discussion at some other time.

Tom, I think you already voted on approvability, but do you want to
restate it?

DR. FLEMING: Sure. Yes, I vote approval. And maybe I could just add one
additional clarification and that is I wanted to reinforce the wisdom
that I have heard today that one has to be extremely cautious when one
is analyzing data in putting particular focus on primary endpoints. I
want to strongly endorse that as extremely important. From a statistical
perspective, when we\'re using a trial as a confirmatory trial, if one
wants to assess strength of evidence in a confirmatory fashion, it is
extremely important that we prespecified our primary hypothesis with
primary analysis methods so that we can really interpret strength of
evidence in that context.

Having said that, as strongly as I think statistical procedures are
extremely useful in making these assessments, as to whether or not
studies adequately establish favorable benefit to risk, any statistical
approach must be viewed with the broadest assessment, bringing in
clinical judgment.

In my own sense in this particular trial, if one views, as I do in this
particular case, that the primary endpoint that was set up here has as
an important component, at least a component that I view to be a
surrogate, which in particular in this setting isn\'t intrinsically
necessary to rely on because the clinical endpoints are occurring so
rapidly, it\'s my own assessment that the evidence that I would have
looked for in this trial ‑‑ even though the primary endpoint had the
triple component, I would have relied on the double component anyway.

Essentially, at least in my own perspective, what one needs to avoid is
a situation where you don\'t see what you had hoped to see in the
primary endpoint and you start looking around for other ways of getting
a more favorable conclusion. Clearly that\'s hazardous.

What I\'m trying to sort through here, though, is in my own assessment,
at least speaking for myself, that\'s not the issue. As we discussed in
January, some of us had argued very strongly that in a setting such as
this, the primary endpoint ought to be based on those elements that are
truly the clinical elements, especially when they can be addressed in a
timely way and especially in a setting such as this where it\'s somewhat
problematic how to interpret the triple endpoint because there wasn\'t a
complete follow-up. It creates a situation, at least for me in my own
judgment, that the primary endpoint would not have been persuasive even
if it had been meeting the standards for strength of evidence of two
positive trials.

So, I guess what I\'m trying to articulate here is just to reinforce
that there is great wisdom in stating that one needs to be extremely
cautious about the strength of evidence and the focus that you give to
the primary endpoint, but there clearly needs to be judgment and you
clearly need to look at the totality of results. So, I would like to
make it clear that, at least in my own case where my view of what is
clinically relevant leads me, independent of what these data would have
shown, to focus on the dual endpoint shouldn\'t be viewed as an
endorsement of readily deviating from the primary endpoint.

DR. BORER: What we\'ve said in summary is that the majority of the
committee favors approval of this drug for the requested indication. I
think it\'s important to remember that there have been many important
concerns raised and that, though the vote was clearly and decisively in
favor of approval, the magnitude of the difference between those who
voted yes and those who voted no may be relatively small and, therefore,
that there\'s no binding precedent based on this vote for how this
committee would view other drugs if they come with similar credentials
for similar indications.

Finally, I think I can say for all of us that we voted the way we did
without the expectation that another trial is going to be performed
because the data didn\'t satisfy everybody. We voted based on what we
have.

Bob?

DR. TEMPLE: I just wanted to thank you. This was another difficult
session, just like the one in January was. You grappled with it.

I have to tell you it\'s hard not to allow people to draw inferences
from the fact that we\'re making use of data from another drug of the
same class, and they will. You are, of course, free to be as
situation-appropriate as you want.

But this was very helpful to us and it was a good discussion. So, we
thank you.

DR. BORER: Thank you.

If there are no other questions from the FDA, I\'ll call the meeting
adjourned.

(Whereupon, at 4:47 p.m., the committee was adjourned.)