ATDEPARTMENT OF HEALTH AND HUMAN SERVICES

> FOOD AND DRUG ADMINISTRATION
>
> CENTER FOR DRUG EVALUATION AND RESEARCH
>
> **ANTIVIRAL DRUGS ADVISORY COMMITTEE (AVAC)**
>
> Wednesday, August 7, 2002
>
> 8:00 a.m.
>
> Holiday Inn Bethesda
>
> Versailles Ballroom
>
> 8120 Wisconsin Avenue
>
> Bethesda, Maryland
>
> PARTICIPANTS
>
> Roy M. Gulick, M.D., M.P.H. Chair
>
> Tara P. Turner, Pharm.D., Executive Secretary
>
> MEMBERS
>
> Victor G. DeGruttola, Sc.D.
>
> Janet A. Englund, M.D.
>
> Courtney V. Fletcher, Pharm.D.
>
> Princy N. Kumar, M.D.
>
> Wm. Christopher Mathews, M.D.
>
> Jonathan M. Schapiro, M.D.
>
> Sharilyn K. Stanley, M.D.
>
> Brian Wong, M.D.
>
> Lauren V. Wood, M.D.
>
> CONSULTANT (VOTING), PENDING NEW AVAC MEMBER
>
> Kenneth E. Sherman, M.D., Ph.D.
>
> CONSULTANT (VOTING)
>
> Maria H. Sjogren, M.D.
>
> INDUSTRY REPRESENTATIVE (NON-VOTING)
>
> Eugene Sun, M.D.
>
> PATIENT REPRESENTATIVE (NON-VOTING)
>
> Timothy Block, Ph.D.
>
> GUESTS (NON-VOTING)
>
> Anna S. F. Lok, M.D.
>
> Jay H. Hoofnagle, M.D.
>
> Zachary D. Goodman, M.D., Ph.D.
>
> GUEST SPEAKER (NON-VOTING)
>
> Nathaniel A. Brown, M.D.
>
> FDA
>
> Mark Goldberger, M.D., M.P.H.
>
> Debra Birnkrant, M.D.
>
> Katherine A. Laessig, M.D.
>
> Jeffrey Murray, M.D., M.P.H
>
> Greg Soon, Ph.D.
>
> [C O N T E N T S]{.underline}
>
> Call to Order:
>
> Roy M. Gulick, M.D., M.P.H. 4
>
> Conflict of Interest Statement:
>
> Tara P. Turner, Pharm. D. 5
>
> Opening Remarks:
>
> Jeffrey Murray, M.D., M.P.H. 8
>
> Natural History and Clinical Virology
>
> of Hepatitis B:
>
> Jay H. Hoofnagle, M.D. 12
>
> Treatment of Chronic Hepatitis B:
>
> Anna S.F. Lok, M.D. 63
>
> Pharmaceutic Development Issues for Hepatitis B:
>
> Nathaniel A. Brown, M.D. 121
>
> Surrogate Endpoints for Hepatitis B Trials:
>
> Greg Soon, Ph.D. 170
>
> Open Public Hearing
>
> Mr. Lee Crooks 219
>
> Dr. Michael Wulfsohn 225
>
> Charge to the Committee 231
>
> Committee Discussion 237
>
> [P]{.underline} [R]{.underline} [O]{.underline} [C]{.underline}
> [E]{.underline} [E]{.underline} [D]{.underline} [I]{.underline}
> [N]{.underline} [G]{.underline} [S]{.underline}
>
> **Call to Order**
>
> DR. GULICK: Good morning. I am Trip Gulick from Cornell. I would like
> to call to order this meeting of the Antiviral Advisory Committee.
>
> We will start with the introduction of the committee members. Dr. Sun,
> can you lead us off? Please state your name and your affiliation.
>
> DR. SUN: Eugene Sun, Abbott Laboratories.
>
> DR. LOK: Anna Lok, University of Michigan.
>
> DR. HOOFNAGLE: Jay Hoofnagle, NIDDK, NIH.
>
> DR. GOODMAN: Zachary Goodman, Armed Forces Institute of Pathology.
>
> DR. BLOCK: Tim Block, Jefferson Medical College and the Hepatitis B
> Foundation of America.
>
> DR. KUMAR: Princy Kumar, Georgetown University.
>
> DR. SCHAPIRO: Jonathan Schapiro, Stanford.
>
> DR. WOOD: Lauren Wood, NCI, NIH.
>
> DR. ENGLUND: Janet Englund, University of Washington, Seattle.
>
> DR. STANLEY: Sharilyn Stanley, Texas Department of Health.
>
> DR. TURNER: Tara Turner, Executive Secretary for the committee.
>
> DR. FLETCHER: Courtney Fletcher, University of Colorado Health
> Sciences Center.
>
> DR. DeGRUTTOLA: Victor DeGruttola, Harvard School of Public Health.
>
> DR. SHERMAN: Ken Sherman, University of Cincinnati.
>
> DR. MATHEWS: Chris Mathews, U.C., San Diego.
>
> DR. WONG: Brian Wong, V.A. Hospital in Westhaven, Connecticut and Yale
> University.
>
> DR. SOON: Greg Soon, FDA.
>
> DR. LAESSIG: Katie Laessig, FDA.
>
> DR. MURRAY: Jeff Murray, FDA.
>
> DR. BIRNKRANT: Debra Birnkrant, FDA.
>
> DR. GOLDBERGER: Mark Goldberger, FDA.
>
> DR. GULICK: Thank you.
>
> Tara Turner will now read the conflict of interest statement.
>
> **Conflict of Interest Statement**
>
> DR. TURNER: The following announcement addresses the issue of conflict
> of interest with respect to this meeting and is made a part of the
> record to preclude even the appearance of such at this meeting.
>
> The Food and Drug Administration has approved general-matters waivers
> for the following special government employees which permits them to
> participate in today\'s discussions; Drs. Victor DeGruttola, Janet
> Englund, Courtney Fletcher, Roy Gulick, Princy Kumar, Wm. Christopher
> Mathews, Jonathan Schapiro, Kenneth Sherman, Maria Sjogren, Brian
> Wong, Lauren Wood.
>
> A copy of the waiver statements may be obtained by submitting a
> written request to the agency\'s Freedom of Information Office, Room
> 12A30 of the Parklawn Building. In addition, Sharilyn Stanley, M.D.,
> does not have any current financial interests in pharmaceutical
> companies. Therefore, she does not require a waiver to participate in
> today\'s discussions.
>
> The topics of today\'s meeting are issues of broad applicability.
> Unlike issues before a committee in which a particular product is
> discussed, issues of broader applicability involve many industrial
> sponsors and academic institutions. The committee members and invited
> guests have been screened for their financial interests as they may
> apply to the general topics at hand.
>
> Because general topics impact so many institutions, it is not prudent
> to recite all potential conflicts of interest as they apply to each
> participant. FDA acknowledges that there may be potential conflicts of
> interest but, because of the general nature of the discussion before
> the committee, these potential conflicts are mitigated.
>
> We would also like to note that Dr. Eugene Sun is participating in
> today\'s meeting as a non-voting industry representative. In addition,
> Dr. Nathaniel Brown is participating in today\'s meeting on behalf of
> an informal industry collaborative group. As such, they have not been
> screened for conflicts of interest.
>
> In the event that the discussions involve any other products or firms
> not already on the agenda for which FDA participants have a financial
> interest, the participants\' 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 product they may wish to comment upon.
>
> Thank you.
>
> DR. GULICK: Thanks.
>
> We will turn now to Dr. Jeff Murray from the division for opening
> remarks.
>
> **Opening Remarks**
>
> DR. MURRAY: Good morning.
>
> \[Slide.\]
>
> I would like to welcome everybody, the committee, guests and everyone
> to this very important meeting on clinical-trial-design issues for
> drugs to treat chronic hepatitis B.
>
> \[Slide.\]
>
> So why are we having this meeting now? As Dr. Birnkrant mentioned
> yesterday, the number of drug products undergoing development for
> chronic hepatitis B has really increased. It has become a large
> proportion of our work now in the division.
>
> Additional drug availability such as now adefovir and lamivudine may
> change the types of clinical trials that are now feasible. I think we
> are entering into a new period maybe of active controls, combination
> therapies and, perhaps, new trial designs.
>
> It is always good to have a discussion like this after consideration
> of a new drug product. It is a good exercise for the committee and
> guests to go through to see the positive aspects and pitfalls of a
> drug-development program. I think it is really time that we reflect on
> the lessons learned from the first two drug-development programs in
> moving ahead. I think that we will have better drug development in the
> future for having some reflection now.
>
> \[Slide.\]
>
> So the meeting focus is primarily on antiviral drugs. We will mention
> interferon and, perhaps, other immunomodulators but, basically, we are
> focusing trial-design issues for drugs.
>
> The focus is also primarily on phase III studies and, perhaps,
> postmarketing studies. Although some phase II drug development, phase
> I drug development, can be addressed, I think the primary focus is
> phase III.
>
> We want to address both compensated and decompensated liver disease
> and we hope that all this will aid in the planning of future clinical
> trials. We have to realize that there are ongoing clinical trials now
> and so any recommendations made today, however strong, we have to
> realize that these may not be able to be incorporated into ongoing
> trials.
>
> \[Slide.\]
>
> So the key issues, and these are how the questions will be divided in
> groups for the committee to address, are what are the essential
> patient populations for a marketing application, selection of control
> arms, choice of primary endpoint, also secondary endpoints and,
> really, a very crucial topic is long-term follow-up data, the type of
> data that might allow us better prescribing information, when to stop
> and start treatment.
>
> \[Slide.\]
>
> Moving on to the next slide is the agenda for today. Before the break,
> we will have two talks that will provide background that will help the
> committee focus on the questions at hand. Dr. Jay Hoofnagle from NIH
> will start at 8:30 with Natural History and Clinical Virology of
> Hepatitis B followed by an Overview of the Treatment Outcomes in
> Trials for Chronic Hepatitis B by Dr. Anna Lok from the University of
> Michigan.
>
> We will have a short break. Following the break, a couple more
> presentations. An industry perspective by Dr. Brown from Idenix
> Pharmaceuticals. I might say that it is impossible for one industry to
> represent or speak for all, but portion of his talk does involve a
> collaboration where several pharmaceutical sponsors had filled out a
> survey indicating what were important issues that the committee should
> address today and what are the important issues facing current drug
> development.
>
> Then two talks following that. I have a couple of brief comments and
> then Dr. Soon, a statistician from our division, has done quite a few
> analyses correlating measurements such as ALT and HBV DNA and
> histologic outcome. Following lunch, there will be an open public
> hearing. Then we will address the questions. This will be done in a
> slightly different format. We wanted to have more widespread
> participation so, after each block of questions, and those are dealing
> with the key issues, I think we are going to allow five to ten minutes
> of open-mike time at Dr. Gulick, our chair\'s, discretion.
>
> During that time, anybody can pose a comment, a question or a
> clarification to the committee if they felt that an issue has not been
> addressed that they were interested in.
>
> So, with that, I will turn it over, actually, to Dr. Hoofnagle for our
> first presentation.
>
> **Natural History and Clinical Virology of**
>
> **Hepatitis B**
>
> DR. HOOFNAGLE: Thank you, Dr. Murray and all, for inviting me to come
> to talk.
>
> \[Slide.\]
>
> When I first entered the field of treatment of hepatitis B it was very
> much different. I had to go around the country to drug companies to
> convince them to try to let us use drugs to treat hepatitis B. I am
> glad now they are coming to the NIH in Bethesda with interest.
>
> I was asked to give an overview of the virology and natural history of
> the disease.
>
> \[Slide.\]
>
> So, for many of you, this is very simple but, to begin with the
> hepatitis-B virus, which is a quite unique virus; it is small
> double-stranded DNA virus that belongs to the family called
> Hepadenoviridae. It is the only human form of this in this family.
> There are some rodent and bird viruses that are very similar.
>
> Infection with hepatitis B is restricted to humans and higher apes, a
> very endangered species, so we don\'t have nice, easy animal models of
> the disease. But, the human provides a lot of source for study.
>
> The virus is found in the blood in very high levels, extremely high
> levels, and quite variable from as low as barely detectable to as high
> as 10^10^ to 10^11^ virions per ml. Now, to compare this to, like,
> hepatitis C, there, most people circulate viruses in a very tight,
> narrow area between 10^5^ and 10^7^. Here, there is a broad range and
> the different ranges of the viral levels are important clinically.
>
> The virus can cause both an acute and a chronic hepatitis but, unlike
> in hepatitis C, chronic hepatitis is somewhat the uncommon outcome of
> this disease, at least in adulthood. Probably only 5 to 10 percent of
> patients with acute hepatitis B virus infection after the age of 20
> will develop chronic infection.
>
> It is spread by parenteral, sexual and maternal-infant routes. In this
> country, the major route of spread is sexual spread. We do see a lot
> of imported hepatitis B, immigrants from areas of the world where this
> disease is common.
>
> It has a marked geographical variation and incidence. This disease,
> for instance, was almost a university disease in China and Southeast
> Asia so that, by the age of 20, 80 percent of people had been infected
> with hepatitis-B virus unlike in the United States where this is
> really an uncommon disease.
>
> Population-based surveys suggested about 5 to 10 percent of Americans,
> at most, will get infected sometime during their life.
>
> \[Slide.\]
>
> Here is a cartoon of the virus-like particles that you see in serum.
> The virus, itself, is this particle called the Dane particle, named
> for Dr. Dane. It is a double-shelled particle with a surface-antigen
> environment and a core-antigen nucleocapsid core.
>
> Inside of the core is a double-stranded circular molecule of DNA.
> Interestingly, the virus in the liver produces a lot of other
> particles. Spherical particles and tubular particles actually
> outnumber the Dane particle by 10 to 10,000 to 1. These are incomplete
> virus particles made up only of surface antigen and, of course, this
> is the basis for the hepatitis-B vaccine to immunize with incomplete
> noninfectious particles.
>
> Also in serum is another antigen, the hepatitis-B e-antigen. It is a
> soluble antigen. It doesn\'t have structure. You can\'t see it on the
> electron microscope. It is about 19 kilodaltons in size.
> Interestingly, it is a byproduct of the production of core antigen.
>
> \[Slide.\]
>
> This is the typical type of display of the hepatitis-B virus DNA.
> These here show you the double-stranded circular molecule of DNA.
> Actually, it is neither circular nor double-stranded.
>
> One of the strands is incomplete here, so it is partially
> double-stranded. Furthermore, both strands are actually linear
> molecules held together by overlapping bases. This slide is incorrect.
> There is actually a nick right here, a nick right there, so that the
> ends of the DNA are not covalently closed as it circulates in serum.
>
> Once it gets in the liver, this is repaired and it becomes a
> double-stranded molecule that sits in the nucleus, the so-called
> circular DNA, and that makes RNA of the hepatitis-B virus which is
> reverse-transcribed in the replication of the virus back into DNA. So
> it has a very peculiar replicative cycle.
>
> It is very important for the natural history and the treatment of this
> disease that the molecule that we are trying to get rid of is the most
> difficult to get rid of and that is this double-stranded circular DNA
> that sits in the nucleus of hepatocytes and spits out RNA.
>
> So, inhibiting the replication of virus, it is very hard to get to
> that stable molecule of DNA.
>
> The DNA has four open reading frames as shown in these color arrows.
> First of all, the surface antigen, the enveloped gene. It is a complex
> antigen and it has three start sites so it has three different sizes,
> large, middle and small hepatitis-B surface antigen.
>
> Here is the core-antigen gene. It also has a strange structure. It has
> a precore region and two start sites. You can synthesize\--if you
> start from here, you synthesize core antigen that is incorporated and
> is the nucleocapsid of the virus. If you begin at the precore region,
> you synthesize a protein that is post-translationally cleaved into a
> soluble molecule, e-antigen.
>
> So there is no separate open-reading frame for e-antigen. It is
> synthesized off the core gene and it shares sequence with the core
> gene. It is probably one of the secrets to the immunology of this
> virus but I haven\'t figured out what that secret is.
>
> Then the large brown arrow is the polymerase gene. It is a
> multifaceted polymerase that can synthesize both the negative and
> positive strands off of its own DNA or off of its own RNA. You see how
> it overlaps. These genes are overlapping. It is amazing that there is
> no nucleotide base in the hepatitis-B virus that isn\'t used, so it is
> not based like the human genome on entrons and exons.
>
> Furthermore, most bases are used twice in that they are used either to
> produce surface or polymerase, or polymerase and core and so forth.
> There are also a lot of enhancing and promoter regions so that this is
> one of the most compact DNAs of any virus.
>
> This is meaningful in several ways. For one thing, the virus can\'t
> mutate very much because, if it mutates, it has got a lot of
> compensation to do. For instance, if you mutate a base here, you can
> affect both the surface and the polymerase gene. This is important
> also in talking about mutants and antiviral resistance.
>
> This region here is called Region X. Its function is somewhat unknown.
> It is a transactivating factor that is somehow important in the
> replication of the virus.
>
> \[Slide.\]
>
> Here are the RNAs of the virus. There are multiple RNAs that are of
> different sizes, some that just synthesize surface antigen and the
> pregenome from which DNA is made by reverse transcriptase. This is
> so-called pregenome, the purple one. This shows you the nick here on
> the incomplete strand.
>
> \[Slide.\]
>
> Circular, partially double-stranded, poor open-reading frames.
> Replicates largely in the liver. It may replicate in stem cells in the
> pancreas and in the spleen and bone marrow, but not in very high
> levels. Furthermore, I don\'t think it is a privileged site. If you
> inhibit hepatitis-B virus one place, you are probably inhibiting it
> elsewhere. It replicates through an RNA intermediate and reverse
> transcription.
>
> \[Slide.\]
>
> So the infectious cycle of hepatitis-B infecting the liver with a very
> rapid production of virus, 10^11^ to 10^13^ virions per day in someone
> with a very productive infection, virus half-life of one to two days.
>
> \[Slide.\]
>
> So let\'s talk about mutants of the hepatitis-B virus. Variations in
> nucleotide sequence in one of the hepatitis-B virus genes can result
> in a change, either in the virological nature or, in some cases, the
> clinical features of the disease. Various genes that have been found
> mutations in each. The famous mutations of the surface-antigen gene
> are vaccine-escaped variants where the virus is not neutralized by
> antibody to\--the typical antibody to hepatitis-B surface antigen.
>
> The core gene has important mutations which can affect disease
> severity or the serological and clinical manifestations. An important
> mutation in the precore region makes a virus that cannot produce
> e-antigen, for instance. Finally, the polymerase gene which is
> important to this audience because it can affect replicative
> efficiency of the virus and resistance to antiviral agents.
>
> \[Slide.\]
>
> So the core region mutants. An important one is in the precore region.
> A mutation can occur that results in the inability to produce
> e-antigen. What happens is there is a G to A change at nucleotide
> 1896.
>
> \[Slide.\]
>
> Which creates a stop codon in the precore region. So it blocks the
> synthesis of e-antigen. This nucleotide, again because of the compact
> nature of the hepatitis-B virus, doesn\'t affect just e-antigen. It
> also affects replication of the virus because this is in the highly
> structured stem loop called epsilon encapsidation signal region of the
> RNA. So it is a part of the RNA structure that is responsible for
> replication.
>
> If this mutation disrupts the stem loop, the virus won\'t replicate.
> For this reason, this nucleotide which is opposite this one in the
> stem loop, you have to have a T for the stem loop to be stable. The
> importance of that is that this mutation, this e-negative mutation of
> hepatitis-B virus occurs largely in three of the four major genotypes
> of hepatitis B.
>
> Genotypes B, C and D have a T at this region whereas genotype A does
> not. Therefore, patients with genotype A rarely develop
> e-negative-variant disease.
>
> \[Slide.\]
>
> Enough of the molecular biology. We will come back to that a little
> bit in talking about the natural history of hepatitis B. This virus
> infection has multiple outcomes and these percentages are based on
> studies long in the past of acute hepatitis B which showed that the
> majority of people infected with the virus\--this is adults\--do not
> have clinical disease. They have an asymptomatic subclinical
> infection, clear virus and make antibody, and they are protected for
> life.
>
> This is 65 percent of people infected with the virus, so that when you
> test people for antibody, you find people in the population that have
> antibody to hepatitis B but they deny a previous history of hepatitis
> B.
>
> They have been infected. They have been lucky and have had an
> asymptomatic subclinical infection. About a third of patients develop
> clinically apparent disease with jaundice and symptoms. They may not
> be diagnosed correctly but they had a period of disease. This can be
> severe and lead to fulminant hepatitis, somewhat rarely, and it
> usually resolves.
>
> But, in a proportion of cases, and, as I said, in adults it is about 5
> percent chronic infection ensues. This 5 percent applies to adults. It
> doesn\'t apply for children. Children are more likely to develop
> chronic hepatitis B. In fact, infection during the newborn period
> results in chronic hepatitis B in 80 to 90 percent of infected
> children.
>
> So part of the natural history is that if it is spread by
> maternal-infant spread, if it is spread in childhood, it is more
> likely to become chronic and the disease perpetuates in it population.
>
> So what happens with chronic hepatitis B? Does it invariably lead to
> cirrhosis? The answer is no. Like most chronic liver diseases, only a
> proportion of patients with these diseases develop cirrhosis. This is
> a guesstimate, that about 30 percent of people with chronic hepatitis
> B virus infection develop cirrhosis.
>
> Of course, if you take a population of patients that come to see me in
> the liver clinic, it will be higher than 60 percent because these
> people are self-referred, or they are selected. There is this
> selection bias. But if you take the whole population of people with
> hepatitis-B infection, if you went around and screened everybody,
> there are a lot of people who have a somewhat benign outcome that
> develop what is called the inactive carrier state and are left with
> hepatitis-B surface antigen but very low levels of viral replication
> and no accompanying liver disease.
>
> Liver cancer can result from chronic hepatitis B. It occurs largely in
> people with cirrhosis but sometimes not. Sometimes, it appears to
> occur in people who are so-called healthy carriers, inactive carriers.
>
> \[Slide.\]
>
> Let me go through some of the serology of what I have just shown you.
> This is typical resolving acute hepatitis B if you happen to have
> blood samples and everything from the very point of exposure on.
> Within a few weeks of exposure, HBV DNA is detectable in the serum and
> it rises to fairly high levels. These are in millions of copies per
> ml, high-level virus infection.
>
> Once it reaches about that level, you have onset of symptoms and ALT
> elevation. During this period, also the patient is positive for
> surface antigen and the e-antigen, the e-antigen reflecting high
> levels of viral replication.
>
> With the clinical disease, the virus is cleared and e-antigen goes
> away. It is one of the first things to go away, then HBV DNA, then
> surface antigen. The symptoms resolve and the ALT falls to normal and
> patients with acute resolving hepatitis B appear to have recovered
> from this disease.
>
> That is not entirely true. This is a DNA virus and, as a virologist
> will tell you, DNA viruses often stay forever in the body and it is
> probably true of hepatitis B. A person with resolved hepatitis B is
> likely to harbor small levels of the hepatitis-B virus in the liver.
> It is not harmful to them at all.
>
> How do we know that? We know that because if you take a liver from a
> person who has recovered from hepatitis B who has the markers of
> recovery, antibody to surface antigen and antibody to core, and you
> transplant that liver into a naive person at the time of liver
> transplantation, that person will develop hepatitis B.
>
> It is kind of the experiment in nature that shows you that the
> hepatitis-B virus is harbored in the liver and people who recover,
> recover probably for life; maybe not 100 percent but for many.
>
> If you do a liver biopsy in these patients, you can often find small
> levels of HBV DNA in the liver. But you don\'t find it in the blood,
> usually.
>
> \[Slide.\]
>
> Here is what happens to a person who doesn\'t resolve the disease but
> develops chronic hepatitis B. Again, HBV DNA appears in the serum and
> goes up. The patient develops e- and surface antigen and, usually, if
> you are testing, at the time, will have ALT elevations but rarely
> jaundice or symptoms so they have a somewhat mild subclinical
> hepatitis B.
>
> The problem is they don\'t clear virus. They remain surface-positive,
> e-positive and DNA-positive. Why do people develop chronic hepatitis B
> and not recover? The answer to that is we don\'t know for sure. It is
> probably immunological, usually a poor T-cell response to core antigen
> and surface antigen in people who develop chronic infection.
>
> So high levels of HBV DNA and usually ALT elevations persist in these
> people. They may be very low. In fact, in children who develop this,
> the ALT usually is normal or near normal when they develop chronic
> hepatitis B despite high levels of virus and e-antigen. This has been
> called the immune-tolerance state. I don\'t like that term but that is
> what it has been called. So children with chronic hepatitis B usually
> have minimal ALT elevations but high levels of virus.
>
> What happens to them in the end is the question. What you generally
> see is that once they reach adulthood, the disease starts to turn on.
> Their enzymes go up and they start developing the complications of
> hepatitis B.
>
> \[Slide.\]
>
> Here is what we call the transition to the inactive-carrier state. A
> patient with chronic hepatitis B, high levels of DNA, ALT elevations,
> here out, let\'s say, three or four years after onset of infection,
> has a flare of disease spontaneously and clears DNA, clears e-antigen
> but doesn\'t clear surface antigen.
>
> That remains. Develops anti-e. Generally the enzymes return to normal.
> This is the generation of the so-called inactive-carrier states. It
> can occur spontaneously. In fact, in following patients with chronic
> hepatitis B in clinical studies, this occurs in about 5 to 10 percent
> of patients a year.
>
> The importance of this is that this is what we accomplish with
> antiviral therapy. We get chronic hepatitis B to resolve but it
> doesn\'t go away completely. You usually don\'t clear surface antigen.
> You are usually left with surface antigen and you are left with what,
> for lack of a better term, we call the inactive-carrier state. In this
> state, the liver disease is generally not progressive\--generally.
>
> So that is what we accomplish sometimes with antiviral therapy but it
> is important to remember this occurs spontaneously. As I said, in 5 to
> 10 percent of patients that we follow each year, they do it on their
> own. This is what plagues studies of hepatitis B, spontaneous
> improvement. Hepatitis C, we never see spontaneous improvements. It is
> an easier disease to study and, as you know, the FDA doesn\'t require
> placebo controls for hepatitis C. But, for hepatitis B, with this type
> of thing, maybe it is still needed. I don\'t know.
>
> The other problem is you can\'t predict it, I don\'t think. You can
> predict it once this type of thing occurs, once a flare occurs and the
> level of virus drops. You can predict it a little bit, not completely.
>
> This is the slide I would have ended with about ten years ago but the
> disease is not that simple.
>
> \[Slide.\]
>
> That is what I refer to as the e-mutant disease, patients who develop
> a mutation in the hepatitis-B virus DNA that prevents the virus from
> making e-antigen. So what happens there?
>
> Here is what happens. This is a patient, basically, that we were
> following, Asian-born patient, who had e-antigen and active disease.
> We are getting ready to treat the patient and he cleared DNA, or went
> down fairly low, and he lost e-antigen. We thought he was going into
> the inactive-carrier state.
>
> But, no. His enzymes went up again. His HBV DNA has been low-level
> positive, intermittently positive. Now, again, I ought to stress here
> that what we are measuring in DNA here is fairly high levels. This is
> using hybridization-based assays so that this goes down to negative
> for DNA, but that level is about 100,000 copies per ml. That is about
> as low as you can go using typical hybridization assays.
>
> So, when it is negative by that assay, it may still be positive if you
> test it by polymerase chain reaction, and, indeed it is. So this is
> evolution to the e-negative mutant disease and this is no better than
> the e-positive disease. In fact, it may be worse.
>
> These people tend to have flares of disease, intermittent worsenings
> and exacerbations. It makes it very difficult to treat because, just
> about the time you decide, well, this patient really needs to be
> treated, they start to get better on their own. So, an up-and-down
> course. It makes it difficult to study particularly if you want a
> stable level before you enroll the patient, like most of these trials
> try to do.
>
> These patients will be knocked out if you use stringent enrollment
> criteria of a stable lever of HBV DNA.
>
> \[Slide.\]
>
> These are the three clinical forms that are important, general forms,
> e-positive disease, e-negative chronic hepatitis B and
> inactive-carrier state. The disease is associated with raised ALT and
> high levels of HBV DNA in serum.
>
> \[Slide.\]
>
> These are the average levels of virus that you see in patients with
> e-positive and e-negative disease, a little bit lower in e-negative
> disease but it is a moving target in these patients whereas the
> e-positive patient generally maintains a fairly stable level of HBV
> DNA.
>
> Inactive-carrier; we say, they are DNA-negative, but they are not,
> really. They have low levels. One of the things that we have trying to
> work out recently is what level of HBV DNA\--what is the level above
> which you see clinical disease, you see liver disease. This is a
> guesstimate, about 10^4^, 10^5^. Below that, the disease is usually
> inactive.
>
> \[Slide.\]
>
> Why don\'t we know that? We don\'t know that because there haven\'t
> been good assays for detection of HBV DNA. It has been corrected in
> the last couple of years with the development of quantitative PCR
> assays that are commercially available and appear, to my mind, to be
> quite accurate and reliable. Using these assays that measure HBV DNA
> down to around 100 to 500 copies per ml, you find that what we call
> the healthy carrier usually maintains somewhat low levels of virus,
> but the virus is there.
>
> Why does it stay at that low level and not go up? That hasn\'t been
> resolved. So patients with active disease usually have virus high
> enough that can be detected by other assays. This slide is a little
> bit dated so some of these assays may be a little more sensitive now.
> But the conventional hybridization assays just measure down to 10^5^
> to 10^6^ virions per ml which is plenty sensitive enough for the
> average e-positive patient with chronic hepatitis B.
>
> It is a bit troublesome in the e-negative group because they go up and
> down below that level and it, of course, will not detect patients who
> are so-called healthy carriers who are usually negative.
>
> \[Slide.\]
>
> I mentioned genotypes of hepatitis B virus. These are somewhat
> important. We used to subtype virus. Now the virus can be genotyped.
> These are seven genotypes that have been described. The first four are
> the most common in this country. In fact, in the United States and
> Northern Europe, the major genotype is Genotype A.
>
> This is the genotype that has difficulty evolving into the precore
> mutant. The important thing here is that, in the studies in the 1980s
> in the United States, when we were dealing with largely Western
> patients, non-Asian patients, in this country who were being treated
> for hepatitis B or being studied, most of them, 90 percent of them,
> had Genotype A. That is what we found.
>
> In our studies of interferon from the 1980s, 90 percent of our
> patients had Genotype A and the rest had Genotype D which is seen in
> Southern Europe. It is also seen in drug abusers in the country,
> Genotype D-ay.
>
> Genotypes B and C are the genotypes of Asia, China and Southeast Asia
> and Viet Nam. One is an adw so it wasn\'t separable from Genotype A by
> serotyping. The other is adr which was.
>
> So, now, when we see patients, I would say 50 percent of the new
> patients I see are Asian in background, Asian or African in
> background. We are seeing a lot more genotypes B and C.
>
> \[Slide.\]
>
> Changing to what we think about the disease. I was going to mention
> something about the epidemiology of the disease to show you that acute
> hepatitis B, unfortunately, is still with us despite the fact that we
> have a vaccine. It accounts for about 34 percent of acute hepatitis B
> that is seen. It has declined in incidence but it is still here with
> us, seen in injection-drug users, men who have sex with men. The major
> source is heterosexual activity.
>
> So the United States has a way to go before we control acute hepatitis
> B.
>
> \[Slide.\]
>
> Next slide after that.
>
> \[Slide.\]
>
> Here is chronic liver disease in the United States. What proportion is
> due to hepatitis B? Hepatitis B is not a very big piece of the pie. It
> represents about 4 to 5 percent of the chronic liver disease that is
> newly diagnosed in the United States. This is a multicenter study
> conducted by the CDC. Hepatitis C is the big one here.
>
> \[Slide.\]
>
> What are the complications of hepatitis B? The main ones are cirrhosis
> and end-stage liver disease and, in that context, hepatocellular
> carcinoma. There are a few extrahepatic manifestations, glomerular
> nephritis and polyarteritis nodosa which are somewhat uncommon.
>
> \[Slide.\]
>
> So how do we look at hepatitis B? What are the features that are
> looked at in grading this disease and staging it, assessing it? The
> major one is liver histology. I think that, in hepatitis B, we are
> still very dependent upon liver biopsy to assess the need for therapy
> and prognosis of the disease.
>
> When looking at the liver biopsy, we look at two things. We look at
> the activity, the necroinflammatory changes, necrosis and
> inflammation. Second, we look at fibrosis. Now, necroinflammation can
> come and go. The enzymes go up, it\'s higher. The enzymes go down,
> it\'s lower. The liver biopsy changes lag behind the enzymes and they
> integrate the enzymes over the previous year or so.
>
> So it is a more integrated look at the activity of the liver disease
> over time. I know the ALT may not correlate very well with these, but
> if you have a large enough series, it does.
>
> You usually look at the inflammation and necrosis in three different
> things and you come up with a score. The fibrosis goes from none to
> portal fibrosis to septal formation to bridging between portal and
> central veins, and then cirrhosis.
>
> The bottom line in chronic liver disease in general is fibrosis,
> progression to cirrhosis. Why do we even look at this? We look at this
> because we think that the degree of necroinflammatory change is
> prognostic for the progression of fibrosis. That is what we believe. I
> think most pathologists will agree with that, that if you have a high
> level of disease activity, fibrosis development will be more rapid.
>
> \[Slide.\]
>
> So here are the scoring systems for hepatitis. These are the U.S.
> systems. They are basically based on systems developed at the AFIP by
> Dr. Ishak and Dr. Knodell who developed the first system here,
> Histology Activity Index. You will hear about HAI. It includes the
> three elements of inflammation and necrosis as well as fibrosis, goes
> from 0, 1, 3 and 4.
>
> This is the original system. We don\'t like it because it doesn\'t use
> enough numbers and, also, it jumps from 1 to 3. 1 is mild, and 3 you
> are already in trouble a little bit. You have got bridging.
>
> \[Slide.\]
>
> So we moved away from this system to the next slide which is the
> system devised by Dr. Ishak again. Actually, the first one is his
> system as well where fibrosis is categorized from 0 to 6 so we have
> more numbers to deal with and a better gradation, where portal
> fibrosis is 1 or 2, bridging 3 or 4 and cirrhosis early are incomplete
> cirrhosis and complete cirrhosis. So this is a better scoring system
> and I think we are all more pleased with this.
>
> The estimation of inflammation in necrosis is about the same. It goes
> from 0 to 18.
>
> \[Slide.\]
>
> Let me go a little bit into therapy as it relates to the natural
> history
>
> \[Slide.\]
>
> And the issue of why do we treat patients, what are the goals of
> therapy, which we will be dealing with today. Well, three major
> things; to improve systems and quality of life. The trouble is that
> the majority of patients with chronic hepatitis C have minimal or no
> symptoms. Many of the drugs we treat them with make them more
> symptomatic. So this is a pretty hard thing to measure and we have
> been remiss in our measurements of symptoms and quality of life in
> studies of hepatitis B.
>
> To decrease infectivity; this is important for some patients,
> particularly if you are a surgeon and you want to operate and you have
> hepatitis B. But, for many patients, it is not an enormous problem. It
> can be a problem for the heterosexual single person who wants to have
> more sexual partners but for a person in a family, you can vaccinate
> family members. So this is a less important goal.
>
> The most important goal, the one that we usually use, is to prevent
> progression of disease to cirrhosis, to hepatic compensation and
> death. This is a slow thing to occur, though. If you did a trial that
> showed prevention of end-stage liver disease, you would have to do a
> study for ten or fifteen years.
>
> Furthermore, you would like to treat patients earlier before they even
> come close to decompensation. So we are not going to see trials that
> prevent progression to end-stage liver disease unless they are trials
> in patients with preexisting cirrhosis.
>
> \[Slide.\]
>
> So what surrogate endpoints can we use to correlate with these
> outcomes and what are the appropriate endpoints; loss of e, loss of
> surface. That would be a good endpoint, wouldn\'t it? I think we would
> all agree with that. We wouldn\'t need much data to support that as an
> endpoint. I think we would all agree with that. We wouldn\'t need much
> data to support that as an endpoint.
>
> Loss of HBV DNA or its fall below a certain level. Normalization of
> ALT or improvement in histology. The answer to that is you need all of
> these put together.
>
> \[Slide.\]
>
> In hepatitis C, the endpoints of therapy have been kind of carefully
> defined and people have joined together and used them in all studies
> of natural history and therapy. In hepatitis B, we haven\'t gotten
> together as well, but let\'s remind you about the types of responses
> and timings that are important in hepatitis C. I think they apply to
> hepatitis B as well.
>
> There are virological responses, loss of e and HBV DNA. Of course, if
> you don\'t have e, this you can\'t use as an endpoint but you could
> use HBV DNA as an endpoint. Biochemical, normal ALT, histological,
> improvement in histology. Or a complete response for hepatitis B would
> be all of those and loss of surface antigen as well, resolution of
> disease.
>
> It is also important and I think this is what I would like to stress
> to the group here is to define the timing of the response. Initial we
> be something that occurs early during treatment, either at three or
> six months. End of therapy is what is the status when therapy is
> stopped.
>
> In trials of antiviral therapy in hepatitis B, end-of-therapy response
> is what has been used in lamivudine and, I guess, adefovir as well.
> The problem is that, when you stop therapy, patients may relapse. So a
> more important endpoint would be a sustained response. The question is
> at what point after stopping can you call the response sustained, six
> months or twelve months.
>
> In hepatitis C, it looks like six months is quite adequate. I don\'t
> know that that is adequate for hepatitis B, whether relapses that
> occur when you stop therapy all occur within the first six months.
> That has not been defined. So this is a problem.
>
> Let me add another type of response which is called a maintained
> response. That means the response is present while continuing therapy.
> This is the important issue in hepatitis B is that we are going to
> start talking about maintenance, continuous therapy, not therapy for a
> defined period like four months or six months or a year but long-term
> maintained therapy. So we need to have a definition of a maintained
> response.
>
> \[Slide.\]
>
> So here is a virological response. This is the typical one that has
> been used in trials; loss of e and fall of HBV DNA levels below 10^5^,
> negative by hybridization assays. This occurs in 25 to 48 percent of
> patients given interferon, alpha interferon, at least in the old
> studies, in Western patients. It is my opinion that it is less common
> in Asian patients although this is still argued.
>
> It occurs in 20 to 32 percent of patients given a twelve-month course
> of lamivudine. It occurs, unfortunately for the clinical trialists in
> 8 to 12 percents on no therapy. So you have to show a difference here.
> Sometimes, that is hard to do.
>
> The question is is this response durable and does it result in
> long-term improvements in disease.
>
> \[Slide.\]
>
> Loss of e cannot be used as an endpoint in patients with e-negative
> disease and we generally rely, in them, on a decrease in HBV DNA below
> 10^5^. The trouble is HBV DNA levels fluctuate widely, particularly in
> this disease. So how do we know that we really have gotten anywhere,
> that the response is sustained? How durable is the decrease without
> other changes in viral status?
>
> I don\'t have an answer for that.
>
> \[Slide.\]
>
> Here is the response that we wish we could achieve which is loss of
> surface antigen and development of antibody to surface antigen. It
> occurs in about 8 percent of patients given a four-to-five-month
> course of alpha interferon, at least in the studies from the 1980s. It
> occurs in 1 to 2 percent of patients given a 12-month course of
> lamivudine. It is rare on patients on no therapy, actually. One of the
> most convincing pieces of evidence that these drugs work is the loss
> of surface antigen on a portion of patients.
>
> It is extremely rare in the treatment of e-negative form of disease,
> though, unfortunately. This response is durable.
>
> \[Slide.\]
>
> The second type of response is a biochemical response, fall of ALT
> into the normal range. This often accompanies loss of e-antigen and a
> decrease in HBV DNA below 10^5^. It is not durable unless the decrease
> in DNA is durable, so it is a surrogate indirect marker. But it is a
> surrogate indirect marker for the necroinflammatory disease.
>
> \[Slide.\]
>
> For most clinical trials, we do rely upon histological improvements
> using virtually all studies of antiviral therapy. Actually, in
> hepatitis C, it may stop being used as the virological response is so
> convincing that it may not be as necessary anymore. But, in hepatitis
> B, it still is necessary.
>
> Typically, in clinical trials, improvement is called a two-point or
> greater improvement in the HAI score which ranges from 0 to 22
> compared to baseline. But we don\'t know whether that is really a
> significant change, two points.
>
> As I pointed out to you in HAI score designed by Knodell, there is
> this skip between 0, 1 and 3. So a two-point change could be from a 1
> to a 3 which could easily be due to sampling error or to a different
> pathologist looking at the slide.
>
> Furthermore, necroinflammatory scores can change rapidly and get
> better and worse. If the person relapses when therapy is stopped, that
> improvement that you saw on therapy is likely to disappear with time.
>
> Fibrosis scores represent the best evidence for progression of disease
> but they are unlikely to improve much with treatment and they improve,
> if they improve, very slowly.
>
> \[Slide.\]
>
> Alpha interferon is the first drug that was licensed for hepatitis B.
> It is a cytokine, acts through receptors. Repegylated forms are now
> available and I suspect the trial of pegylated interferon will be
> starting up in hepatitis B.
>
> \[Slide.\]
>
> This is the type of response, the character of response that occurs
> with interferon treatment\--I mean, a good response in a patient who
> is called a responder. This person had elevated ALT and HBV DNA here
> by dot blot\--this is an old patient treated in the 80\'s with alpha
> interferon treatment.
>
> The levels go down and it becomes negative by the end of treatment. He
> clears e-antigen. A couple of things to point out. First of all, his
> enzymes actually get worse on treatment rather than better. This is
> typical of the response to alpha interferon. There is a flare of
> disease that usually begins at about two months.
>
> It is usually asymptomatic but occasionally it will be symptomatic.
> Occasionally, a patient will develop jaundice. With this flare, the
> DNA falls and e is clear.
>
> The second point I would like to make is that the loss of e didn\'t
> occur during treatment. It occurred after treatment. This is typical
> as well. So, at the end of treatment, there is no improvement in this
> patient whatsoever. The end-of-treatment response doesn\'t look very
> good, does it? The enzymes are higher, still DNA-positive, still
> e-positive.
>
> What is important is that, at twelve months, he has a sustained
> response. He is e-negative. His enzymes are not normal. He has anti-e.
> This patient was followed indefinitely at the NIH and, actually, at
> two years, when he came back, he had also cleared surface antigen.
> This is what we had found at the NIH. Other people haven\'t found it
> as commonly as we have, but in five- to ten-year follow up, the
> patients who have lost e on alpha-interferon therapy, 70 to 80 percent
> of them will clear s, sometimes many years later. That is very
> supportive.
>
> So this is the best response with alpha interferon. The trouble is not
> everybody has such a response. Some people don\'t clear e. Some people
> have a flare and don\'t clear e.
>
> \[Slide.\]
>
> Some people do this. This person was treated. He had a nice flare. In
> fact, he was flaring when he started therapy. He clears e-antigen
> rapidly, develops anti-e. His enzymes are normal. He does have an
> end-of-treatment response. But, at nine months, he is e-positive again
> and his enzymes have gone up again. He has relapsed before the
> twelve-month period.
>
> This is Patient B. I will show you Patient B again. Patient B has
> genotype B.
>
> \[Slide.\]
>
> Here is e-negative chronic hepatitis B with alpha interferon, what we
> used in the past. We gave it up. We found that this is what happened
> to virtually every patient we treated with e-negative disease. You
> have a nice response on-treatment. Almost before treatment, they
> become DNA-negative by hybridization. The enzymes are normal.
>
> But, when you stop therapy, these patients relapse. We have never had
> a long-term response to interferon on an e-negative patient. There has
> been reported from Italy, where this is more common, that they can get
> a long-term response in about a quarter of people with a year of
> interferon treatment.
>
> One of the difficulties is you don\'t know when the patient really has
> responded. There is not something nice like clearance of e-antigen.
> You rely upon the DNA test.
>
> \[Slide.\]
>
> So interferon for hepatitis B had many problems and was effective only
> on a third of patients. It is expensive. The side effects are very
> difficult, can be very severe. We use high doses of interferon in
> hepatitis B. It is not appropriate for many categories of patients.
>
> \[Slide.\]
>
> Lamivudine came along and was the answer to many of those problems
> with alpha interferon. You have heard about this. It is approved for
> use in chronic hepatitis B as a one-year course of therapy but
> continuous long-term use is common in this disease because it is so
> easy to administer and has so few side effects.
>
> \[Slide.\]
>
> This is what I call a maintained response in talking about responses
> in a patient on lamivudine long-term. This is my Patient B that I
> showed you before who relapsed after interferon. He has bad disease
> again, responds immediately, becomes DNA-negative, becomes e-negative,
> after a year and a half of therapy.
>
> Here are the histology scores. He begins with very active disease, a
> score of 14. At one year, it has decreased markedly, you see more than
> two points, to 4. A four-year biopsy is 1. So it looks like terrific
> response. He is still surface antigen. He is still on lamivudine. It
> is a maintained response.
>
> \[Slide.\]
>
> For e-negative chronic hepatitis B, also a maintained response on
> lamivudine, a patient with fluctuating disease develops normal enzymes
> that stay normal. There is no loss of e but HBV DNA falls here from 53
> million down to 200 copies per ml by PCR. We don\'t detect it now. It
> is less than 100 and his histology has also has improved markedly. He
> is still on lamivudine, a maintained response.
>
> \[Slide.\]
>
> The problem with lamivudine is viral resistance where HBV DNA goes
> down but then creeps up again towards baseline. This is associated
> with a mutation in the polymerase gene, in the so-called highly
> conserved YMDD motif either to YVDD or YIDD. These patients generally
> lose their biochemical response and their histology may not improve.
>
> This patient was improved at one year, 12 months. He had resistance at
> this point. You can see his histology had improved by more than two
> points. His ALT was improved, quite a bit, actually. His DNA was
> little bit less, so it looked like a good response.
>
> The problem is, with time, this is lost and this patient developed
> cirrhosis on lamivudine.
>
> \[Slide.\]
>
> These are the histology scores of patients. This is the activity,
> remember, the necroinflammatory activity, before treatment, at one
> year and at four years. These are patients with a maintained response,
> beautiful resolution of disease. With resistance, there is a decrease
> you see. On average, at four years, they are still a little bit better
> in necroinflammation.
>
> \[Slide.\]
>
> The problem is fibrosis. I told you fibrosis didn\'t go away, but it
> looks like it may improve in patients who have maintained responses
> largely resolved. Fibrosis scores go from 4 to 3 to 1. But in patients
> with resistance, there is no improvement in fibrosis over time. So we
> are not sure these patients are really better off.
>
> \[Slide.\]
>
> The other problem is this, the plague, which is late relapse. This is
> my famous Patient B who relapsed after interferon, had a nice
> maintained response to lamivudine at one year. His histology was
> basically resolved. At five years, he has relapsed. His disease is
> back. HBV DNA close to where it started and ALT elevated. So
> maintained response may not be durable either in a person who remains
> surface-antigen positive.
>
> \[Slide.\]
>
> This is the rate of resistance in our studies in e-positive patients,
> very high. E-negative, less with long-term lamivudine therapy.
>
> \[Slide.\]
>
> The major shortcoming of long-term lamivudine therapy for hepatitis B
> is the emergence of resistance. In larger studies, it occurs in about
> 20 percent of patients per year so it can approach a very high rate of
> five years. The loss of surface antigen appears to reliably predict
> long-term benefit and you can stop lamivudine if the surface antigen
> is lost.
>
> But loss of e does not insure that you will not have relapse. Future
> studies should focus on combinations that might prevent resistance.
>
> \[Slide.\]
>
> So what is the optimal therapy of hepatitis B? The first paper on
> treatment of hepatitis B using interferon came out twenty-five years
> ago and we still don\'t have a good answer for this question. Should
> it be monotherapy or combination therapy, for a defined period or
> continuous, for all patients or only those with moderately severe
> disease?
>
> If you use monotherapy, which agent? If you use combination therapy,
> which combination?
>
> \[Slide.\]
>
> This was a meeting that we held about two years ago on the management
> of hepatitis B. We had to put a question mark after therapy. It is
> very hard to make statements recommending therapy in this disease,
> what exactly to use. Should you use interferon first? If you use
> interferon, should you use pegylated interferon? What dose should you
> use? How long should you treat people for? I don\'t know.
>
> I find it kind of counterproductive to use standard interferon today
> with the presence of pegylated interferon on the market. Yet, we
> don\'t know what dosage to use or how long to use it for or whether it
> works very well.
>
> What about lamivudine? What patients should use it? It is very hard to
> decide. In patients with decompensated liver disease, it is pretty
> clear. But, in those with compensated liver disease, the problem of
> resistance is one that can plague one. And what will be the role, now,
> of adefovir as it comes to market?
>
> \[Slide.\]
>
> So we have a lot of work to do in hepatitis B. I think the future
> direction should be on combination therapy with long-term outcomes
> assessed, not just one year on-therapy outcomes with histology
> verification of long-term benefit, not just a decrease in inflammatory
> scores by a couple of points.
>
> Loss of surface antigen; it would nice to have that as the gold
> standard if it could be reached in a large proportion of patients.
>
> These are some appropriate directions, I think, combinations of
> interferon with one of the nucleosides, nucleoside combinations,
> long-term, and so forth.
>
> Thank you.
>
> DR. GULICK: Thanks, Dr. Hoofnagle. We probably have time for a few
> questions from the panel, if you wouldn\'t mind staying.
>
> Dr. Mathews?
>
> DR. MATHEWS: Thank you. That was a great talk. Could you clarify
> something about the e-negative state? The example you showed was a
> patient who apparently had wild-type virus and developed a mutant and
> had e-antibody. But, presumably, the precore mutant is transmissible.
> Are patients who are initially infected with the precore mutant
> different clinically from those who acquire it in the course of
> chronic infection?
>
> DR. HOOFNAGLE: I wish I knew the answer to that, and we should know
> the answer to that, but we don\'t. The precore mutant is not very
> transmissible. This is the truth. If it is transmitted, it usually
> results in acute self-limited disease.
>
> In fact, I don\'t know that it has been very well shown that you can
> get chronic hepatitis B from a precore mutant infection. Chronic
> hepatitis B generally results from an e-positive infection, de novo
> chronic hepatitis B. So it is probable that most patients begin with a
> period of e-positivity and then evolve into a precore mutant. That is
> probably the natural history.
>
> But we don\'t know for sure. The precore mutant can cause hepatitis B,
> acute hepatitis B. In fact, there is a little evidence that it is more
> severe than exposure to e-positive disease. So newborns, for instance,
> who are infected with the precore mutant develop clinically apparent
> acute hepatitis, which is virtually unheard of in newborns infected
> with e-positive disease.
>
> So this isn\'t very clear, is it? But the patient I showed you evolved
> from a wild-type to a mutant-type virus. The interesting thing is that
> was a child and his father is being treated by us for e-positive
> hepatitis B. So that is the source of the disease, e-positive. But the
> child has evolved to a precore mutant and he has Genotype\--I believe
> he had Genotype C. This was an Asian child.
>
> DR. MATHEWS: So presumably someone who was infected with the precore
> mutant would not have e-antibody so you could serologically
> distinguish them that way?
>
> DR. HOOFNAGLE: No. The precore-mutant patients do have e-antibody.
> They are also called e-antibody-positive chronic hepatitis B.
>
> DR. MATHEWS: But if they were infected with the precore mutant, why
> would they make e-antibody if they never were exposed to antigen?
>
> DR. HOOFNAGLE: Because, as I showed you, the e-antigen has the same
> amino-acid sequence as core antigen. In fact, the t-cell responses to
> e are the same as to core. It is just the b-cell responses are
> different. It is wild. It was really a shock when this was first shown
> by the cloning of the hepatitis B virus. We all kind of just dropped
> our mouths open that there was no separate gene for e-antigen, that it
> was part of core.
>
> So if you take purified core particles, which is what I did, and
> immunize animals, you get anti-core but you also get anti-e. So, just
> because you can\'t synthesize it and secrete it from the liver cell
> doesn\'t mean e-antigen epitopes are not being made.
>
> Confusing; right?
>
> DR. GULICK: We have time for one or two more questions. Dr. Block?
>
> DR. BLOCK: Jay, thanks for a very nice overview. In speaking about the
> e-negative hepatitis-B carriers, you spoke mostly about those who are
> e-antigen-negative because of the mis-sense mutation. That was nicely
> covered, and you discussed their eligibility for treatment.
>
> I am wondering, could you talk again just briefly about the population
> of individuals who are e-antigen-negative spontaneously, not because
> of a mis-sense mutation, not because of the precore mutation. You
> alluded to them briefly. There was a paper in Hepatology a couple of
> months ago that talked about the risks of disease in individuals who
> are simply low DNA, e-antigen-negative, but surface-antigen-positive.
>
> I am thinking about the eligibility of those for treatment, that
> population.
>
> DR. HOOFNAGLE: Do you mean patients with normal liver enzymes?
>
> DR. BLOCK: Well, they may or may not have normal enzymes. Usually,
> they do, of course, but they are characterized by e-antigen-negative
> relatively low DNA. Their risk of liver disease is still, of course,
> greater than those of the general population. They also present a
> challenge for treatment because of the markers. They are
> surface-antigen positive.
>
> What is your thinking about that group?
>
> DR. HOOFNAGLE: I am not sure we are talking the same language, Tim.
> Not everybody with e-negative chronic hepatitis B has the classical
> precore mutant. There are other mutations in the so-called basic core
> promoter that can result\--
>
> DR. BLOCK: No; I\'m sorry. I didn\'t mean the molecular biology in
> that detail. I just mean this would be people who would be\--this is
> what you would call the inactive-carrier state.
>
> DR. HOOFNAGLE: Inactive carrier. Should these people be treated?
>
> DR. BLOCK: That\'s right. What is their risk and are they eligible for
> treatment?
>
> DR. HOOFNAGLE: The risk of chronic liver disease and cancer is
> somewhat low in them if they do not have cirrhosis. As I showed you,
> most people begin with a period of chronic hepatitis and then they
> resolve it. During that period of chronic hepatitis, they can develop
> cirrhosis. So some people that we call inactive carriers actually have
> 3-plus fibrosis or cirrhosis as a result of the disease they had in
> the past.
>
> This is what makes these cross-sectional studies very confusing. So,
> in those patients, in a patient who has cirrhosis who then
> seroconverts as normal enzymes, the disease burns out, that patient
> has increased risk of cancer. There is no question about it.
>
> But if a person is truly an inactive carrier and if you do a liver
> biopsy, it is usually not done, and it shows minimal or no fibrosis,
> it is the general feeling that risk of cirrhosis in those patients is
> uncommon.
>
> Now, the disease can reactivate. You can reactivate hepatitis B by
> manipulations; for instance, high-dose steroids or cancer
> chemotherapy, and so forth. We see a case at the NIH once a year in
> our cancer group who have treated someone for cancer who is a carrier
> to begin with and they reactivate the disease and they get an acute
> flare of hepatitis after their third or fourth cycle of chemotherapy.
>
> So you can reactivate an inactive carrier to active disease but, in
> general, it is fairly benign. Now, can you treat them? Is it
> worthwhile treating them? Nothing happens when you do is the problem.
>
> We haven\'t treated many inactive carriers with lamivudine. I have
> treated a couple and it doesn\'t\--well, what can you do. There is
> nothing to do. The enzymes are normal. The DNA is low. The liver
> histology is mild. So there is no kind of endpoint. But they don\'t
> clear surface antigen.
>
> In fact, the levels of surface antigen don\'t decrease. This comes up
> in delta hepatitis because delta hepatitis usually is superinfection
> of hepatitis B with a delta agent and it typically occurs\--when it
> occurs, the B is inactive. It is like an inactive-carrier state of B
> and they have delta on top of that.
>
> If you treat those patients with lamivudine, for instance, nothing
> happens to the underlying B and the delta goes on. Interestingly, if
> you treat the delta, sometimes the B will reactivate. So there is this
> interactive\--making delta the most confusing disease to treat, and
> difficult.
>
> So I don\'t know that the therapies that are currently available are
> of use, but I think, actually, something should be tried to look at it
> carefully, looking at surface antigen titers, maybe even looking at
> histology in a small group of patients who are so-called inactive
> carriers.
>
> DR. BLOCK: Thank you.
>
> DR. GULICK: We will take one last question from Dr. Stanley.
>
> DR. STANLEY: This may be a little too lengthy question but, at some
> point, I would like to have someone address for us the capability or
> the technology available to do genotypic or phenotypic resistance
> testing of hep B.
>
> DR. HOOFNAGLE: I\'m sorry; the technology available to what?
>
> DR. STANLEY: To do genotypic and phenotypic resistance testing for
> hepatitis B.
>
> DR. HOOFNAGLE: Well, those tests are\--there is a commercial company
> that has a test for some of the classic mutations as well as\--their
> sequencing is usually done to characterize the mutations. For
> instance, with lamivudine resistance, it is almost invariably in this
> YMDD\--in fact, I think it has been invariably in the YMDD motif. So
> you don\'t need to do a lot of sequencing to detect that.
>
> Furthermore, Glaxo and the companies that make adefovir have been
> doing this for investigators
>
> DR. STANLEY: But I am more interested in the phenotypic capability.
>
> DR. HOOFNAGLE: Phenotypic
>
> DR. STANLEY: In vitro testing of\--like we do with HIV where we can
> culture and show that it is resistant or not. I know that it is not
> the same technology for hepatitis B.
>
> DR. HOOFNAGLE: Cell-culture systems have been developed that used
> cloned hepatitis-B virus and put these mutations in that show that
> with the YMDD mutation, the virus in vitro as well is resistant to
> lamivudine and is sensitive to other agents like adefovir and
> entecavir. So you can show the lack of cross-resistance with the
> various agents and assess them.
>
> DR. GULICK: We will take one more last question from Dr. Kumar.
>
> DR. KUMAR: Dr. Hoofnagle, can you comment on this two-point decline in
> histology activity index. Is that a validated point? Has that proven
> to be, in the long term, if somebody has a two-point decline, that,
> over the long run, that they are going to do well?
>
> DR. HOOFNAGLE: Zack Goodman is smiling at me, the pathologist from the
> AFIP who can comment on this. I think a two-point change in histology
> is not very significant. Of course, when you are doing a large study
> and you are looking at statistics, yes, it means that there is
> improvement. But, in an individual patient, a two-point improvement in
> histology is not very significant.
>
> I think a new algorithm has to be developed for what is a histological
> response, yes or no. It has to be more than two points and it should
> probably take other things in mind. For instance, it should be
> improvement in necroinflammatory and no worsening of the fibrosis, for
> instance. That would be bad, wouldn\'t it, if the fibrosis got worse
> but the inflammation was down a little bit.
>
> Furthermore, I think if you start with an inflammatory score of 18 and
> you go to 16, that is different than if you start with an inflammatory
> score of 4 and you go to 2. So the pathologist at the NIH has
> suggested it, that we use a percent drop, that a greater than 50
> percent drop in necroinflammatory should be worthwhile.
>
> But I think this is the type of thing that needs to be tested on
> cohorts or samples to show what really correlates with a long-term
> improvement.
>
> DR. GULICK: Can I suggest that we delay further discussion until the
> questions on that particular point.
>
> We will move on to Dr. Anna Lok from the University of Michigan who is
> going to discuss the treatment of chronic hepatitis B.
>
> **Treatment of Chronic Hepatitis B**
>
> DR. LOK: Good morning.
>
> \[Slide.\]
>
> First of all, I would like to thank the organizers for inviting me
> here and I would like to thank Jay Hoofnagle for setting the tone. He
> has provided a lot of the introductions which is going to make my job
> a little easier.
>
> \[Slide.\]
>
> I was asked to review sentinel trials on treatment of hepatitis B
> specifically focussing on interferon and lamivudine and to talk a
> little bit about what we currently do in practice and discuss some of
> the issues for future clinical trials.
>
> \[Slide.\]
>
> Jay had touched upon the goals of treatment. Actually, what we would
> like to do is have sustained suppression of hepatitis-B virus
> replication because we believe that, if we are able to suppress
> hepatitis-B virus replication, that this would lead to remission of
> liver disease and ultimately to improvement in clinical outcome.
>
> What the FDA is interested in knowing is really whether, if we achieve
> No. 1 and No. 2, that we would get No. 3. This, unfortunately, is
> going to be a very difficult question to answer and prove because of
> the very long natural history. But we will try to see if there is some
> data out there.
>
> \[Slide.\]
>
> Some of the things that we need to consider when we review a clinical
> trial or we plan a clinical trial is to ask ourselves what are the
> patients that we want to include in the study. I think that we now
> understand the natural history enough that we can\'t just lump
> hepatitis B as one group. It is a very heterogeneous disease with
> multiple phases and patients in different phases behave differently.
>
> I think we can broadly consider patients with e-antigen-positive
> chronic hepatitis B. As defined by Dr. Hoofnagle\'s talk, these are
> patients who are e-antigen-positive with high levels of virus DNA,
> elevated liver enzymes, evidence of chronic hepatitis on liver biopsy.
>
> The e-antigen-negative chronic hepatitis B patients are the ones who
> are surface-antigen-positive, e-antigen-negative. The majority of them
> are e-antibody-positive. They have high levels of virus DNA. They are
> a little lower than the e-antigen-positive ones, but, generally
> speaking, the DNA levels are in the region of 10^5^ to 10^6^ to 10^7^.
>
> They should have elevated liver enzymes and evidence of chronic
> hepatitis on biopsy. We are not talking about the inactive carriers
> that Dr. Block asked about. Those are the patients that, right now, we
> are not sure that they should be included for treatment. Certainly,
> patients with decompensated cirrhosis, whether they are waiting for
> transplant or not, they need to have something to help stabilize them.
>
> We need to think within each of these groups of patients what are the
> specific inclusion-exclusion criteria. I will come back to some of
> these issues. Obviously, we need to think about treatment regimens.
> Should this be monotherapy? Should this be combination therapy?
>
> We need to think about sample size. Is this a properly done study?
> What are the endpoints for treatment and how do we assess response.
> Obviously, the most important question for today\'s meeting is whether
> any of these things allow us to predict clinical outcome.
>
> \[Slide.\]
>
> Let\'s do a little bit of comparison about interferon and lamivudine
> clinical trials for patients with hepatitis B e-antigen-positive
> chronic hepatitis B.
>
> Before we start comparing, it is very important for us to understand
> that we are comparing studies done about ten years apart. Our
> understanding of the disease and our capability of measuring various
> things differ in the era of the interferon trials versus the era of
> the lamivudine trials and, as we move forward to other new trials,
> what applies in the past may not apply in the future as we understand
> the disease better.
>
> A lot of the interferon trials were actually controlled trials but the
> control patients did not receive treatment because it is very hard to
> justify giving patients placebo injections. Therefore, the controls
> usually received no treatment whereas with lamivudine, adefovir and
> many of the other orally administered nucleoside-nucleotide analogues,
> because they are orally administered with very little signature side
> effects that the patients are aware of, placebos can be administered.
>
> Interferon trials tend to be a lot smaller in size. In fact, there are
> very few industry-sponsored hepatitis-B clinical trials. The majority
> of them were investigator-driven and, therefore, they were
> single-center, small trials.
>
> Lamivudine trials tend to be a little bit bigger. In the era of
> interferon trials, we didn\'t think about sample size. It wasn\'t
> something that we knew too much about. The lamivudine trials, and
> subsequently in all the licensing trials, the studies are powered for
> the primary endpoint.
>
> Here we are talking about e-antigen-positive chronic hepatitis B but
> the primary endpoint for the interferon trials and the lamivudine
> trials are different. For the interferon trials, we used virological
> endpoints. Most studies used e-antigen loss and hepatitis-B virus DNA
> dropping to undetectable levels using whatever assay was available at
> that time point as the primary endpoint.
>
> The assays were, in general, home-brew, dot-blot hybridization assays
> or some of them used the commercially available liquid hybridization
> assays. The majority of these assays had a lower limit of detection of
> 1 million or 10^7^ copies per ml.
>
> The lamivudine trials used histology as an endpoint. As you have all
> heard, this is done with a decrease in the HAI by two points or more.
> Whether the fibrosis changed or not was not considered and the
> virological assays used in most of the lamivudine trials was the
> liquid hybridization assay which had a detection limit of about 10^7^
> even though the manufacturer claimed it to be 10^6^.
>
> \[Slide.\]
>
> What about e-antigen-negative chronic hepatitis B patients? Again, the
> entry criteria for both interferon and lamivudine trials was whether
> the patients had detectable hepatitis-B virus DNA, but, again,
> detectable using whatever assays are available. Most of the patients
> had detectable DNA based on dot-blot or liquid hybridization assays
> for the interferon trials meaning that they had viral levels that were
> at least above a million copies per ml.
>
> The majority of the lamivudine trials also used a liquid hybridization
> assay although some of the studies used the branch-DNA assay or the
> hybrid-capture assays and many of the recent studies also report PCR
> data. Nonetheless, almost every study would only include patients with
> high viral load, probably 10^5^, 10^6^ or even higher. All these
> patients had elevated liver enzymes.
>
> Some of the interferon trials include controls. There is only one
> trial of lamivudine that included controls, placebo controls, and,
> even then, the placebo controls ran through only half of the duration
> of the study. Unfortunately, with e-antigen-negative chronic hepatitis
> B, the studies tend to be smaller. Until very recently most people
> were saying that this is a rare disease, let\'s not put too much
> attention to it. So many of these studies tend to be smaller and less
> well organized.
>
> Duration of treatment is highly variable. With interferon, it ranges
> from about three to 24 months. Most of the studies had been about six
> to twelve months. With lamivudine, initial studies treated patients
> for about twelve months and it was realized that the relapse
> post-treatment is very high. Many of these studies now go on to
> indefinite life-long treatment which is a major concern, particular
> with issues of drug resistance.
>
> What about primary endpoints? Histology, surprisingly, is not included
> as primary endpoint in many of these studies of e-antigen-negative
> chronic hepatitis B although this probably is very important. Since we
> are not really able to look at e-antigen loss or e-antigen
> seroconversion as an endpoint and, therefore, the endpoint tends to be
> fairly soft, ALT dropping to normal levels and hepatitis-B virus DNA
> undetectable, again using the assay of the day.
>
> \[Slide.\]
>
> Let\'s go on now to some of the interferon trials. Since there are
> really not that many good sentinel interferon trials, I took the
> liberty of sharing with you some data that will be presented at the
> ISAL Consensus Conference in a month from now. This is an update of a
> meta-analysis of randomized controlled trials of interferon presented
> by Craxi, et al.
>
> They looked at 24 randomized controlled trials with about 900
> interferon-treated patient and 400 control patients because, in some
> of the trials, there were several different dose regimens of
> interferon so the number of treated patients outnumber the controls.
>
> If you look at the difference in response rate between the treated
> patients and the controls, the interferon treatment does affect a
> positive response whichever parameter you use, ALT normalization,
> difference of 26 percent, clearance of e-antigen, difference of
> 24 percent, sustained loss of HBV DNA, again mostly hybridization
> assays, difference of 23 percent and clearance of surface antigen, a
> difference of 6 percent. All these are highly statistically
> significantly different.
>
> You can also see a fairly tight 95 percent confidence interval.
>
> \[Slide.\]
>
> What about longer-range outcome. Here is where you get into trouble.
> First, you don\'t have 24 studies; you have twelve studies. Secondly,
> you start asking, the number of treated patients is fairly similar but
> how come you now have more controls. That is because a lot of these
> studies throw in a lot of historical controls, nonconcurrent controls.
> That makes this data very, very muddy.
>
> The mean follow up is about six years. All the parameters indicate
> that the interferon-treated patients did better in terms of loss of
> surface antigen, in terms of less hepatic decompensation, less
> development of hepatocellular carcinoma as well as less liver-related
> death. But, because of the use of nonconcurrent controls and because
> all these studies show significant heterogeneity of results, we are
> not sure how meaningful these results are.
>
> \[Slide.\]
>
> I am going to show you just one measure of the clinical trial of
> interferon therapy and that is Perillo\'s study. It actually led to
> approval of interferon therapy for chronic hepatitis B.
>
> This is a study that involved about 160 patients, patients who
> received prednisone priming that was fashionable in the 1980s. We
> thought that if we give patients a short course of prednisone,
> suppress the immune system, bring down the liver enzymes and then
> abruptly withdraw it, that the immune system might rebound and the
> patients might now respond better to interferon therapy.
>
> We have since then recognized that this may not be the smartest thing
> to do and it doesn\'t always do what you want. Then there were two
> groups that received interferon alone, 5 milliunits daily or 1
> milliunit daily\--we now recognize that this is a suboptimal
> dose\--and then an untreated control group.
>
> Again, what you see is that, in terms of the primary endpoint which,
> in this study, was loss of hepatitis-B virus DNA by the Abbott liquid
> hybridization assay and loss of hepatitis B e-antigen. The two groups
> that received optimal dose of interferon had about 36, 37 percent
> response. The suboptimal dose obviously had a lower rate of response.
>
> Again, we sort of saw that some patients dropped their virus DNA down
> to undetectable level but they still remained hepatitis-B
> e-antigen-positive. I should clarify, however, that, in this study,
> the patients received only sixteen weeks of interferon and treatment
> response was actually assessed six months after interferon was
> stopped. So it wasn\'t really while the patients were still on
> treatment but, rather, after the patients had come off treatment.
>
> When you look at normal ALT normalization at the last follow up which
> is six months after stopping treatment, that is seen in about 44
> percent of patients and a couple of patients that reactivate after
> stopping treatment.
>
> \[Slide.\]
>
> So much for interferon treatment of e-antigen-positive chronic
> hepatitis B. What about interferon treatment of e-antigen-negative
> chronic hepatitis B. As I have mentioned, this is much more muddy.
> There were very few controlled trials so there were only a handful of
> untreated controls that one can compare against.
>
> Since it is recognized that, in patients with e-antigen-negative
> chronic hepatitis B, sustained spontaneous improvement is rare. Dr.
> Hoofnagle mentioned that these patients tend to run and
> up-and-downhill course but, after they go down, they tend to go up
> again. So sustained remission is extremely uncommon and, therefore,
> inclusion of controls is rarely considered in clinical trials.
>
> Often, clinical trials compare different regimens of interferon
> therapy or comparing some of these patients against active treatment.
> Many of these were just single clinical trials.
>
> \[Slide.\]
>
> I borrowed this data from Dr. Alfredo Alberti who presented data at
> the NIH-organized workshop two years ago. This is really summarizing
> 700, 800 patients treated with interferon therapy. As you can see, at
> the end of treatment, while the patient, be it three months or six
> months or twelve months duration of therapy, the biochemical response,
> meaning normalization of liver enzymes, was seen in about 55 percent
> of patients with a range of about 40 to 70 percent.
>
> The virological response, meaning hepatitis-B DNA, undetectable in
> most instances by non-PCR-based assays, in about 50 percent of
> patients with a range of about 40 to 60 percent.
>
> There are some studies that report on sustained response, and
> sustained response was, in general, assessed six to twelve months
> after stopping treatment. Overall, about 20 percent of the patients
> had sustained response with a range of about 7 to 38 percent. Much of
> this variability was related to the duration of treatment.
>
> \[Slide.\]
>
> What about histology? There are a couple of studies that did report on
> histology of interferon treatment in patients with e-antigen-negative
> chronic hepatitis B. As you can see, in the patients who received
> treatment, there was a decrease in the HAI score, fairly significant
> in some of these studies, which you don\'t see in the controls.
>
> The repeat biopsies were, in general, taken a year after the patients
> got into the treatment, most of the time at the end of the treatment
> duration, a few months after stopping treatment. But, with this very
> short follow up, you don\'t see an improvement in fibrosis even in the
> treated patients despite the dramatic drop in inflammatory score. This
> is what Dr. Hoofnagle had pointed out; changes in fibrosis score is
> important but it tends to lag behind. So, if you do biopsies very soon
> after you start the patients on treatment, even if there is an
> improvement, you are unlikely to see it unless you repeat a biopsy
> several years later.
>
> \[Slide.\]
>
> Because of the difficulties in finding good interferon trials for
> e-antigen-negative chronic hepatitis B, I have also shown you some
> slides which review the experience of a single center. Now, this is
> very muddy. This is, perhaps, the largest experience but they really
> report the entire clinical experience of the investigators over a
> ten-year period of time, patients being treated with varying
> durations.
>
> So this is 216 patients followed up for a median of seven years.
> Initially, they though a short duration of treatment would be
> sufficient, like for e-antigen-positive chronic hepatitis B. So the
> first 78 patients had a median of five months of treatment.
> Subsequently, they realized that the patients needed a longer duration
> of treatment and gave the patients a median of twelve months of
> treatment.
>
> Some of these patients initially did not respond or responded and
> relapsed and were retreated. The data is really lumped together. But
> one thing which was consistent was that they used a low dose, 3
> milliunits three times a week for the entire experience.
>
> If you look at response at the end of treatment which was defined as
> normal ALT and hepatitis-B virus DNA dropping to below detection in
> hybridization assay, they saw, in 54 percent of patients. A year after
> stopping treatment, this is post-treatment, they had 24 percent of all
> patients who were able to maintain the response and, at the end of
> follow up, which is a median of seven years from the beginning, 18
> percent of patients continued to maintain the response.
>
> But, again, I have to quality that some of the patients relapses and
> were retreated again in order to have this maintained response.
>
> Predictors of response have been identified for interferon treatment
> of e-antigen-positive chronic hepatitis B and that is really mainly
> pretreatment ALT as well as pretreatment hepatitis-B virus DNA level.
> Predictors of response are far less clear for e-antigen-negative
> chronic hepatitis B, in general, duration of treatment appears to play
> a role. If you treat the patients for less than six months, the chance
> of having a sustained response is lower. If you treat the patients for
> twelve months, the chance is better.
>
> It has also been shown by these investigators that patients respond
> very early, normalize their liver enzymes, drop their DNA. Within the
> first two to three months of treatment, they have a better chance of
> having and end-of-treatment response and a sustained response.
>
> \[Slide.\]
>
> So much for interferon treatment. Let me now move to lamivudine
> treatment. I am going to focus mostly for e-antigen-positive chronic
> hepatitis B on three trials that are very familiar to most of the
> audience; the multicenter Asian trial reported in 1998, the U.S. trial
> reported in 1999 and an international trial reported in 2000.
>
> These two trials compare lamivudine with placebo. They are all
> e-antigen-positive patients with hepatitis B virus DNA detectable by
> the liquid hybridization assay. In the Asian trials, patients with
> normal or elevated ALT can be enrolled. In the U.S. trial, patients
> all had elevated ALT. In the international trial, it is a three-armed
> trial. There was lamivudine alone for a year. There was interferon
> alone for sixteen weeks. And there was combination therapy of
> lamivudine for 24 weeks and interferon therapy for sixteen weeks with
> lamivudine starting eight weeks prior to the start of interferon.
>
> Response was assessed at Week 52. If you look at e-antigen
> seroconversion, and, again, I have to clarify that, in most interferon
> trials, when we talk about e-antigen response, we talk about e-antigen
> loss and HBV DNA dropping to undetectable level using the DNA assay of
> the day. But, with the lamivudine trials, e-antigen seroconversion was
> defined except for the pediatric study as e-antigen loss, detection of
> e-antibody, detection of e-antibody was not specified in most
> interferon trials and hepatitis B virus DNA dropping to undetectable
> level in general using the Abbott liquid hybridization assay.
>
> Here you see that, for the lamivudine group, it is fairly consistent
> across the different studies, 16 to 18 percent of patients with
> e-antigen seroconversion compared to 46 percent in the placebo
> controls. You can also see very nicely in this particular study that
> 52 weeks of lamivudine and sixteen weeks of interferon had almost
> identical response rate in terms of e-seroconversion with higher
> e-seroconversion rates in the group that received combination therapy.
>
> \[Slide.\]
>
> What about histologic response? Histologic response here is defined as
> a decrease in HAI by two points or more with a liver biopsy performed
> at Week 52 which would mean that the patients were still on treatment
> in these two studies and, in this particular study, the lamivudine
> patients were still taking lamivudine at the time of the repeat biopsy
> whereas the group that received interferon alone and the group that
> received combination therapy, they had been off treatment for 28 weeks
> at the time of repeat liver biopsy.
>
> So, here again, in terms of histologic response, it is fairly
> consistent, about 50 to 55 percent of patients have improvement in HAI
> score by at least two points but note that, as Dr. Hoofnagle mentioned
> repeatedly, hepatitis B is a disease in which sometimes you can see
> improvement even in untreated patients. Whether this is a genuine
> improvement or whether this just reflects the up-and-downhill course
> of the disease is not clear, but about 25 percent of placebo patients
> also meet the criteria for histologic response.
>
> Surprisingly, the combination-therapy group, even though there was a
> higher e-seroconversion rate, histologic response was actually less.
> But that may, in part, be related to the timing of the repeat liver
> biopsy because this was performed 28 weeks after stopping treatment
> whereas these folks were still on treatment.
>
> \[Slide.\]
>
> What about normalization of liver enzymes? Again, fairly consistent.
> The treated patients, about 50 to 70 percent have normalization of
> liver enzymes compared to placebo which is much lower. In the
> multicenter studies, there were more patients with normalization of
> liver enzymes on treatment, but this was also true for the placebo
> group.
>
> Again, when you look at the international studies, normalization of
> liver enzymes was fairly comparable across the three treatment arms.
>
> \[Slide.\]
>
> A big problem with lamivudine obviously is drug resistance. So,
> although at one year, the e-seroconversion rate is higher than the
> rate of drug-resistance mutation, this is genotypic resistance. This
> is really looking for the resistant mutation and the patients may or
> may not necessarily have breakthrough infection although the majority
> of them would have.
>
> However, as you prolong the duration of treatment, and this is in the
> multicenter Asian study, to four years, you find that, even though
> continuation of treatment does increase, the e-seroconversion rate,
> but the two lines have crossed and now you actually have more patients
> with genotypic resistance than patients with e-seroconversion. It does
> make you wonder if extending the duration of treatment is beneficial
> to these patients.
>
> \[Slide.\]
>
> What about lamivudine treatment of e-antigen-negative chronic
> hepatitis B? This, again, gets into muddy territories. We don\'t have
> good controlled trials because almost everyone believes that the
> patients won\'t get better on their own. This is really the only real
> controlled trial, or partially controlled trial, because the study is
> designed in such a way that the patients on lamivudine were to receive
> lamivudine for a year.
>
> The patients randomized to placebo would only be on placebo for up to
> 24 weeks and then, unless they go into spontaneous remission, they are
> allowed to go into open-label treatment. So the comparison-group
> analysis can only occur at Week 23. Here, obviously, you see that the
> treated patients did better with about 60 percent of patients
> achieving response defined as hepatitis B virus DNA dropping to
> undetectable level using the branch-DNA assay which has a detection
> limit of about 700,000 copies per ml as well as normal liver enzymes
> compared to about 4 or 5 percent in the placebo group, again showing
> that in the e-antigen-negative chronic hepatitis B patients,
> spontaneous improvement is not common.
>
> As this group of treated patients continues out to Week 52, the
> majority of these patients, about 65 percent, still had maintenance of
> the response and roughly 35 percent actually dropped their DNA level
> to undetectable even using the PRC assay, and about 55 or 60 percent
> of these folks have improvement in histology as defined as decrease in
> HAI by at least two points.
>
> \[Slide.\]
>
> That is the good news. The bad news is if you try to take them off
> treatment after one year, you are going to get 90, 95 percent of the
> patients relapsed. The relapse in many of these cases is really not
> due to selection of drug-resistant mutation but, rather, you haven\'t
> actually controlled the disease well enough so that, if you stop
> treatment, everything is just going to come back.
>
> \[Slide.\]
>
> So this, again, is a slide that I borrowed from Hadziyannis who put
> together a very nice review. This summarizes interferon treatment,
> lamivudine treatment and adefovir treatment for e-antigen-negative
> chronic hepatitis B while the patients are still on treatment and
> sustained response as assessed six to twelve months after stopping
> treatment.
>
> If you look at interferon, short-duration, on-treatment response is in
> the region of 60 to 90 percent, sustained response, 10 to 15 percent.
> If you treat the patients for at least twelve months, on-treatment
> response is about the same. You don\'t have issues of drug resistance
> so whether you treat the patients for six months or twelve months, the
> difference is very small.
>
> But you do get a higher rate of sustained response if you put the
> patients on treatment for a little longer, 20 to 25 percent sustained
> response.
>
> Lamivudine is somewhat different. If you treat the patients for one
> year, at the end of treatment, you get about 70, 80 percent response
> but the response rate actually drops with longer duration of treatment
> because of the issue of drug resistance and the patients initially
> have virologic breakthrough and, ultimately, most of them will develop
> biochemical breakthrough.
>
> If you stop treatment at the end of one year, you get, at most, 10
> percent sustained response and some people even say less than 10
> percent. We don\'t really know what happens if you treat the patients
> for two years and then stop, or three years and then stop, because
> everyone is just terrified. Everyone thinks that you need to put the
> patients in treatment for the rest of his or her life.
>
> I am not sure that that is a wise thing to do. We need to reexamine
> whether, after two or three years, there would be a subset of patients
> in whom, if they fulfill certain criteria, we can consider stopping
> the treatment.
>
> You all have heard the adefovir data with one-year treatment. You get
> about 70 percent rate of on-therapy response and, again, we don\'t
> know anything about sustained response because these patients are, in
> general, left on-treatment.
>
> \[Slide.\]
>
> Let\'s now move on to decompensated cirrhosis. How do we actually
> assess response? This is getting more tricky because just bringing
> down the level of virus may not save a patient\'s life because you are
> now talking about patients who have got end-stage cirrhosis. They may
> have ascites. They may have hepatoencephalopathy. They may already
> have had a couple of episodes of life-threatening variceal bleeding.
>
> Even if you bring the level of virus down from 10^7^ to 10^5^, that is
> still a very small, shrunken liver. So we need to look at more than
> virus suppression. We do want to see biochemical improvement due to
> transaminases coming down. Thus the bilirubin comes down. Thus the
> albumin goes. Thus the prothrombin time or the INL improves.
>
> Unfortunately, you find that, in some patients, these problems just go
> in different directions. Also you may some patients with a very high
> bilirubin level but the albumin is pretty decent, or some with a very
> low albumin level but the bilirubin is only 3. So it is very hard to
> actually take one biochemical parameter and say, okay, we are going to
> use this for monitoring the patients because different patients really
> have worsening of different parameters.
>
> Therefore, it is important perhaps to look at more global parameters,
> a combination of markers. What has been used in many of the clinical
> trials has been the Child-Turcotte-Pugh score. This is the CTP score
> which combines three laboratory parameters and two clinical
> parameters; albumin, bilirubin, prothrombin time, ascites and
> hepatoencephalopathy.
>
> This has a lot of advantages because it allows us to look at
> biochemical improvement and clinical improvement. We are looking at
> not just one facet but trying to be generalized. There are, however,
> disadvantages with the CTP score because your score of ascites and
> encephalopathy is very subjective.
>
> I can say that the patient has mild ascites. But a different
> investigator would say that the patient has got moderate ascites. Some
> patients appear to be a little bit mentally sluggish when I see them
> in clinic because they drove three hours to my clinic and they had to
> get up at 4:00 in the morning, so I thought that they were
> encephalopathic. But maybe they are not truly encephalopathic. So
> these can be subjective.
>
> There are also problems with the laboratory parameters which are
> supposed to be objective because the CTP score assigns a numerical
> score based on the range of log values. So, for example, a bilirubin
> of 3 and a bilirubin of 30 has the same score in the CTP scale.
> Clearly, someone with a bilirubin of 30 is a lot sicker than someone
> with a bilirubin of 3.
>
> That is the reason why recently, in the transplant community, we have
> switched from the CTP scoring system to the MELD scoring system which
> allows a continuous range of log values. Whether that is better or not
> remains to be determined.
>
> One can also assess these patients by looking at clinical
> complications, whether we can prevent development of ascites or
> whether we can make the ascites go away so that the patient can stop
> taking diuretics and ascites won\'t come back. We can look at
> decreased need for transplantation, decrease in hepatocellular
> carcinoma. And we can look at improvement in survival.
>
> What have we learned so far? Of the studies that have been reported,
> we can see that lamivudine can bring about viral suppression, can
> bring about biochemical improvement, can bring about improvement in
> the CTP score. There are some studies that suggest that you can
> actually reduce clinical complications and there are some studies that
> suggest that you may obviate the need for transplant although I would
> argue against that.
>
> I think that, in most of these patients, you are delaying the need for
> transplant. I am not so sure that we actually decrease the need for
> transplant.
>
> It seems that we are not doing much good here so far because there are
> still patients on treatment that have been reported to have developed
> hepatocellular carcinoma and it is hard to actually know whether you
> improve survival or not because this is not the type of clinical
> situation where we can do a randomized controlled trial.
>
> I am going to just talk about lamivudine and not about interferon
> because none of us are really going to use interferon in patients who
> decompensate to cirrhosis because of the side effects.
>
> \[Slide.\]
>
> I am only going to show one study because there are many studies, none
> of them are perfect, and it is impossible to do perfect studies in
> patients who are that sick. But this is a study from Canada. It
> involves some several centers. They looked at 35 patients who
> decompensate to cirrhosis.
>
> You notice that\--and this is a common observation \--some of these
> patients are so sick that, unless God is around and can turn on the
> switch, there is no magical treatment. Therefore, within the first few
> months, they had five deaths in seven patients who went on to
> transplant. But, for those patients who were able to take treatment
> for at least six months, and there were 23 of them, 22 out of these 22
> patients had improvement in liver disease as defined by decrease in
> the CTP score by at least some two points. Only one patient had no
> improvement and went on to transplant.
>
> So, the moral of the lesson is, some patients come to you and they are
> way too sick, they have already crossed the line and there is no magic
> treatment that would work fast enough to save those patients. However,
> if you are able to catch the patients before they have reached the
> point of no return and are put on treatment, you can stabilize the
> disease. You drop the virus level. You can stabilize the disease and
> they can do better.
>
> That is better for some time but is it really a cure? Is it really
> these patients getting out of the woods? That is where you start
> seeing problems because, even though these 22 patients had decrease in
> CTP score by at least two points, two patients subsequently died, one
> from spontaneous bacterial peritonitis which often is a complication
> of end-stage liver disease and one patient developed hepatocellular
> carcinoma.
>
> So the fact that the patient is maintained on treatment and appears to
> be doing better does not necessarily mean that these complications
> will never occur. So, while some investigators are very gung-ho and
> think that they can take their patients off the transplant waiting
> list, I think is really\--a more appropriate thing to do is probably
> to put the patients on hold.
>
> What about these 20 patients who have not developed any problems? At
> the time of the reporting, 20 patients were still alive. They are
> about a year and a half from the start of treatment. It is hard to
> know whether the treatment improved the survival because there was no
> control group, but three patients had developed resistant mutations.
>
> There is a lot of debate as to what happens if these patients were to
> go to transplant. There have been case reports that these patients can
> be transplanted without evidence of recurrence if you give them
> adequate prophylaxis with hepatitis-B immunoglobulin and lamivudine.
> But there are also several reports from Europe showing 100 percent
> recurrence rate in the absence of other drugs that can suppress the
> lamivudine-resistant mutations.
>
> \[Slide.\]
>
> Let me now move on to what we do in practice. The issues are who to
> treat, what treatment and when to stop treatment.
>
> \[Slide.\]
>
> I am going to sort of borrow some of these things from the AASLD
> Practice Guidelines and this, in turn, was borrowed from some of the
> conclusions that we made at the NIH workshop two years ago.
>
> Essentially, we said that it is very clear that current therapy for
> hepatitis B works short-term but has very limited long-term efficacy.
> It is still very worrisome if we have to put patients on treatment
> forever and ever when you have a twenty-two-year old patient or, worse
> still, when you have a child.
>
> It is very important that we think very carefully before we start the
> patients on treatment, particularly if we don\'t know when to stop. We
> must balance the benefits and the risks before we start the treatment.
> The factors that we need to consider are, really, how old is the
> patient, how bad is the liver disease, what is the likelihood of the
> patient\'s responding to treatment and what are the potential side
> effects.
>
> \[Slide.\]
>
> This is what we recommended. This is really based on just interferon
> and lamivudine data. Clearly, as new therapeutic agents become
> available, these guidelines need to be reassessed. But what we said
> was if we have someone who is e-antigen-positive with high levels of
> DNA but the liver enzymes are normal or minimally elevated, at the
> moment, we are going to just observe these patients.
>
> It is not that we are not worried about these patients. It is we
> don\'t have effective treatment for them. None of the treatments, be
> it interferon, be it lamivudine, is effective in these patients with
> high levels of virus but normal liver enzymes. Therefore, we choose to
> observe them.
>
> For people who are e-antigen-positive, high levels of DNA, with
> elevated liver enzymes, we can consider using interferon, we can
> consider using lamivudine, because it appears that sixteen weeks of
> interferon has similar efficacy to lamivudine and it is really the
> patient\'s choice or the physician\'s choice.
>
> Clearly, patients who are interferon nonresponders, they do respond to
> lamivudine and they can be considered for lamivudine therapy. Patients
> with contraindications can use interferon, which does happen quite
> often if the patient has underlying autoimmune disease. If the patient
> has some significant depressive illness, they are good candidates for
> interferon therapy and they should be considered for lamivudine.
>
> For e-antigen-negative patients who have high levels of DNA, elevated
> liver enzymes, again, they can receive interferon therapy or
> lamivudine treatment. With both treatments, longer-term therapy is
> required but we don\'t really know what longer-term means. Is it two
> years? Is it three years? Is it truly for life?
>
> For the patients who are e-antigen-negative with very low levels of
> DNA, this is not actually negative DNA but negative using assays with
> a detection limit of 100,000 copies and normal liver enzymes. At the
> moment, we don\'t recommend treatment because we don\'t believe that
> there is any treatment out there that is going to make the situation
> any better. So why take a treatment that is not going to make you any
> better.
>
> For patients who have already developed cirrhosis, if the levels of
> virus are high and they are very well compensated\--when I say
> compensated, I mean you don\'t know that a patient has cirrhosis until
> you do the biopsy\--these patients can sometimes still be considered
> for interferon therapy.
>
> Some of the early interferon trials did include a bunch of patients
> with histological cirrhosis but you didn\'t know that they had
> cirrhosis until the biopsy reports comes back. Certainly, you can
> consider lamivudine. But, by the time the patients have decompensated,
> interferon is not an option. Lamivudine would be the treatment. Of
> course, as we know, alternative treatment, we would have to reconsider
> these options.
>
> The biggest problem in the decompensated patients is when do we start
> treatment? Ideally, you want to start treatment early so that you have
> a chance to improve the patient\'s clinical condition, give them a
> chance to get on a transplant waiting list. If they don\'t need a
> transplant, maybe the transplant can be deferred for five years. If
> they need a transplant, you give them time to wait for the transplant.
>
> However, there is also the argument that if you put patients on
> treatment too early and now they develop resistance, and now they
> decompensate and an organ is not available, or now you bring the virus
> level up ten-fold higher and they develop recurrence transplant, that
> is not a very good option.
>
> But, again, with availability of other drugs, we have to rethink all
> these and maybe starting patients on treatment early might be an
> option that we should consider. Certainly, these decompensated
> patients ought to be put on a transplant list.
>
> \[Slide.\]
>
> I keep giving people options because I do think that, in terms of
> efficacy, pure efficacy, the two drugs are fairly comparable, both for
> e-antigen-positive chronic hepatitis and for e-antigen-negative
> chronic hepatitis. But there are other considerations.
>
> One of the advantages of interferon is that one can consider a more
> finite, more limited, duration of therapy. It seems that, for the
> e-antigen-positive patients and, perhaps also, for e-antigen-negative
> patients, you have a better likelihood of getting a durable response.
>
> In most of the e-antigen-positive studies, as we follow the responders
> out to eight to ten years, we find that there is an 85 percent
> durability. With lamivudine treatment, it appears that durability is
> lower. There is no issue, no concern, about resistant mutants.
>
> Most patients don\'t like parenteral medications and most patients
> walk away as long as soon as they hear the long list of side effects
> of interferon therapy. So the course as well as the side effects sway
> patients as well as some physicians away from using interferon
> therapy.
>
> Lamivudine is convenient. It is orally administered, negligible side
> effects. Certainly one year of lamivudine is far cheaper than sixteen
> weeks of interferon but, if you put patients on treatment for five
> years, it all adds up eventually. So I am not so sure that it is less
> expensive.
>
> The biggest concern is no one knows when to take the patients off
> treatment. This is really not a good thing. When you put patients on
> and you just keep saying to them, \"Well, I don\'t know. I don\'t
> know. Let\'s wait and see and think about it again six months from
> now.\"
>
> Perhaps a more important issue is the resistant mutants, a regimen, we
> have been told, \"Well, don\'t worry. The resistant mutant has
> diminished replication fitness and maybe it is not going to be a big
> deal.\" But, as we follow more and more of these patients out, we do
> see some patients in whom the virus level keeps creeping up. The
> disease comes back and, from time to time, we hear of patients acutely
> decompensating and we do hear of patients dying.
>
> Again, as we get other alternative treatment that we can offer these
> patients, hopefully, we don\'t hear about those sad stories anymore.
> But this continues to be a concern.
>
> \[Slide.\]
>
> These are the doses that we recommended for interferon therapy. The
> interesting thing with interferon therapy is that there wasn\'t really
> good dose-response studies. Doses were picked from a hat. I remember
> twenty years ago when I was a fellow, I used some 50 million units
> I.V. infusion and I, as a fellow, was asked to stand by the patient\'s
> bed to make sure that the shaking and rigor wouldn\'t throw the
> patient off the bed and that the patient wouldn\'t become very
> hypotensive.
>
> We have come a long way. We have scaled down. But whether these are
> really the appropriate doses, we don\'t know for sure. For e-positive
> patients we recommend sixteen weeks. There is some data to suggest
> that, in a subset of patients, a longer duration of therapy might be
> of benefit. Patients how haven\'t quite responded at sixteen weeks
> might benefit if you continue to 24, 32 weeks. But we don\'t really
> have a lot of data.
>
> For e-negative patients, we think that perhaps at least twelve months,
> maybe longer, but, again, it is a lot of maybes, a lot of question
> marks.
>
> \[Slide.\]
>
> With interferon, there are, again, a lot of question marks. We know
> the dose\--and, actually, I am not sure. I don\'t even know the
> dose\--because the dose-response curve were really based on using the
> Abbott liquid hybridization assay, a fairly bad HBV DNA assay and, had
> a better HBV DNA assay been used, whether we would have picked 100
> milligram or whether we might have ended up picking a higher dose
> because we would be able to see that a higher dose actually brings a
> further drop in viral load, I don\'t know for sure.
>
> With patients with HIV coinfection, we do recommend a higher dose and,
> in conjunction with other HIV treatment.
>
> The biggest problem with lamivudine treatment is we don\'t know what
> is the duration of treatment. For the e-positive chronic hepatitis B
> patient, we say, well, at least one year and, at the end of one year,
> we are going to think. If the patient has developed e-seroconversion,
> you should certainly consider stopping treatment.
>
> But do you stop treatment the moment has e-seroconversion? Probably
> not because increasing data suggests that, if you do so, the patient
> is going to relapse very quickly. So we believe that we need to
> maintain the patients on treatment for a little longer before we stop
> treatment. But what is a little longer? Is a little longer three
> months? Is a little longer six months? Is a little longer twelve
> months?
>
> Those are questions that we don\'t know. But what is more of a problem
> would be these patients whose DNA continues to be at low level but
> they are still e-antigen-positive. Remember only about 16, 17 percent
> of patients will have e-seroconversion at the end of one year. So the
> majority of the patients are going to be here, or here.
>
> What do we do? The data from the multicenter Asian studies would
> suggest that if you leave the patient on treatment for a second year
> and a third year and a fourth year, some of these patients are going
> to e-seroconvert subsequently but you also run the risk of these
> patients developing resistance with longer duration of treatment. So,
> is it a wise thing for us to leave the patients on continued treatment
> or should be stop if they haven\'t e-seroconverted at the end of one
> year?
>
> What about patients with break-through infection? At the time when we
> wrote these guidelines, adefovir was still investigational. So we
> said, well, continue treatment if the patients remain clinically
> stable, if their current ALT and DNA levels are lower than
> pretreatment because we were worried that, if we stopped the treatment
> and the wild-type virus comes back, the disease will be worse.
>
> We recommend stopping treatment only if the patients clinically
> deteriorate. If the patients are worse off than before treatment,
> there is no point in leaving the patients on that treatment. But,
> again, the recommendations will change as we have other alternatives
> available to us.
>
> With the e-negative chronic hepatitis B patients, we know that the
> patients need longer than one year of duration of treatment. But how
> much longer? That is the question that we don\'t know.
>
> \[Slide.\]
>
> Let me now move on and wrap up by talking about some issues for future
> clinical trials. We need to talk about study population, entry
> criteria, treatment regimens, indications for assessing treatment
> response, endpoints, durability of response and short- and long-term
> safety and efficacy.
>
> \[Slide.\]
>
> We have mentioned that, with the study population, we should consider
> these different groups separately. The e-positive chronic hepatitis B,
> the e-negative chronic hepatitis B, the decompensated cirrhosis. So
> far, most of the studies have forgotten about these other groups. The
> patients with coinfection, the patients with extrahepatic diseases,
> the patients on immunosuppressive or chemotherapy. Some of the trials
> have involved children.
>
> \[Slide.\]
>
> What about entry criteria? For the e-positive patients\--well,
> actually, for both groups\--we have to consider viral load, liver
> enzymes and liver histology. For the e-positive patients, the majority
> of them have viral loads from 10^5^ to 10^10^. So an entry criteria of
> 10^5^ or 10^6^ sounds reasonable.
>
> For the e-negative patients it is less clear because these patients
> tend to run fluctuating viral levels and a lot of these patients do
> run lower viral levels. So we lower the entry criteria such that we
> take patients in with 10^4^ to 10^5^ or do we need to insist on higher
> levels. What about liver-enzyme levels? Because pretreatment ALT is a
> very predictor of response, patients with normal ALT or minimally
> elevated ALT tend not to respond.
>
> So we tend to recommend a pretreatment ALT of two times the upper
> limit of normal. The Asian Pacific Guidelines actually recommend going
> up to five times the upper limit of normal as the entry criteria for
> starting patients on treatment. Again, for e-negative patients, we
> only treat patients with disease, not the inactive carriers. But what
> is the cutoff that we use?
>
> Do we need to insist on having histology as an entry point for
> starting patients on treatment? This seems to be still important for
> clinical trials but what about in clinical practice and if we want to
> have a liver biopsy, how much liver disease, in terms of inflammation
> and fibrosis, should we use as an entry criteria?
>
> \[Slide.\]
>
> What about the treatment regimens? Should we still be looking at
> monotherapy or should we really be moving from the stage of
> monotherapy to look at monotherapy versus combination therapy? Should
> we be using placebo controls or, in view of the availability of so
> many different drugs, be thinking of active controls?
> Placebo-controlled trials have their advantages, but we also need to
> look at feasibility. What is the likelihood of enrolling a patient
> into a study in which there is placebo when there are so many other
> treatments available.
>
> What about the duration of treatment? Should we be looking at finite
> duration, treatment of one year or two years, or should we actually
> mandate that there is built-in follow up and follow on so that we can
> address the issues of durability of response, long-term safety, drug
> resistance and what are the additional responses if we extend
> treatment.
>
> These need to be planned ahead of time so that there are not gaps
> between the licensing studies and the subsequent studies because, once
> you have gaps in between, all the data become messy and muddled.
>
> \[Slide.\]
>
> What about endpoints? So far, many of the antiviral trials in
> hepatitis B have focused on histology as an endpoint, in particular
> using a decrease in HAI by two or more points. There are advantages of
> using histology because this is a direct assessment of liver disease.
> This is to look at inflammation which is more dynamic and fibrosis
> which is, perhaps, a more long-lasting effect.
>
> But there are disadvantages with looking at histology. I requires two
> biopsies. Liver biopsy is not a fun thing for the patient. It is not a
> fun thing for the physician either because there is risk of
> complication, it is an expensive test, there are problems of sampling
> error, inter- and intra-observer variability.
>
> The scores are not linear. Even when the score is 1, 2, 3, 4, 5 and 6,
> the increment from 1 to 2 versus the increment from 2 to 3 is not,
> necessarily, the same in terms of increment in inflammation, increment
> in fibrosis. These are all very subjective.
>
> Certainly, histology does not apply outside of clinical trials and, as
> Dr. Hoofnagle mentioned, we don\'t know what it means if someone drops
> their HAI by two points, particularly if this occurs only when a
> patient is still on treatment.
>
> \[Slide.\]
>
> What, then, are the alternatives that we can think of? For the
> e-antigen-positive patients, I propose that we should seriously
> consider\--I am not saying that this is definitive, but I would throw
> this out for discussion\--that we should look at e-antigen loss. I am
> still not sure whether we need to insist on detection of e-antibody
> and whether this means a more durable response or not.
>
> We want a substantial decrease in HBV DNA level, probably to less than
> 100,000 copies because studies in the 1980s show that if we drop the
> DNA level to undetectable by hybridization assays, many of these
> patients do have improvement in the liver disease and we do want to
> see normalization of liver enzymes.
>
> For the e-negative chronic hepatitis B patients, we want to have a
> drop, a substantial drop, in DNA level. Here I am not so sure where we
> want it to be dropped down to. These patients start at a lower level.
> I believe that these patients need to be dropped at lower levels than
> the e-positive patients. Many of us think that it should be dropped
> down to less than 1,000. Some people think that we should drop it to
> below detection by PCR and I throw it out for discussion.
>
> We also want to see normalization of liver enzymes. For the patients
> with decompensated cirrhosis, we also want a drop in viral load. We
> want to see improvement in biochemistry and clinical outcome so we
> want to see improvement in CTP score and, perhaps now that the
> transplant community has moved to using the MELD score, which is a
> combination of INR, bilirubin and creatinine, we may want to use this
> as an endpoint as well.
>
> \[Slide.\]
>
> So the question is if we use as endpoints, do they correlate with
> histology? Do they correlate with improvement in clinical outcome?
>
> \[Slide.\]
>
> There is very limited data because of the prolonged natural course.
> Most prospective studies have limited follow up. I am going to lose my
> job if I tell my boss that I publish a paper every twenty years. There
> are very few randomized controlled trials and many of them have small
> sample size.
>
> So a lot of times, people use retrospective studies, use historical
> controls, nonconcurrent controls. But then you run into the risk of
> disease heterogeneity. You are comparing apples and oranges.
>
> \[Slide.\]
>
> Let\'s now review a few studies to see if there is some data out
> there. This is Perillo\'s study of interferon therapy of
> e-antigen-positive chronic hepatitis B that I showed you earlier. He
> looked at treated patients that had paired biopsies. The repeat liver
> biopsy was done six months after stopping treatment.
>
> In the treated patients who had a response, you see a dramatic
> reduction in HAI score, about two points, with rank assessment
> improvement outweighing deterioration. In patients with no response,
> you don\'t see much in the way of improvement and, on balance, it is
> about the same.
>
> On treated controls, not much in the way of improvement. So the
> virological endpoints do correlate with histological improvement if
> you look at it in that way.
>
> \[Slide.\]
>
> What about clinical outcome? Here is a study from the German group
> where they included interferon-treated patients and untreated
> controls. Here, unfortunately, some of the untreated controls were
> nonconcurrent controls. They included controls from previous clinical
> trials as well as nonconcurrent controls. But what you do see is that,
> in the treated patients, if they clear e-antigen, they did much better
> than the patients who remained e-antigen-positive in terms of
> proportion with complication-free survival.
>
> These are patients with survival without liver decompensation. This is
> also true for untreated patients indicating that clearance of
> e-antigen is a good thing if this is associated with viral suppression
> as well.
>
> \[Slide.\]
>
> What about e-negative chronic hepatitis B patients? There is some data
> from Hadziyannis\' group again that overall you don\'t see as dramatic
> improvement but, in the interferon-treated patients with sustained
> response, there was also improvement in transplant-free survival
> compared to the patients who were treated and did not respond or the
> patients who were not treated.
>
> Again, this is not randomized controlled trials. These are really
> lumping patients who got treated versus those who didn\'t get treated.
>
> \[Slide.\]
>
> What about lamivudine, then? This is a complicated slide and this is
> some data that Lynn Combray and Steve Gardner provided. This really
> combines the U.S. e-positive study and the multicenter Asian study.
> The orange represents the placebo, the yellow represents the
> lamivudine-treated patients.
>
> The shaded part represents the patients with e-seroconversion. This is
> looking at Week 52 DNA levels and e-seroconversion. As you would
> imagine, the treated patients, the DNA levels shifted to lower levels.
> In the initial published report, they used the liquid hybridization
> assay and this is really reanalysis of some of the patients using the
> PCR assay.
>
> So the DNA level shifted with the treated patients and you find that
> there is a reasonable correlation between the viral load at Week 52
> and e-seroconversion in the sense that most of the patients with
> e-seroconversion had HBV DNA level dropped down to below 10^3^.
>
> Then you get some e-seroconversion with viral load of 10^3^ to 10^5^,
> but very few when the viral load is above 10^5^.
>
> \[Slide.\]
>
> What about correlation between viral load and ALT normalization.
> Again, orange is placebo, yellow is lamivudine and the shaded bars are
> the patients with normal liver enzymes. Here, you find that you can
> normalize liver enzymes even with higher viral levels. With
> e-seroconversion, you need to drop the viral load to about 10^3^ but
> if you drop the viral load to about 10^6^, the majority of these
> patients will have normalized liver enzymes.
>
> You also get normalized liver enzymes in some of these patients
> amazingly with viral levels of 10^8^ and 10^9^. But, obviously, many
> of these patients have elevated liver enzymes.
>
> \[Slide.\]
>
> What about histology. Once you get into histology, it gets a little
> bit more complicated. I think, in part, it is because of the way we
> define histologic response. At low viral levels, the majority of these
> patients have improvement in histology. Certainly, when the viral
> level is below 10^4^, almost everyone had improvement in histology.
> Between 10^4^ to 10^6^, you still get the majority, more than
> 50 percent, with improvement in histology, less improvement in
> histology with higher viral levels but, surprisingly, a fair number
> have improvement in histology again even at viral levels of 10^8^ and
> 10^9^ which makes us wonder what this all means.
>
> \[Slide.\]
>
> Finishing up with two slides that John Fry and Carol Brosgart shared
> some of the data in the adefovir studies. This slide shows the
> e-positive chronic hepatitis B patients, adefovir Trial 437. These are
> all the patients on adefovir 10 milligram.
>
> If we look at a composite endpoint with e-seroconversion and with
> decreasing viral level and with normalized liver enzyme, do we
> actually get improvement in histology? The first thing you see is the
> patients with e-seroconversion compared to the patients who didn\'t
> have e-seroconversion, the viral load shifted to the left side. So
> they tend to have much lower viral levels and almost every one of them
> had HBV DNA levels of less than 10^4^.
>
> ALT normalization represents the orange bar so the majority of the
> patients with e-seroconversion also had normalized liver enzyme and
> almost every one of them had the shaded bar which means that they also
> have improvement in histology.
>
> But, if you look at the patients without e-seroconversion, some of
> them also had low viral levels but didn\'t seroconvert. Some of them
> even have normal liver enzymes but still didn\'t serconvert. Some of
> them even have normal improvement in histology.
>
> So, again, regardless of e-seroconversion, if the viral level is low
> and the person has normalized liver enzymes, a lot of them also had
> improvement in histology. But, again, the amazing thing is if the
> viral level is high and, even in patients whose ALT remains elevated,
> you also see a fair number of them with improvement in histology. So,
> again, what does this mean?
>
> Is it a problem, all these virological and biochemical endpoints or is
> it a problem with the way we interpret liver histology?
>
> \[Slide.\]
>
> This is the e-negative chronic hepatitis B study, adefovir patients,
> placebo patients, patients on treatment, viral load shifted to the
> left side, lower levels, compared to the untreated patients. Again, if
> you have low viral load, most of these patients have normalized liver
> enzyme, the orange bar, and most of them have the shaded bars with
> improvement in histology.
>
> But, even in the placebo patients, even in those of elevated ALT, you
> also have improvement in histology and, again, you tend to see
> improvement in histology spread all the way and it doesn\'t correlate
> as well. So it raised, really, a lot of questions as to what the
> histology response means.
>
> \[Slide.\]
>
> This is my last slide. One of the things that we really need to
> address is not just the primary endpoint which then allows FDA to
> decide whether a drug is approved, but in clinical practice, it is
> also when do we stop treatment? The primary endpoint for a clinical
> trial is one thing, but we have learned that it may not necessarily
> mean that this is an indication for stopping treatment.
>
> This is something that we all need to understand because, in practice,
> we have to be able to advise physicians how long to treat the
> patients, what do you need to see in order to stop treatment.
> Obviously, we want to see that they achieve on treatment response or
> the primary efficacy endpoint.
>
> We need to see that, but it seems that these patients also need to
> have the ability to maintain these responses for a certain duration of
> time while they are still on treatment before you can take them off
> treatment. The indications for stopping treatment may vary depending
> on the severity of the underlying liver disease and the immune status
> of the host. By that, I mean that, in a patient who started off with
> decompensated cirrhosis, even if they achieve some of these endpoints,
> you might still not have the courage of stopping the treatment and
> running the risk of relapsing.
>
> For patients who require long-term immunosuppression, for example, a
> renal transplantation who requires lifelong immunosuppressive therapy,
> even if everything looks good, is it safe to stop the patient\'s
> treatment? These are all questions that we need to deal with.
>
> Thank you.
>
> DR. GULICK: Thanks, Dr. Lok.
>
> Are there one or two quick questions from the panel? Dr. Wood?
>
> DR. WOOD: I had a question regarding the decompensated patients with
> cirrhosis. What would you consider a significant magnitude drop in
> terms of the HBV DNA levels as far as an endpoint response in that
> specific patient population?
>
> DR. LOK: I think, what that specific population, the degree of viral
> drop is, perhaps, not as important as looking at biochemical and
> clinical endpoints because many patients with decompensated cirrhosis
> have fairly burned-out disease. Even if they have what we call high
> viral load, seldom do we see it 10^9^, 10^6^. We might see it at
> 10^6^, 10^7^. So, to actually expect a hundred-fold or a thousand-fold
> drop might now realistic and it may not be necessary because, perhaps,
> a tenfold drop is sufficient to bring about some clinical improvement.
>
> I really think that biochemical and clinical parameters might be more
> important in those settings.
>
> DR. GULICK: Dr. Wong?
>
> DR. WONG: I guess my question also concerns the decompensated liver
> patients. Both yesterday and today, we have seen presentations where
> there seem to be clinical improvement but there was no comparator
> group. How should these sorts of data be interpreted? How much
> improvement does one have to see and what should be the proper control
> group even if it is historical controls? What are the criteria that
> should be used for deciding that something really worked in the
> clinical sense or the biochemical sense rather than the virological
> sense?
>
> DR. LOK: Controlled trials are never going to be possible if you have
> a patient who is sitting in front of you with the risk of dying within
> three months and you say, \"I am going to randomize you to placebo.\"
> So that is impossible to do.
>
> We can use historical controls. Unfortunately, this is not a disease
> for which we have really very good data. Or you can actually use the
> patients themselves as some controls if you have data on the patient.
> By the time patients come to you with decompensated liver disease, in
> general, we don\'t see a spontaneous improvement unless they have
> recently had a flare and, for some reason, you are able to turn off
> the flare.
>
> So, for example, if a patient comes to you with a bilirubin of 15 and
> now drops to 3, you have to say that whatever I put the patient on, it
> is doing its job and this is not just the act of God. Likewise, if a
> patient develops ascites and had required huge amounts of diuretics,
> multiple paracentesis and, six months later, you find that the patient
> can be off diuretics with no ascites, this has to be a clinical
> improvement.
>
> Therefore, I think that we are probably going to sort end up trying to
> define how much improvement in bilirubin is an improvement, how much
> improvement in pro-time, how much improvement in albumin and how much
> improvement in some of these aggregate scores, whether we use the CPT
> score or the MELD score, is considered to be clinically relevant.
>
> Again, this is an issue that is going to be complicated because you
> can\'t say, well, a drop in the bilirubin by 2 milligrams per
> deciliter is important because, if you drop from 4 to 2, it is,
> perhaps, important but if you drop from 15 to 13, it is not.
>
> So these are really tricky issues. But I think, ultimately, it is
> sitting down and figuring out do we use a percentage drop or do we use
> a percentage drop and dropping below a certain level because, for
> example, you can say, a 50 percent drop in bilirubin, and it should be
> less than 3. That is perhaps an improvement.
>
> Other than that, I am not sure. Mortality is very hard because, when
> you have the way out of transplanting the patients. So you are not
> allowing your patients to die. You are going to get your patients
> transplanted. Using transplant as an endpoint also is tricky because,
> across the country, and certainly across different countries, the
> availability of transplant varies.
>
> In some states, the patients need to wait for a little longer than in
> another state. So it isn\'t necessarily true that, if your patient
> waited six months versus waited nine months, that this is always a
> reflection of the clinical severity of liver disease. Sometimes, it is
> a reflection of organs being available versus not being available.
>
> DR. GULICK: Thanks again, Dr. Lok.
>
> We will take a break now and we will reconvene at ten minutes of
> 11:00.
>
> \[Break.\]
>
> DR. GULICK: Our next speaker is Dr. Nathaniel Brown from Idenix
> Pharmaceuticals to give a pharmaceutical perspective on development
> issues for hepatitis B.
>
> **Pharmaceutical Development Issues for Hepatitis B**
>
> DR. BROWN: I thank the FDA organizers for inviting me here today.
>
> \[Slide.\]
>
> As Dr. Murray indicated in his overview comment, part of my talk will
> be on an effort to present a perspective of what many of the companies
> in industry working in hepatitis B consider to be the most important
> issues for discussion and potential resolution today so that we can go
> forward with progress in this therapeutic field.
>
> But, as was implicit also in Jeff\'s comment, the first part of my
> talk will really be a personal perspective based on eleven years of
> developing hepatitis-B drugs. I think, when the organizers called, I
> woke up and realized I had actually worked on four nucleosides and one
> interferon project over the last eleven years.
>
> I think my wife tells me to stop worrying about hepatitis B, at least
> on the weekend.
>
> The other thing that I have noticed at scientific meetings is it has
> become popular to replace the opening humor with disclaimers. So I
> think I will try that. I think both my current and past company would
> want you to know that my perspectives today are largely personal and
> do not represent the views of either Glaxo or Idenix.
>
> With that, let\'s start out. I think you will find there are some
> common themes in my talk that play off of things you have heard from
> Jay and Anna and, hopefully, share a lot of experience using these
> kinds of endpoints in clinical trials.
>
> \[Slide.\]
>
> What I am going to talk about today in the first part are some
> personal reflections and perspectives based upon working in this area
> for about eleven years trying to develop new drugs for hepatitis B.
>
> Toward the end, I will present an industry perspective\--I guess this
> is the one place I forgot to change the word \"consensus\"\--but a
> perspective among a number of people working at companies. That will
> be clearly identified at the end so, up to that point, these are
> personal perspectives.
>
> \[Slide.\]
>
> I thought it might be worthwhile\--the point was made yesterday, it is
> very important to learn from the HIV experience. Personally, I think
> it is also important to keep in mind some of the important disease
> differences which are not always highlighted in the race toward
> combination therapy.
>
> So let me try that. First, I think, as probably Jay alluded to early
> on, while, in HIV infection, there is really one end-stage pathway
> which is essentially protein-immune failure due to loss of depletion
> of the CD4 compartment. In hepatitis B, there are two ways patients
> can die and I think we are aware of both of those; liver failure
> related to cirrhosis and, of course, hepatocellular carcinoma.
>
> These may have a common pathway early on with regard to the
> necroinflammatory liver disease acting as kind of a promoting
> environment for tumor formation. I think that was highlighted in the
> New England Journal editorial a couple of weeks ago by Jake Liang and
> Mark Gainey. But I think the implication for this group is we need to
> understand that a lot of clinical trials so far have been founded more
> on the predicate of knocking down the liver inflammation and hopefully
> preventing end-stage cirrhosis.
>
> We don\'t yet really know whether we are going to have an impact on
> HCC. It is a fair guess that if the necroinflammatory response and the
> neoregenerative response in the liver is important in HCC genesis,
> that, if we treat patients early, we might be able to have an effect
> on HCC. But if we treat patients in their 40s and 50s when there may
> have already been malignant transformation, then I think experience
> suggests that we will have successes with regard to necroinflammatory
> responses and failures with regard to patients dying of HCC. So I
> think we need to keep that in mind.
>
> Probably the two strongest arguments for early treatment, I believe,
> are that argument that maybe, early on, just knocking down
> necroinflammatory response, if we have any chance on HCC, it may be at
> that stage of tumor development. Then the second one may be to prevent
> advanced fibrosis and cirrhosis.
>
> Another important disease difference which has been highlighted by
> both clinical speakers so far is that this infection can spontaneously
> revert to low replicative states, typically galdeans and anesians, in
> seroconversion. This can happen, as previous speakers mentioned,
> spontaneously or with therapy.
>
> So, as you already know, the therapeutic goal becomes, in e-positive
> patients, to try to induce this state before the patient is already
> cirrhotic. I think there are smidgens of data that say that
> e-seroconversion, when the patient has advanced disease, may actually
> be dangerous and can knock out the last few hepatocytes.
>
> But this leads to a very important observation that has been discussed
> today. A very important goal in trials is to look at the issue of can
> we stop patients on therapy. The answer in e-positive patients, as
> Anna and Jay well highlighted, e-seroconversion or e-clearance, e-loss
> with DNA suppression, that does appear. We are getting toward an
> appreciation of when patients can be stopped in e-positive disease and
> simply followed.
>
> It is important to emphasize that patients who are stopped still need
> close observation because they are still s-positive and they can
> potentially reactivate.
>
> Another important point that was covered was HBV infection is quite a
> bit slower than HIV to cause irreversible damage to the target organ,
> perhaps ten to fifty years for hepatitis B compared to about five to
> twenty for HIV.
>
> \[Slide.\]
>
> There are some important biologic reasons for why the disease is
> slower to irreversibly damage the target organ. These are partly
> related to the virology. Hepatocytes are not known to be a life-long
> cell type. There appears to be neoregenerative activity in the liver
> almost continuously.
>
> The life span of uninfected hepatocytes is poorly established but it
> may be as short as months. The life span of infected hepatocytes is
> even shorter than that. It may go down to days. So the primary target
> cells for hepatitis B are turning over at variable rates. That is one
> important concept.
>
> Whereas, with HIV or herpes viruses, which this group has a lot of
> previous experience with, the primary cell types, the primary targets,
> may be long-lived cell types, n the case of herpes viruses, for
> example, neurons or memory CD4 cells and other long-term cell types.
>
> Another key virologic difference is that the replication templates for
> hepatitis B are maintained by a continuing level of polymerase
> activity in the so-called intracellular conversion pathway and not by
> cellular alpha polymerases whereas, with herpes viruses and HIV, once
> that double-stranded DNA integren or episome has been formed, those
> have maintained by cellular polymerases and, in those cases, in the
> long-term cell types.
>
> So it is hard to get rid of viral templates in herpes virus and HIV
> infections, but in HBV, they are continually turning over and you can
> get a net reduction when you the infected hepatocytes die.
>
> So what that means, I think, biologically and clinically, and it does
> influence my thinking about hepatitis-B trials, is that treatment of
> chronic hepatitis B infection can be more realistically associated
> with long-term template reduction compared to HIV and herpes viruses.
> But it may take a very long time and the current treatments are
> probably not adequate to eradicate infection.
>
> But there is a theoretic chance for virologic cure. These
> considerations also add up to the concept that HBV is less likely to
> be associated with early resistance and I think the lesson with
> lamivudine is a perfect example there, polymerases are ten-fold better
> fidelity for the HBV polymerase compared to the HIV reverse
> transcriptase.
>
> Sure enough; with hepatitis B with lamivudine the medial time to
> detectable YMDD mutants is on the order of three years whereas, in
> HIV, it is on the order of three months, almost parallel to that
> ten-fold difference in polymerase fidelity. So I think, to my mind,
> these are important considerations that do bear upon the issue of how
> valuable would monotherapy be versus sequential switches versus
> combination therapy.
>
> \[Slide.\]
>
> Should we investigate combination therapies in hepatitis B? I believe
> the answer is yes but we need to say that the combination therapy
> needs to prove its worth in this disease just as it has in HIV. The
> underlying biologic and virologic considerations are somewhat
> different particularly with regard to target cells and templates. So I
> personally believe that combination-therapy investigations should
> focus around the issue of combination therapy with any of two
> categories of goals. If combination therapy does actually improve
> durable responses in the overall compensated patient population, we,
> of course, would all like that.
>
> Short of that, there are patient subpopulations where combination
> therapy may have value. These are patient subgroups where virologic
> breakthrough may happen more frequently or the medical consequences of
> virologic breakthrough are often more severe with quicker progression
> of hepatic disease. The includes decompensated cirrhotics whom you
> have heard about today. Transplant recipients can progress quite
> rapidly after reinfection or reactivation.
>
> HIV or other coinfected patients have proved to be a rather difficult
> group to manage with monotherapies and possibly precore mutant
> disease, which has been talked about a lot today, may be a little more
> refractory to monotherapy for the reasons I think highlighted in Dr.
> Lok\'s talk and Dr. Hoofnagle\'s.
>
> So combination therapy may have value. But I would like to approach it
> with specific goals in mind. The improved efficacy, of course, in any
> one of these categories must offset the potential increase in cost and
> potential toxicities.
>
> \[Slide.\]
>
> You have heard about the array of endpoints that are used in
> hepatitis-B clinical trials over the last ten to twelve years; e-loss,
> e-seroconversion, s-loss, s-seroconversion. These are becoming fairly
> standard. I think highlighted in the publication at both the NIH
> workshop and the AASLD Practice Guideline is the possibility of
> composite endpoints which, I think, Anna touched upon quite
> extensively, the possibility of e-loss coupled with some measure of
> DNA suppression.
>
> Those endpoints are attractive. Let me mention that I think what was
> also apparent on both Jay\'s and Anna\'s slides that actually is the
> very endpoint that was used in the early interferon trials. So
> composite endpoints are not new but I think there was a sense that
> that might be a good way to go with regard to linking viral
> suppression with some of these surrogate endpoints.
>
> You have heard a lot about histology, really, since yesterday morning
> onward. I will talk about that a little bit.
>
> \[Slide.\]
>
> I have tried to pick data slides that have been very important to my
> perspective thinking about hepatitis B and hepatitis-B trial design.
> So, when you see a data slide, most of them are going to be lamivudine
> slides. I am using them to illustrate some scientific points around
> endpoints. I tried to pick the ones that have taught me the most of
> the last eight years or so of experience.
>
> This is a now rather famous cohort of 58 Asian patients out of the
> original Asian multicenter study, the Lai study, so to speak, who were
> treated with lamivudine continuously for up to four years in this
> display.
>
> There are some important lessons in this with regard to the endpoint
> of e-seroconversion or any endpoint that incorporated e-loss. We think
> the pattern would be similar if we had just done this according to
> e-loss. This happens to be the e-seroconversion endpoint of e-loss and
> antibody gain but, probably, the lessons are the same for any measure
> of e-clearance.
>
> Some of the important lessons are quite apparent here. I think to get
> to one of Tim\'s points, should we be treating patients with inactive
> disease? What you see here is the result\--oh; I think Anna
> highlighted it. I should mention in this cohort, almost a third of the
> patients were actually ALT normal at the start. The Asian study was
> the only one that allowed normal ALT patients in and that gives us
> some interesting scientific observations.
>
> If we talk about patients with relatively inactive disease who are
> actually ALT normal at the start, the e-seroconversion rate in those
> patients was quite low over four years. I think it was just under 20
> percent.
>
> The overall seroconversion rate for all patients with elevated ALT at
> entry, anything above the upper limit of normal, is illustrated here
> in the difficult-to-see tan line. I tried black background for better
> contrast. I hope people can see these endpoints.
>
> What this says is that, for any elevation of ALT, the e-seroconversion
> rate is substantially higher than patients with normal ALT. So is the
> 1.5 X or the 2 X number a magic number? I don\'t know, but there does
> appear to be a treatment effect for any patient with elevated ALTs at
> any level.
>
> But that is, perhaps, not the only interesting lesson. Another
> interesting lesson is the rate of seroconversion appears to be maximal
> in the first year at all ALT levels. That may be an important lesson
> for the future. I think the real question here is, in the first year,
> are we disproportionally selecting out patients who need an antiviral
> nudge into a seroconverted state and is seroconversion more difficult
> for the remaining patients.
>
> I think this is an extremely important biologic question that was,
> perhaps, underlying some of Anna\'s and Jay\'s concerns about
> long-term therapy. I don\'t think this slide answers it. This happens
> to be a lamivudine slide and, of course, as you know, resistance
> starts to kick in toward the end of the first year and becomes
> cumulative during time frame of this data display.
>
> So the real question is, as we develop treatment regimens, whether
> they are combination or monotherapies, are we going to be able to keep
> the slope of seroconversion that we see in the first year here which
> would imply that this tapering off of slope among these various ALT
> cohorts is due to the cumulative development of resistance.
>
> We do know that the seroconversion rate goes down when patients
> develop lamivudine-resistant virus. It doesn\'t become zero, however.
> I should point out, and it wasn\'t mentioned, I don\'t think in
> Anna\'s talk, but about a third of these patients who seroconverted
> over the four years actually had YMDD mutant virus so they did
> contribute to this overall area under the curve of seroconversion at
> any ALT level. But their rate was substantially lower than the
> patients who still had PCR-detectable wild-type or were non
> detectable.
>
> So the important lesson, I think, is is there a different biology in
> treatment response in the first year compared to subsequent years. I
> don\'t think we know the answer to that but I think we will find out
> as viral suppression gets better for longer-term therapy. We may see
> that the slope for seroconversion goes up in this direction which I
> think we would all be pleased by.
>
> \[Slide.\]
>
> That was an Asian cohort of 58 patients followed continuously. We took
> a look in the lamivudine data and, by the way, I want to recognize the
> large group from Glaxo here that helped generate these data and slide
> that have been previously presented at various meetings and their
> permission to present these slides.
>
> The Week 52 data from all of the four lamivudine trials in e-positive
> hepatitis B were integrated electronically and we examined, through
> univariate and multivariate analyses, what pretreatment factors
> influence the e-seroconversion rate.
>
> There were not big surprises here. This shows that, in a
> multivariate-adjusted analysis, lamivudine was superior to placebo
> treatment but, after that, the most important influence was baseline
> ALT, as is implicit in the slide I just showed you moments ago,
> absolutely important for both interferon and lamivudine that we treat
> patients with active liver disease indicated both by the ALT level as
> well as by the HAI score. This is a somewhat novel observation where
> HAI actually had the second greatest predictive value at baseline
> after multivariate adjustment.
>
> In the lamivudine database, viral load at baseline was not a
> statistically significant predictor of e-seroconversion response
> although there was some trend in that direction. The data for
> interferon have been controversial there. Some people feel that viral
> load does influence e-response. Others feel that it may not be as
> strong as in the original report.
>
> But these are absolutely key features when we think about this durable
> response which I want to emphasize, I think I agreed with the
> preparatory document by the agency staff that said this is the only
> endpoint that has been associated in the literature with long-term
> clinical benefit. The world is a factious place, so even that is not a
> uniform opinion. There have been studies to the contrary, but I think
> there is a consensus and I think both Dr. Hoofnagle and Dr. Lok tried
> to highlight that e-antigen clearance does appear to be\--the best
> consensus is that it probably is associated with long-term clinical
> benefit.
>
> Of all the endpoints you have seen today, this is the only one that
> appears to have that statement behind it.
>
> \[Slide.\]
>
> Certainly, during the lamivudine program and subsequently, I always
> worried abou is antibody important to the durability response. I
> don\'t think Anna is going to be completely happy with me on this
> slide, but we did try to address that\--yeah; I knew it\--we did try
> to address that very question in the lamivudine database, and we can
> talk about whether this is a final answer to the question or not.
>
> But the best impression that we had out of analyzing lamivudine data
> by looking, again, at integrated phase III data looking at patients
> with various known parameters of e-antigen-related response at Week 52
> and following them, in this case, just for twelve to sixteen weeks
> post treatment. This is very short-term data.
>
> If you look at patients where the only statistical requirement for
> inclusion was e-antigen loss, you see that on the left column. The
> next one is e-antigen loss plus DNA nondetectable by the solution
> hybridization assay. That is the second from the left.
>
> Third from the left is e-antigen loss with antibody present and DNA
> nondetectable. Then the last column, over to the right, is that same
> response documented on two successive clinic visits. This displays
> what proportion of patients were still e-antigen-negative at end of
> study. These were all off-treatment patients, three of the four
> lamivudine trials, and e-positives required an off-treatment period
> after Week 52.
>
> My interpretation of these data was that the durability is all between
> about 74 and 77 percent regardless of whether antibody is present, et
> cetera, et cetera. Now, this is not long-term data. I will offer one
> comment to Jay\'s comment about when do patients relapse when they are
> going to relapse. My view of primarily the lamivudine data but some
> other data would be that, as Jay said, the story in hepatitis B is not
> as clear as it is in hepatitis C. I think in hepatitis C the data is
> very strong the 90 percent of relapses, or 90-plus percent of
> relapses, occurs in the first six months post-treatment, as I think
> Dr. Hoofnagle said.
>
> In hepatitis B, with very limited data, my guess would be most of the
> relapses occur in the first twelve to eighteen months after these
> kinds of responses. But I think it is well established in the
> literature that these patients are at risk for reactivation at almost
> any time, particularly if they get debilitated or immunosuppressed. So
> I think the current and long-standing goal to follow all
> surface-positive patients essentially for life with at least
> observation certainly is supported by an understanding of the relapse
> phenomenon.
>
> So I think, personally, relapse is relative to eighteen months after
> e-antigen clearance but it can be sporadic thereafter, particularly if
> patients get debilitated.
>
> \[Slide.\]
>
> So that bottom line is e-loss alone, perhaps coupled with the DNA
> suppression criterion, just as the AASLD Practice Guideline
> recommended, I think that was data to support that kind of
> recommendation.
>
> Now, everybody has their favorite slide about what important things
> have we learned from liver histology. I think one of the themes
> yesterday is highlighted here, but there are some other ones. If we
> have learned anything for liver histology, I think at least half of it
> is thanks to Dr. Goodman who, I think, is still here this morning. So
> he has been a big part of this evolving story for the last ten years
> in hepatitis B and C.
>
> It probably needs to be emphasized that there are a relatively small
> number of hepatopathologists who are truly expert in doing these kinds
> of scoring techniques.
>
> This is my personal list of what we have learned from liver histology.
> I think that we have learned that, a the FDA guidance document kind of
> highlights, probably the mechanism of action of these antiviral drugs
> is viral suppression leading to the range of improvement on clinical
> parameters that you are seeing.
>
> So I, personally, believe that the data do suggest that viral
> suppression is associated with decrease of necroinflammatory activity
> in the liver. The correlation is not nearly as good as we would like.
> I think that is a theme today that the FDA speaker will continue to
> address and it has been apparent, I think, so far.
>
> But one of my first realizations of this fairly important feature is
> that I looked at I think it is Table 4 in Bob Perillo\'s original
> multicenter study. They had a category in the interferon studies
> called indeterminate responders. They were patients who were still
> e-positive but had actually gone undetectable for DNA in the Abbott
> assay.
>
> If you look at the HAI reductions in those patients where they were
> still e-positive but had a reduction below roughly six logs or so, the
> HAI improvement in those patients was about three to four points, very
> similar to what you see in the seroconverted patients. Seroconverted
> patients usually have about one point more improvement. So that was an
> early lesson to us on the lamivudine program because we are going into
> phase III with no data on our primary endpoint of histologic response.
>
> That gave us some faith that DNA suppression might be associated with
> histology improvement. I believe that association exists, but it is an
> imperfect association, as you saw in some detail in Anna\'s talk.
>
> Both the lamivudine and adefovir trials have produced some interesting
> data on fibrosis and worsening of placebo patients. It does appear
> that placebo patients, even over the course of a year, get detectably
> worse although not markedly so with regard to liver histology
> including some worsening in fibrosis. That was the bad news of placebo
> controls in those studies.
>
> The good news was analysis of quite a lot of lamivudine and now
> adefovir data indicate that fibrosis and in even early degrees of
> cirrhosis can probably improve in antiviral therapy, at least in some
> patients. So, perhaps, this progression of stages is not as
> irrevocable as we have thought for a long time. I see Dr. Hoofnagle is
> probably going to want to comment on that, but I think he did show
> patients who went from 14 or 13 down to a score of about 1.
>
> So, again, it is probably not something that we can achieve in
> patients with very advanced cirrhosis but I personally think, in both
> hepatitis C and B, there is increasing data that the constant
> plasticity of the liver can lead to improvements, at least for earlier
> degrees of fibrosis.
>
> One of the issues with interferon in the mid-\'90\'s was largely from
> hepatitis-C trials, did cirrhotics respond as well as noncirrhotics.
> So we did look at that question in the lamivudine program and adefovir
> probably has some more data. The answer was that histologic stage of
> disease did not appear to influence most of the array of endpoints
> that you saw displayed for hepatitis B.
>
> So that left the compensated cirrhotics in the same treatment category
> as the compensated noncirrhotics to my mind.
>
> Now, a couple of exploratory studies have been interesting. I don\'t
> consider these to be established facts but there was a study from the
> North Carolina group, Mike Fried and colleagues, using some biopsies
> from the lamivudine program and looking at them in a blinded fashion,
> both placebo and drug-treated.
>
> They published this in the Journal of Hepatology, the effect the
> antiviral therapy does appear to be associated with decreased
> stellate-cell activation, so that may be a mechanism for antiviral
> therapy resulting in preventing worsening of fibrosis.
>
> The adefovir group produced a very interesting presentation at ISAL
> just this spring in a subgroup of about twenty patients or so. It did
> look like there was a chance for long-term reduction of cccDNA in the
> liver in collaboration with a European collaborator. I think they
> reported about a nine-fold reduction over the course of a year.
>
> Again, I consider these two last points to be rather exploratory but,
> interesting observations that have come from liver-biopsy material
> from clinical trials.
>
> \[Slide.\]
>
> There are some problems with liver biopsies, both scientific and
> practical. The practical problems, I should say, are looming worse and
> worse as the FDA guidance document I think accurately forecasts that
> we are going into an era of large active-control studies, and the
> larger the studies get, the more they need to be multinational and
> these kinds of problems become magnified with that assumption.
>
> So I have come to call, thanks to a couple of colleagues, the liver
> biopsy is certainly a direct picture of the disease but it is only a
> snapshot in time and space. We used to call it a snapshot in time, but
> the biopsy sampling error is the result of the space addition to this
> concept.
>
> So the problem is, until patients get either very consistent very
> early disease or very consistent very late disease, in between, the
> disease can be somewhat patchy and there is a significant sampling
> error even in a well-done biopsy.
>
> Then the waxing and waning nature of this disease coupled with the
> sampling error, I think it has probably been highlighted by others
> using different words that a lip in hepatitis B probably is less
> predictive of long-term outcome than, let\'s say, in the hepatitis C
> patient where the disease is a little more constant.
>
> The flare activity of this disease can result in sudden worsenings of
> the necroinflammatory activity which, within a few months, will lead
> to worsenings in fibrosis so a patient may look fine one year and be
> dead the next year from a nasty flare. I think that is an important
> concept with we think about how important are liver biopsies in
> hepatitis-B trials.
>
> Another issue is the histologic scoring does have very wide inter- and
> intraobserver variation. That variation, in much of the trial data you
> have seen, has been minimized by the fact that number of people doing
> these scorings has been very, very small. I think Dr. Goodman has been
> involved in probably at least half of the data you have seen, and Zach
> is a recognized expert.
>
> But, as you go to other scores, you do find increasingly wide
> variation. I think an example in the lamivudine program was when we
> had a European-Canadian study with a different pathologist. With a
> similar patient population, the histologic response estimated rate was
> 15 percent less than in the other trials.
>
> So there can be significant variation.
>
> Another good example of that variation was in the data that you saw
> yesterday. I don\'t mean to, in any way, discount the marvelous
> efforts of the adefovir team in getting all those biopsies, and I
> think the same would be true for lamivudine, but if you noticed in the
> data yesterday, the treatment effect was exceeded by the standard
> deviation. When you have treatment effects that are smaller than the
> standard deviation\--this was for the 437 study I believe where the
> mean reduction was 2.8 points and the standard deviation was 3.2
> points.
>
> I don\'t think we primarily analyzed lamivudine by medians so I don\'t
> know if that would have been true with lamivudine but it is an example
> of how difficult it is to precisely assess histologic changes, very
> large standard deviations and standard errors when you approach that
> with mean reductions.
>
> Nonetheless, there are consistent treatment effects with antivirals
> that have a consistent DNA suppression effect.
>
> Now, the missing data thing becomes important as we move to larger
> trials especially. It is potentially feasible, when you are working at
> tertiary university centers with well-trained and enthusiastic
> hepatologists\--it is potentially feasible to get the missing-data
> rate down to about 10 percent as you saw yesterday. The original
> interferon trials, I think, had 30, 35 percent missing data. The
> lamivudine trials typically had 15 to 20 percent missing data.
>
> But, as we go to larger studies, studies of 800, 1,000, 1,300
> patients, there is just a limited number of centers that take care of
> large numbers of hepatitis-B patients who also have confidence and
> expertise in serial level biopsies. So that becomes a real problem and
> it predicts that the missing data rate we may never, even with good
> efforts, exceed the relatively low missing-data rate you saw
> yesterday.
>
> But if you consider the adefovir missing-date rate of around 10
> percent, and you consider that the delta is probably 15 percent, you
> can see how important the missing data is to estimating noninferiority
> or superiority.
>
> The other key this is that, as we go toward active-control-trial
> designs, the attempt to treat assumption that missing data is
> treatment failure, as the FDA officers, I think, would want to remind
> us, if you use that intent-to-treat assumption in active designs, that
> tends to make two treatments artificially look more similar than they
> really are. So in active designs, you actually need to go to an
> efficacy subset analysis. I think the FDA feels this way and, in my
> experience, the European agencies as well.
>
> So missing data with liver biopsies becomes a key issue and can we
> really limit that to 10 percent or less in these huge multinational
> trials. I am not optimistic, personally.
>
> But these considerations do cause a real problem when you are trying
> to design a trial and with histology as the primary endpoint, it
> becomes very iffy with regard to sample-size calculation. You really
> don\'t know ahead of time how much missing data there will be and you
> don\'t know ahead of time what your chosen histopathologist\'s scoring
> record is compared to some other histopathologist who might be chosen
> whose result on the same patient population might be 15 percent
> different.
>
> So it causes real problems in trial design when histology is the
> primary endpoint. But, fundamentally, in my view, one of the greatest
> problems as we go to these very large trials is it is extremely
> difficult to find centers, in Asia, particular, particularly in
> Mainland China, who are very comfortable with serial liver biopsies.
> So we do end up excluding a lot of sites if serial liver biopsies are
> required for the primary endpoint.
>
> There is an issue around liver biopsies which came up yesterday. There
> are two liver biopsies involved. One, the pretreatment, is presumably
> a good idea on the basis of disease stage and, as somebody mentioned,
> that is really an issue for a practice guideline. I think the AASLD
> Practice Guideline does continue to recommend staging biopsies in B
> as, perhaps, Anna or Jay alluded to.
>
> But the real issue is the follow-up liver biopsy. I want to get into
> that shortly.
>
> \[Slide.\]
>
> Let me back up for a second. We have heard a lot about the
> correlations among efficacy endpoints. I am not going to speak to that
> a lot because you have heard a lot from two speakers and you are going
> to hear more from the FDA speaker. But we did look at the lamivudine
> data for one key issue having to do with how valuable is that second
> liver biopsy.
>
> My personal view is that monitoring of serological markers is at lest
> adequate to predict lack of worsening in the follow-up biopsy. So let
> me walk you through that thinking.
>
> This was presented, I think, at the NIH workshop in a poster form
> about two years ago. In the integrated database, we ended up with a
> very simple kind of analysis. If patients were normalized in their ALT
> or at least improved by 50 percent during the course of the first year
> of lamivudine therapy, the chances of the HAI score being worse at
> Week 52 were only 5 percent.
>
> Looking at the other principle serologic parameter of DNA, if viral
> load was nondetectable by the Abbott assay or reduced by 50 percent,
> the HAI was worse in only 9 percent of patients at Week 52. I think
> most of us would agree that these 5 and 9 percent numbers are within
> the scoring error of the histologic scoring techniques.
>
> So my bottom line out of this experience was that monitoring of viral
> load and ALT, just as you imagine in the clinic when you are looking
> at the numbers from your patient\'s clinic visit, does, in fact, have
> an adequate prediction of whether the patient is getting worse. It
> doesn\'t say that the histology is getting better but it at least says
> they are probably not getting worse. So that is a somewhat happy
> message for routine clinic monitoring which is what we do nowadays
> with viral load and ALT.
>
> For seroconversion, the story is a little different. It is quite
> apparent that you need an ALT response and the correlations there are
> affected by that. But I think what I took away from Anna\'s talk was
> there is probably a better correlation among serologic efficacy
> parameters than there is between serology and histology. Maybe that is
> a theme or an issue we could address in today\'s discussions.
>
> \[Slide.\]
>
> I am going to talk a little bit about experience with some of the
> endpoints you heard about from Dr. Lok in decompensated-disease
> trials; survival, improvement in Child-Pugh. I am not calling it here
> Child-Pugh-Turcotte, although it was an improvement in the biochemical
> parameters reflecting liver function.
>
> \[Slide.\]
>
> This is an overall\--we put together three lamivudine cohorts in an
> integrated database because they had somewhat similar entry criteria.
> Their laboratory parameters were all sent to a central lab with
> consistent performance of the HBV markers as well as the biochemical
> markers.
>
> What you see here is an overall survival curve for this assembled
> cohort of 133 patients. This is the initial slide from AASLD from a
> couple of years ago that was expanded to a 154 patient database and
> these results will be coming out in Gastroenterology within the next
> two to three months in a paper by Bob Fontana and myself and possibly
> others in this room.
>
> When you look at overall survival, I think this really reflects some
> of the observations in the Villeneuve paper that Anna talked about.
> There is kind of a break at about six months in overall where you see
> 20 to 25 of patients dying in the first six months essentially all of
> liver-related complications. Then there is almost a kind of leveling
> off or a quasi-stabilization of these patients with regard to
> survival.
>
> This suggested, just seeing that initial survival curve when we were
> putting these data together suggested that there are really two groups
> of patients here, as Anna talked about, those who are going to die
> anyway and those who can be stabilized with antiviral therapy.
>
> But the important point was, out of this\--I should mention these
> protocols were relatively open-ended so there were a lot of Child C
> cirrhotics in these ALT requirements. The only ALT requirement was you
> had to be under 1500. For example, we didn\'t want people who were in
> huge flares right at the start.
>
> Other than that, it was pretty open-ended. The only albumin
> requirement was 1.5, for example. But this suggested\--this is an
> important observation and suggested there were two populations of
> patients, those who can be stabilized with antiviral therapy and those
> who can\'t. The important observation looks like it was the majority
> of patients can at least be stabilized with antiviral therapy.
>
> If this infection kills 1 million to 2 million people a year
> worldwide, most of them in places where you can\'t get a liver
> transplant, there is some hope that antiviral therapy can stabilize or
> help a lot of patients toward long-term survival.
>
> \[Slide.\]
>
> I need to caution you, these are uncontrolled data. The survival did
> look better in historical, as I think Anna mentioned.
>
> In fact, when we divided the two groups up according to those who died
> early, and, again, they were all of liver complications, and those who
> died late, the actuarial survival for the patients who survived six
> months was actually 80 percent for three years, and kind of the
> historical range was anywhere from about 14 percent to about 50
> percent for these kinds patients.
>
> So, in an historical comparison, there were a lot of patients
> experiencing fairly prolonged survival. In a univariate analysis,
> these parameters showed up. But, in a multivariate analysis, the most
> important parameters predicting early mortality were elevated
> bilirubin, elevated creatinine and detectable DNA in the Abbott assay.
> There were some surprises there that I see Dr. Hoofnagle perking up
> on.
>
> The DNA was particularly interesting because we looked at were there
> any kind of markers of patient response that could predict six-months
> survival; in other words, early-on therapy responses. It turned out
> ALT normalization and viral-load response or viral DNA reduction
> really didn\'t predict six-month survival. It was really the extent of
> preexisting liver disease because both groups had viral suppression in
> the Abbott assay. We didn\'t have an assay sensitive enough to
> discriminate by PCR.
>
> But, at least when using the Abbott assay and looking at ALT
> normalization, early ALT and DNA responses did not differentiate these
> groups. It appeared to be, really, the degree of liver damage early on
> and, in the multivariate, bilirubin essentially wiped out albumin as
> an independent predictor so it was only bilirubin in the multivariate
> contrary to some other series.
>
> But elevated creatinine was the other surprise here so marginally or
> bad renal together with bad liver function logically does predict
> worse survival early on. Needless to say, these are interesting data
> but long-term control data are going to be more feasible now that we
> have multiple agents available.
>
> I should mention we did try to do a placebo-controlled study with
> lamivudine in decompensated disease and five out of the eight IRBs
> turned it down. I think some people in this room will remember that
> effort. That was around 1996, 1997. So that is why you don\'t see
> placebo-controlled data with lamivudine.
>
> \[Slide.\]
>
> Here is the performance of Child-Pugh score in one of these three
> patient groups, a 70-patient cohort Group A out of the so-called
> compassionate-use study for lamivudine. What you see is, again I think
> Anna probably alluded to this parameter as an interesting endpoint
> that does have some validity, at least performance validity, in
> decompensated disease.
>
> Here you see, over the course of six to twelve months, patients get an
> average of about a two-point reduction in Child-Pugh score. This is
> not quite as dramatic as the result that Anna showed in the Villeneuve
> series which is a little smaller but, nonetheless, relatively dramatic
> in the sense that most patients either improved or stabilized in their
> Child-Pugh score with only three patients out of the cohort worsening.
> The average follow up on these data was just over a year.
>
> \[Slide.\]
>
> Biochemical parameters; thankfully, there is sometimes a correlation
> between text books and what we see in clinical trials. Sure enough,
> with prolonged therapy, let\'s say of six to twelve months or more,
> one can appreciate, in patients with elevated bilirubin at the start
> or patients with low albumin, one can appreciate improvements over
> time, albumin improving with bilirubin declining in this case over a
> period of one and then two years.
>
> \[Slide.\]
>
> My personal view of the array of endpoints that you have seen
> displayed today is that there is at least a correlation between viral
> suppression and histologic responses in ALT normalization. There is
> some correlation of viral suppression with e-antigen responses,
> e-clearance, as you saw, I think, in the data that Anna showed from
> both the lamivudine and adefovir programs.
>
> It is not an absolute correlation, but e-antigen loss does appear to
> be more common under about four or five logs. But, in that case, it is
> clear that preexisting immune response is heralded by, or I should say
> marked by, pretreatment. Elevated ALT levels are required for any real
> treatment effect, any appreciable seroconversion rate.
>
> Serologic monitoring, again, I mentioned, out of the integrated data,
> was at least good enough to predict lack of histologic worsening. That
> speaks to does the follow-up biopsy really give you any independent
> information. It might give you information on fibrosis improvements
> which, I think, has been highlighted by the FDA speakers. That is an
> important issue for discussion.
>
> But at least we can generally tell by monitoring ALT levels and DNA
> levels that the histology has not generally worsened overall. That
> actually was somewhat apparent in the discussion of the adefovir data
> as well yesterday in one of Carol Brosgart\'s responses.
>
> Clinical and biochemical signs of disease progression are rare. I
> didn\'t highlight this in my talk so far but, in the one-year
> lamivudine studies, there were actually no deaths and no hepatic
> decompensates in the four controlled trials involving something like
> 958 patients during one year.
>
> Now, we have gone to two-year trials and I am not sure the same will
> be true and I haven\'t seen all the adefovir data but, at least during
> relatively short periods in compensated patients, the incidence of
> hepatic decompensate is rare in placebo recipients as well as in drug
> recipients. There were 200 placebo recipients in the phase III
> lamivudine trials.
>
> However, there was some histologic deterioration that I mentioned in
> placebo recipients.
>
> The markers that are appropriate in decompensated disease clearly need
> to be different, as we have all highlighted. The good news is we do
> have some parameters available that do appear to respond to clinical
> trials to antiviral therapy.
>
> \[Slide.\]
>
> One slide that I thought the group might be interested in and,
> certainly from yesterday\'s discussion I think there may be some
> interest in some of the stuff that is happening now in clinical trials
> in hepatitis B. I think there was a plea yesterday, can we get
> combination-therapy trials started.
>
> As Carol indicated, there are some collaborative studies between Glaxo
> and Gilead in treatment-naive patients, I should say, for lamivudine
> plus adefovir. We also heard from her that there is a plan or ongoing
> plan to have a trial of adefovir plus m-tricytovene, FTC.
>
> There is also an ongoing phase II-B trial with about 104 patients in
> five countries. This trial investigates two doses of LDT but it does
> include two combination arms of LDT plus lamivudine and a lamivudine
> reference arm, as well. So that trial is ongoing.
>
> I think that my understanding is that abstracts from both of these
> trials at least regarding early virologic observations that may show
> up at AASLD this fall. So, hopefully, you will start to see data from
> some of these nucleoside, nucleotide, combination trials.
>
> Again, in my book, the jury is still out on what will be the benefit
> of combination therapy in hepatitis B. I have been involved in trying
> to help set up both of these so, while I might be seen as a skeptic on
> combination, I have tried to be supportive in my involvements, at
> least.
>
> There is a large clinical-endpoints trial that has just been stopped.
> I think the group needs to be aware of this and I do have the Glaxo
> folks permission to mention this. It was, apparently, mentioned at a
> meeting recently so it is not a total secret. But there was a large
> study set up prospectively by Glaxo four or five years ago, was when
> it started.
>
> It became fully enrolled I think over three years ago. There are
> people from Glaxo here to answer any specific questions but probably
> not on the data yet. But, in any case, this was set up as a
> placebo-controlled\--we couldn\'t do the trial in decompensated
> disease but we flipped over the endpoint and tried to do a trial
> suggested essentially by one of Jay\'s comments this morning.
>
> As you heard, you can\'t do a clinical-endpoints trial if you start
> with people who only have lobular hepatitis. But if you start with
> people who are cirrhotic, there is a chance that they still have
> enough hepatocytes left that you can stabilize them or even improve
> them and that you can get clinical decompensation endpoints over a
> relatively shorter period.
>
> So that was the concept behind this very large placebo-controlled
> lamivudine trial. I don\'t know the exact numbers because, again, this
> has just happened, but there were over 600 patients involved in the
> initial\--enrolled in the study. I think the study was roughly two to
> three years after full enrollment so many patients were far along.
>
> In fact, the study was stopped. This study, I should mention, had an
> external steering committee verifying each of the clinical endpoints
> which were protocol-specified. And then it also had an external
> independent DSMB. The DSMB stopped the trial for overwhelming efficacy
> on clinical disease progression in favor of lamivudine.
>
> You will be seeing those data, I imagine, soon. I think those data
> will speak to a lot of issues that are on people\'s minds right now
> with regard to the benefit of antiviral therapy as well as the benefit
> of continuing treatment after Year 1 particularly in patients with
> resistance virus.
>
> The other issue that I realize hadn\'t been talked about so far and
> might not be talked about by others is the issue is there a role for
> perinatal prevention in hepatitis B. There is a current ongoing trial
> with a little over 400 patients as the accrual goal where lamivudine
> is being looked not as a substitute for vaccine but as an adjunct to
> both vaccine and HBIg.
>
> That is the primary role because there is a certain leak-through of
> infection in high viremic mothers. The vaccine failures in the
> perinatal setting are often in moms who have nine logs of virus or
> above or even in the high 8s. So it has been traditionally known that
> e-positive moms had a fair failure rate, and the Glaxo folks got
> together some data about how could one specify that by DNA entry
> criterion.
>
> So that trial will be ongoing but I think we are probably several
> years from that result.
>
> \[Slide.\]
>
> We have a couple of slides on an effort that involved a questionnaire
> and then a follow-up telecon trying to get a sense of what do people
> working in hepatitis-B development right now with drugs sort of in
> phase IV and beyond, what are our primary concerns for the committee
> to discuss today.
>
> Those are really illustrated on the next couple of slides. The people
> who contributed to this process are indicated here. The Gilead folks
> were also canvassed but they were really tied up trying to prepare for
> yesterday. So we did have pretty good contributions from all the
> companies indicated here.
>
> I think we decided to call this a perspective rather than a consensus
> because I don\'t mean to imply that everybody was uniform on every
> issue.
>
> \[Slide.\]
>
> Interestingly, the questionnaire responses where 1 was a critically
> important rating, all of the respondents rated discussion of histology
> as absolutely critical for the committee to discuss today. The second
> issue that was uniformly rated as critically important was the issue
> of active versus placebo controls in trials going forward.
>
> There was also very high interest in the group discussion of the
> correlations between endpoints which I think is a big topic discussed
> by others and will come out further in the discussion, and also some
> of the criteria for noninferiority versus superiority. Particularly
> discussed were the endpoints in e-negative hepatitis B where we still
> don\'t know when to stop treatment there, but the therapeutic-response
> endpoints might at least be more clearly identified.
>
> So there was very clear consensus on these issues and we hope the
> committee will take note of them and discuss today.
>
> \[Slide.\]
>
> We thought maybe an interesting framework to try to get at those
> issues would be to first discuss what are the therapy goals in chronic
> hepatitis B, discussing therapeutic-response endpoints versus
> treatment-discontinuation endpoints as one way to frame it. What are
> the choices of endpoint in e-positive, e-negative, and then what
> endpoint really best discriminates in active-control-trial designs.
> That is a key issue.
>
> \[Slide.\]
>
> Scientific issues? I don\'t think I want to highlight a lot here today
> but we are probably as frustrated as anybody that we still don\'t know
> what other targets, other than the polymerase, might produce tractable
> therapeutics. One of the reasons we don\'t have a good handle on that
> are some of the scientific unknowns including one of the key ones
> which is what immune factors result in clearance versus persistence of
> the virus.
>
> I think we will stop there on elaborating this slide.
>
> \[Slide.\]
>
> In closing, I would really like to offer this as a set of personal
> perspectives based upon a number of years in trials in this area. We
> very much value the FDA and committee guidance today on endpoint and
> trial-design issues. The future registration trials, in my view,
> particularly as we move toward large active designs, are going to need
> to be large multicenter international trials incorporating many sites
> in Asia, North America, Europe and elsewhere.
>
> The active-trial designs my have monotherapy arms or combination arms,
> but the principles of design are similar and, in my view, we do need
> primary serologic endpoints for precision and the ability\--to really
> come up with accurate assumptions and accurately design trials, I
> think we need serologic endpoints, possibly the composite type that
> Dr. Lok mentioned toward the close of her talk, clinical endpoints
> linked to viral suppression.
>
> I think there is a need to get assay standardization before we can
> really move to viral load as a primary endpoint in this disease. I
> think you have heard enough vagaries in that regard that I don\'t have
> to elaborate further. But, after we achieve assay standardization,
> might it be possible to use viral load as a primary or at least as a
> conditional endpoint in some patient populations where the death rate
> is particularly high such as decomp patients and then follow on with
> more clinically related endpoints. I think that paradigm might be
> visited in the discussion.
>
> I think I need to close by saying that, under today\'s condition of
> HBV drug development, it takes about four to six years from the time
> an IND is filed until approval. During that time, if the global death
> rate of this disease is 1 million to 2 million a year, then, during
> the time of clinical development of a single drug, somewhere between 4
> million and 8 million people have died from this disease.
>
> We need to find a way to make a quicker impact on that.
>
> Thank you very much.
>
> DR. GULICK: Thank you.
>
> Are there one or two quick questions? Dr. Block?
>
> DR. BLOCK: Very quick question. Nat, very nicely done. On your slide
> where you were showing the decompensated chronic hepatitis B
> treatments with lamivudine, you had one of the early predictors of
> early mortality, if I understood this correctly, detectable HBV DNA.
>
> DR. BROWN: That was in the integrated database for decompensated
> patients, viral load positive at baseline in the Abbott assay which is
> roughly a six-log threshold.
>
> DR. BLOCK: Was a positive predictor\--
>
> DR. BROWN: Was a predictor of early mortality.
>
> DR. BLOCK: If I flip that, then you are saying if there was low DNA or
> no DNA, that had a positive predictive value.
>
> DR. BROWN: Even short-term survival was better; that\'s correct.
>
> DR. BLOCK: But then what would the rationale of lamivudine be, an
> antiviral that would then serve to\--
>
> DR. BROWN: Clearly, none of these observations are absolute. So my
> take on why viral load and six logs and above was a predictor of early
> mortality probably had to do with the intensity of infection in the
> liver. But it did appear that quite a number, roughly three-quarters,
> of the patients can be stabilized with antiviral therapy.
>
> By implication of that multivariate analysis, those tend to be
> patients whose liver disease is not as far along and whose viral load
> may be a little lower.
>
> DR. GULICK: Why don\'t we move along. The final presentation of the
> morning will be from the agency, Dr. Greg Soon.
>
> DR. MURRAY: I was going to make some initial comments but I think we
> will just have Greg do the statistical talk and then my comments would
> be better left for the charge to the committee right before the
> questions.
>
> DR. GULICK: Okay, if you like.
>
> **Surrogate Endpoints for Hepatitis B Trials**
>
> DR. SOON: Good morning. I\'m Greg Soon, the statistical team leader
> for the Antiviral Division.
>
> \[Slide.\]
>
> This talk will examine the feasibility of replacing biopsy by several
> potential outcome variables and using them as the primary efficacy
> measures; that is, to find surrogate endpoints to replace biopsy for
> hepatitis B trials. This is work done with Dr. Bhore.
>
> \[Slide.\]
>
> What are the potential replacement measures for biopsy? The measure
> could be the ALT, viral load and various serologic markers. Different
> metrics of the same measurement could be used like the changes of
> baseline, end of treatment, duration, suppression, et cetera. There
> are many possibilities here.
>
> In this talk, liver biopsy will be measured by the necroinflammatory
> component of the Knodell score. I will simply refer to this as the
> Knodell score.
>
> \[Slide.\]
>
> The next one will be based on the NDA submissions, one from the
> adefovir submission that you have seen yesterday and the other NDA is
> from the Epivir HBV submission that was reviewed in 1998. The Epivir
> submission had four studies with a total of five treatment groups. The
> four studies I will refer to as the U.S. study, IFN nonresponder
> study, Asian study and active-control study.
>
> The five groups are placebo, lamivudine 100 milligrams, lamivudine 25
> milligrams, lamivudine plus interferon, and interferon alone. These
> three groups are treated for 52 weeks plus. These two groups are
> treated for 24 weeks with additional follow up. The total number of
> patients is about 900 and there are substantial missing biopsies at
> the end of week 52. The average missing rate is 16 percent.
>
> \[Slide.\]
>
> The two adefovir trials are 437 and 438. I will refer to them as the
> e-antigen-positive study and the e-antigen-negative study. The
> duration of these trials are slightly shorter, 48 weeks, compared to
> the 52 weeks for the Epivir trials. The number of patients is 672 and
> the missing rates are much lower. It is about 80 percent on average,
> particularly lower for the e-antigen-negative study at 5 percent.
>
> These two submissions, in combination, have 1573 patients. Of these
> patients, 1372 had both baseline and year-end biopsy. There were an
> additional 17 patients that are either missing ALT or the HBV DNA at
> either baseline or Year 1. So there are 1355 patients who had both
> biopsy, ALT and HBV DNA at both baseline and Year 1. So once a year it
> means we treated for the Epivir trials and Week 48 for the adefovir
> trials.
>
> \[Slide.\]
>
> One difference between the Epivir and the adefovir trials is the
> assay. The Epivir trials used the Abbott hybridization assay which has
> a lower limit of about 500,000. Some people say it is higher, but the
> same magnitude. In the Epivir trials, we see many patients achieve a
> suppression. But the estimate is so high that even if there are
> differences between these patients, the assay will not be able to
> differentiate these patients on the HBV DNA.
>
> For this presentation, I have converted the units for this assay into
> copies per ml to be comparable to the adefovir trials. The adefovir
> trials have the PCR assay that had a lower limit of 400 copies per ml.
>
> \[Slide.\]
>
> So this is an overview of the talk. There are five sections. First, I
> will go over the efficacy again and also describe the variabilities of
> both efficacy and also the measurement over time.
>
> Next, I will look at the patient-level correlation of the HBV DNA, ALT
> and measure these with the Knodell scores. Next, I will look at
> trial-level correlation as well as the proportion of treatment effect
> explained. Lastly, I will do a summary.
>
> \[Slide.\]
>
> First, I will go over efficacy.
>
> \[Slide.\]
>
> The first efficacy I will go through is the Knodell score.
>
> \[Slide.\]
>
> This is a convention, the color convention, I will be using for the
> talk. The white will be for the placebo arm. The yellow will be for
> the lamivudine 100 milligram adefovir 10 milligrams. These are the
> markings of those. The orange will be for the lamivudine 25 milligrams
> or adefovir 30 milligrams. Red will be for the
> interferon-plus-lamivudine treatment. Green will be for the
> interferon-alone arm.
>
> \[Slide.\]
>
> This plots the baseline Knodell score against the change from baseline
> of the Knodell score. The X axis is the baseline Knodell score and the
> Y axis is the change of Knodell score.
>
> The Knodell score has a range of from 0 to 18 which roughly you can
> see from the X axis. It is not the whole range but it is close.
> Patients who have a baseline Knodell score close to 0, by definition,
> will not have a chance to see much improvement while patients on this
> end of the baseline will not see a worsening because they have already
> reached the upper limit of the Knodell score.
>
> These two lines indicate the upper bound and the lower bound for the
> change that could have been achieved. The solid white line is for the
> placebo arm that indicates a trend for the placebo arm. The yellow
> curve is for the lamivudine\--sorry; for Study 438. That is the
> e-antigen-negative study. So this will be the adefovir 10-milligram
> arm.
>
> We can see several things from this graph. First, we can see that the
> yellow line, this line, is separate from this white line. The
> separation is roughly consistent over the whole range of the baseline
> Knodell score which means that the treatment-effect size is roughly
> the same regardless of what is the baseline status.
>
> Secondly, we can see the negative correlation in both treatment groups
> so that means the higher the baseline score, the more change you are
> going to see. Thirdly, we can see the variability at each point
> between the patients. So there is a range of about 10 points in total.
>
> \[Slide.\]
>
> This is the same plot, but this is for the adefovir e-antigen-positive
> study. The orange line is for the adefovir 30 milligrams. You can see
> roughly the 30 milligram and the 10 milligram are overlapping, but
> both of them are separate from the placebo group. The conclusions are
> roughly the same as in the previous slide.
>
> \[Slide.\]
>
> So these are for the lamivudine studies, the four lamivudine studies.
> We can see here, in the U.S. study, there is a similar pattern here.
> For the interferon-nonresponder study, these two groups in the middle,
> they have a similar separation, but at the two ends, there is some
> crossing here.
>
> The red line is the interferon-plus-lamivudine arm which is not very
> clear in the picture. For this graph, the Asian study, we can see
> roughly the same pattern here. The 100 milligram is separated from the
> placebo, and the orange is somewhere in between here.
>
> This is the active study without a placebo arm. The yellow one, again,
> is the lamivudine 100 milligram and the red is the combination, the
> interferon plus lamivudine. The white in the middle is interferon
> alone.
>
> \[Slide.\]
>
> The next measure I will go over is ALT. In this presentation, the ALT
> will be transformed by the log10 and also divided by the upper limit
> of normal.
>
> \[Slide.\]
>
> The same order. I will show the adefovir e-antigen-negative study
> first. This is the median of the ALT over time for the two groups and
> the bars are the 95 percent confidence interval for the medians. So
> you can see a clear separation here between the two curves which is
> indicates the treatment-effect effects. That starts very early
> probably from Week 4 or maybe even earlier.
>
> \[Slide.\]
>
> This is for e-antigen-positive study. Again, we can see the same
> pattern. Also, additional, we have the adefovir 30 milligrams which is
> traces the 10 milligram also time except at the end, it has a
> separation.
>
> \[Slide.\]
>
> So, for the lamivudine studies, I combined all four studies. This is
> the 100-milligram group and this is the placebo group. You can see
> roughly the same pattern as we have seen for the adefovir trials. The
> orange one is lamivudine 25 milligrams.
>
> This may be artificially lower because this appears on one study. The
> red one is interferon plus lamivudine which, initially, it is
> somewhere between the placebo and the lamivudine 100 milligrams, but,
> it is off the treatment here, it stands to rebound back to more like
> the placebo here.
>
> The interferon-alone arm bounces around and eventually ends up
> somewhere around the placebo.
>
> \[Slide.\]
>
> This is, again, the same plot except here the bounds are for the
> individual patient variability. So this patient variability shows a
> range of the numbers. So we can see a shift of the effects again.
>
> \[Slide.\]
>
> This is a case study for about fifteen patients for the adefovir 437
> study. That is the e-antigen-positive study. I randomly picked fifteen
> patients from the placebo arm so we can see the history of each
> patient. Later, I will show also fifteen patients randomly selected
> from the adefovir 10 milligrams.
>
> This graph is somewhat busy so I will break this down into several
> graphs.
>
> \[Slide.\]
>
> Here we can see, there are four patients on this graph. This patient
> drops down, seems to be going the other way gradually. This patient is
> gradually dropping down, then coming down somewhat more rapidly, then
> went back. This patient has an initial drop and rebounded, then seems
> to be stable. This patient is stable, then has a small drop, then has
> a rebound and then comes back again, then somewhat moves down, is
> stabilized here.
>
> \[Slide.\]
>
> These are an additional four patients here. This patient goes up, then
> comes down fairly dramatically. This patient gradually decreases, then
> has a rise, then has a drop again. This patient is fairly stable,
> starts to decrease over time. This patient is only on the trial maybe
> for four weeks and then drops out. There is no more data.
>
> \[Slide.\]
>
> This is an additional four patients. This patient has a slight drop
> here and then it is maintained. This patient has a slight rise, then
> he had a slight drop, then slight rise again. This patient is going
> down most of the time except here there is a small flare.
>
> This patient has a drop here and then goes up gradually, then has a
> drop again in the end.
>
> \[Slide.\]
>
> There are three patients here. One patient is still a dropout. We
> don\'t have long enough data. This patient has some ups and downs and
> then not very big drop or rise. This patient is fairly stable.
>
> So, in summary of these fifteen patients we sampled from the placebo
> arm, some are stable, some vary to a certain degree and some have
> relatively large variations.
>
> \[Slide.\]
>
> This is fifteen patients chosen from the 10-milligram arm. I will not
> go into details of this but here you can see the same thing here.
> There are ups and downs. Some patients have fairly subtle drop, then
> it goes back and then goes down again. But it seems to be that more
> patients have smaller ups and downs here in this graph.
>
> \[Slide.\]
>
> This, I will show you three patients out of those fifteen patients to
> see in detail here. This is a patient who had a drop, then goes up,
> goes down again. These two patients seem to be relatively stable.
>
> \[Slide.\]
>
> The next endpoint I will talking about is HBV DNA, again on a log10
> scale.
>
> \[Slide.\]
>
> Again, we are seeing treatment effects over time.
>
> \[Slide.\]
>
> This is an e-antigen-positive study. This graph is different from the
> graph with the ALT in that the 30 milligrams showed a significant
> different from the 10 milligrams here over time.
>
> \[Slide.\]
>
> This is the lamivudine study. Here you see the graph appears to be
> very different. That is because of the assay problem. Patients\' viral
> load cannot go down below this level. That is the lower assay limit.
> Still, you can see the separation between the lamivudine 100
> milligrams and the lamivudine 25 milligrams against the placebo arm.
>
> The combination arm, interferon plus lamivudine, had a drop initially.
> Once off the treatment, it rebounded back to the same level as
> placebo. The interferon-alone arm seems to be bouncing up and down
> but, in the end, it is close to the placebo arm.
>
> \[Slide.\]
>
> This shows the Study 437. That is e-antigen-positive study for
> adefovir as an example to show the range of the variability for the
> individual patients.
>
> \[Slide.\]
>
> Again, these are some fifteen case studies for the placebo patients.
> Here, again, you can see\--I will go over this in detail and splitting
> it up into several graphs.
>
> \[Slide.\]
>
> This are four patients here. You can see this patient had a drop here,
> then a rise again. Then it sort of stabilizes. This patient goes up,
> then has a sharp drop and then has a sharp rise, then also stays
> there. This patient has a sharp drop, then a gradual rise here. This
> patient has a sharp drop and a sharp rise, then another not-so-gradual
> drop.
>
> \[Slide.\]
>
> These are the additional four patients. Here you have a smaller drop
> but a quick rise, smaller drop, quick rise again. This patient is
> relatively stable but decreases over time. This patient has an initial
> rise, then relatively rapid drop, then a rise so it goes up and down.
> This patient is gradually dropping over time.
>
> \[Slide.\]
>
> These are the additional four patients. I will skip this one because
> it is not that clear on the screen.
>
> \[Slide.\]
>
> These are three additional patients. This patient drops, rises, rather
> sharp drop. This patient is stable here, sharp drop, sharp rise. This
> patient, gradual drop, gradual rise, gradual drop again.
>
> \[Slide.\]
>
> For the placebo patients, for the HBV DNA, we also see ups and downs
> for the investment patients. So these are fifteen patients from the
> adefovir 10 milligram arm. Again, I will not go through the details
> but you can see ups and downs here for the patients.
>
> \[Slide.\]
>
> I will just show you three patients here as an example.
>
> \[Slide.\]
>
> The last endpoint is e-antigen loss over time.
>
> \[Slide.\]
>
> This is Study 437, the e-antigen-positive study. I looked at the
> proportion of patients who become e-antigen-negative at any given
> visit. You can see the placebo arm is also gradually rising over time
> together with the other two arms also rising gradually over time.
> Actually, the 30 milligram has a separation from the placebo arm and
> then, in the end, the 10 milligram also is nearly separated from the
> placebo arm.
>
> \[Slide.\]
>
> This is the lamivudine studies. The placebo arm also gradually rises
> here. The yellow one is lamivudine 100 milligrams. There are some
> variations here but, in the end, it is separated from the placebo arm.
> However, the 25-milligram arm is here. It bounces around, but it is
> closer to the placebo here.
>
> The combination arm also bounces around, ends somewhere here, I think.
> The green one is the interferon alone. It comes in the middle here, in
> the end.
>
> \[Slide.\]
>
> This table shows the transition probabilities for e-antigen status. I
> combined all the lamivudine plus the adefovir data here. I think
> divided them into the placebo, adefovir 10 milligrams, 30 milligrams
> combined here, the lamivudine 100 milligrams and 25 milligrams
> combined here, and then the interferon-containing arms.
>
> This column will be the patients who were e-antigen-positive at
> baseline, then became e-antigen-negative before the end of the year.
> That is either Week 48 or Week 52.
>
> Let\'s look at the placebo arm first. You can see 14 percent of the
> 364 patients become e-antigen-positive somewhere during the one-year
> period of time. But, of these 14 percent of patients, that is roughly
> about 50 or 60 patients. 37 percent of them become positive again,
> also within the one-year period of time.
>
> Of these 37 percent of patients, 26 percent of them become negative
> again. Of these patients, 40 percent become positive again, and so on.
>
> So, for the three other groups which are being actively treated, there
> are a higher proportion of patients who become e-antigen-negative for
> the first time. But, afterward, roughly about 20 to 28 percent
> reverted back to the e-antigen-positive status. Of these patients, 28
> to 58 percent become negative again. Of these patients, somewhere
> between 0 to 37 percent become positive again.
>
> So some patients even changed their status four times in one year.
>
> \[Slide.\]
>
> Next I will go over the patient level correlation which examines how
> the reverse measurements on a single patient correlate to each other.
>
> \[Slide.\]
>
> I will go over this study-by-study and arm-by-arm. Each row is a
> single study. The first row is the U.S. study and this is the placebo
> and this is lamivudine 100-milligram arm. This is the
> interferon-nonresponder study and the three treatment groups.
>
> Here you see\--the curve in the middle is, again, sort of the average
> of the things, at least at each level of the HBV DNA to indicate a
> trend. For example, for this curve, we can see a slightly upward trend
> but also, on the patient level, there is lots of variability around
> this line. That is indicating some correlation but also probably a
> fairly weak correlation.
>
> In the other graphs, we can see some similar patterns here. In this
> graph, the trend is probably somewhat stronger. This one had a sharper
> rise, then is flat. But if you just look at the average, probably it
> is going to have a stronger trend.
>
> \[Slide.\]
>
> These are the other two studies for lamivudine. This is the Asian
> study and this is for the active-control study. Again, here, there is
> a slight uptrend. This is fairly hard to tell, almost flat. This maybe
> has some very minimal trend here. This has a trend. This is hard to
> tell. This has a trend here.
>
> But, still, again, you see lots of variability. Also, you can see this
> line. That is the assay limit. So the patient cannot pass that line.
>
> \[Slide.\]
>
> This is a summary of those graphs in numbers, in a correlation
> coefficient. The overall correlation coefficient is 0.3. Also, one
> star means the p-value is less than 0.05, two stars means the p-value
> is less than 0.001. So if you combine all the data, you get a
> correlation of about 0.30 which is significant at the 0.001 level.
>
> However, there are variations between the arms or between the studies.
> For the U.S. study, the lamivudine 100-milligram had a correlation of
> 0.41 and the placebo arm, 0.19. It seems to be different. For the
> interferon-nonresponder study, the correlation here is fairly strong
> at 0.62 compared to the other two arms which is relatively small at
> around 0.3.
>
> Between studies, the Asian study seems to have a weaker correlation at
> 0.22.
>
> \[Slide.\]
>
> So this is plotted for the adefovir trials. This is for the
> e-antigen-positive study. That is Study 437. This is for 438, the
> e-antigen-negative study. Here, it appears to see more clear of a
> trend. That is partially because of the range of the assay is
> broadened here. The lower limit is around here compared to the
> lamivudine, the lower limit is here. So everything was cut off here
> for the lamivudine.
>
> For the e-antigen-positive, we can see in all three graphs an uptrend
> but also lots of variation between the patients. For the
> e-antigen-negative study, the trend here\--you may see a slight trend
> here but the trend here is not apparent at all.
>
> \[Slide.\]
>
> This is, again, a summary of the graph in numbers. The overall
> correlation is 0.29. That is fairly consistent with what we see for
> the lamivudine trial at 0.30. For the e-antigen-negative study, the
> correlation is 0.09, overall it is 0.09. It is fairly small for the
> adefovir 10-milligram arm at 0.05. None of them are significant,
> whereas, for the e-antigen-positive study, the correlation is fairly
> similar and the overall is 0.34.
>
> \[Slide.\]
>
> I will now move to the correlation of the ALT versus Knodell score.
> This is, again, for the lamivudine study, the U.S. study and the
> interferon-nonresponder study. The correlation seems to be stronger
> here, at least the uptrend seems to be sharper here.
>
> \[Slide.\]
>
> These are the other studies. Again, you can see the uptrend in most of
> the graphs, except for this study here, it seems to be fairly flat.
> This has a trend but not that dramatic.
>
> \[Slide.\]
>
> This is a summary of ALT correlations in numbers. The overall
> correlation is 0.43 which, again, is significant from 0 at a p-value
> of less than 0.001. Some of the patterns are similar and some of them
> are not. For example, the U.S. study, these correlations are similar
> whereas, for the HBV DNA, these correlations seem to be different.
>
> However, the correlation here is, again, stronger for this study, for
> this arm, than the two other treatment groups. That is consistent with
> what we have seen for the HBV DNA. However, this correlation is
> not\--in the active-control study, it also has this combination arm
> but the combination is smaller there.
>
> \[Slide.\]
>
> This is the adefovir trials. Again, we can see an upward trend, up
> trend, up trend here. But, for the e-antigen-negative study, the trend
> is not clear here. There may be a slight trend here.
>
> \[Slide.\]
>
> The overall correlation is 0.46. Again, it is fairly similar to what
> we have seen for the lamivudine trial. The correlation is 0.43 for the
> lamivudine trials. Again, we see a weaker correlation for the
> e-antigen-negative study. Overall, it is 0.29. But it is significant
> here at the p-value of 0.001.
>
> For the e-antigen-positive study, the correlation is 0.52.
>
> \[Slide.\]
>
> I will digress from what we have just talked about and to examine the
> threshold issue for the viral load. In this analysis, I grouped the
> patients according to their Year 1 viral load into less than 400, 400
> to 1000, 1000 to 10,000, 10,000 to 100,000 and greater than 100,000.
> So there are five groups of patients here.
>
> Then I will combine the data for the 30 milligram, placebo and also 10
> milligram, all treatment arms. This red line is from Study 437. That
> is the e-antigen-positive study and the combined all the three
> treatment groups. It appears to be flat here up to about 10,000. These
> three groups have a similar response on the Knodell score.
>
> Here are the Knodell responses, the percent of patients who have a
> two-point improvement. For the other group\--sorry; these are patients
> who are e-antigen-positive at the end of one year. So these are
> patients who are e-antigen-negative at the end of one year. You see a
> drop here. There is a sharper drop here and then a rise.
>
> This is for the e-antigen-negative patients at baseline. That is Study
> 438. So, you have up, down, then sharp drop, then flat, started up.
>
> Here the numbers of the sample size at each point. Note that the
> sample sizes are relatively small between 400 and 100,000. So that is
> one problem that is probably making this graph difficult to interpret.
>
> There is another issue that is not apparent from the graph. When you
> further break down this graph according to the treatment arms, some of
> these patterns will disappear. For example, in Study 438, if you break
> it down, then, you can roughly get two almost parallel curves here
> whereas the placebo arm will be here and has a lower response rate and
> the adefovir 10 milligram will be here, also flat.
>
> So we don\'t see the threshold effect anymore. Overall, they say,
> because of the limitations of the data, we don\'t have a conclusion on
> this issue.
>
> \[Slide.\]
>
> Now we turn to the prediction of the correlations here. We have seen
> that the ALT and the viral load are correlated with a Knodell score,
> particularly in the e-antigen-positive group. But the correlation, in
> general, is fairly weak.
>
> A natural question is can we do better if we put several variables
> together to do the prediction.
>
> \[Slide.\]
>
> In this exercise, I incorporated the baseline viral load and the
> baseline ALT into a linear model for the change in the Knodell score.
> They are stratified by the study and also treatment.
>
> These are the predictors I considered. One is baseline Knodell score.
> One is the change of log10 ALT. One is the DAVG of the log10 ALT.
> Another one is time to ALT rebound to the 1-times upper limit of
> normal.
>
> For the DNA, I have end-of-one-year DNA and the DAVG for the DNA and,
> also, time to the nadir. That is the lowest value for the DNA. Also,
> e-antigen-negative nadir. That means the status of patients\--if the
> patient ever achieved e-antigen-negative activity. Also, the status of
> the e-antigen at the end of one year.
>
> As a reference, the model that only has the baseline log10 ALT and the
> baseline DNA has an r-square of 14 percent. So if you add to the model
> one of them each time\--if you add this one to these two variables,
> you get an r-square of 47 percent, which is quite some improvement in
> terms of precision for the prediction.
>
> But if, instead, I add this change of the log10 ALT into these
> variables in the model, I get an r-square of 29 percent. So there is
> about a 15 percent improvement here for this variable. If, instead, I
> added the DAVG for the log10 ALT, I get 27 percent here. It is fairly
> similar to the change for the ALT.
>
> For the time to ALT rebound to the one-times upper limit of normal, it
> is 15 percent so there is not much change here from the 14 percent
> reference point. For the Year-1 log10 DNA, the r-square is 20 percent.
> It is an increase of about 6 percent from 14 percent. It is a much
> smaller increase.
>
> For the DAVG of the log10 HBV DNA, the increase is 21 percent. The
> time to the nadir of the DNA is 15 percent. Not much. For the Year-1
> e-antigen-negativity, if the patient ever achieved e-antigen-negative
> in the 48 weeks or the 52 weeks, the r-square is 18 percent, so about
> a 4 percent improvement just using these variables alone.
>
> The Year-1 e-antigen status is 17 percent. It is fairly similar to the
> nadir.
>
> \[Slide.\]
>
> The previous table is for each time I added only one variable. This
> table shows what if I put in more than one variable into the model.
> The first variable I put in is the change in log10 ALT and also Year-1
> HBV DNA into the same model. I get an r-square of 30 percent.
> Remember, that even the change of log10 ALT alone, you get an r-square
> of 29 percent. So there is really no improvement, not much improvement
> adding the log10 DNA into this model.
>
> If, instead, I use the DAVG DNA replacing the Year-1 DNA, it is
> slightly better at 33 percent. I looked at some other combinations
> here, 34 percent and 34 percent. In my extreme case, I have eight
> predictors and I get an r-squared of 38 percent. It is not much of an
> increase.
>
> \[Slide.\]
>
> So, in summary, for the e-antigen-positive patients, the Year-1 HBV
> DNA and the change of ALT are associated with the change in the
> Knodell score. But the associations are typically weak to moderate.
> For the e-antigen-negative patients, the evidence is weaker,
> particularly for the HBV DNA. Multiple predictors do not improve much
> upon the change of the ALT alone.
>
> \[Slide.\]
>
> The next topic will be about the validation. The first method will be
> the trial-level correlation.
>
> Earlier, when I talked about the correlation between the surrogates
> and the Knodell score for the individual patients, the unit of study
> is the patient. Here, for this validation, the unit of study is the
> trial. So each trial, you get a treatment-effect size for, say, the
> Knodell score, for the HBV DNA or for the ALT.
>
> Then you try to go through many trials to correlation the effect size
> of each trial.
>
> \[Slide.\]
>
> Because the study unit is clinical trials instead of individual
> patients, it is important to have many trials for this analysis.
> However, we only have six studies and five of them have placebo
> controls. So we have too few trials for this analysis.
>
> One approach to address this issue is to break each study into smaller
> trials to have more trials. The way I broke this down is, first,
> according to where the study is conducted; is it Asia, is it Europe or
> is it North America. If, afterwards, if the trial is still large, I
> will break that further down according to the ethnic background.
>
> So, in the end, I have about 40 such smaller trials. The sample size
> ranges from 20 to 70.
>
> \[Slide.\]
>
> Before the validation, I have two graphs to show the response in each
> arm. First we look at the HBV DNA versus the Knodell score at one
> year. The plot graphically summarizes the treatment response in all
> studies and all treatment arms for the viral load and for the Knodell
> score. The X axis is the treatment response of the Year-1 HBV DNA on
> the log10 scale. The Y axis is the response for each trial for the
> change of the Knodell score. These blue points are from the adefovir
> trials. The yellow points here are from the lamivudine trials. The
> size of the symbols are referent to the size of the trial after
> breaking it down from those six studies.
>
> The capital letter A stands for adefovir 10 milligrams. The lower-case
> a stands for adefovir 30 milligrams. The capital letter L stands for
> the lamivudine 100 milligrams. The lower-case l stands for the
> lamivudine 25 milligrams. The zeros are the placebo arms.
>
> The M is a mixture of the lamivudine plus interferon and the F stands
> for the interferon alone.
>
> You can see here that, in this graph, the points are separated by the
> treatment arms. The adefovir 10 milligrams and 30 milligrams are
> clustered here in this region. The lamivudine, these are 100 or 25
> milligrams here. The placebo arms are here. The interferon arms are
> here.
>
> Also, you notice there is a separation between the lamivudine trial
> and the adefovir trial. This separation may be artificial because of
> the assay limit. The lamivudine trial can only show a response lower
> than this level.
>
> One thing to notice here, if you know the treatment groups, you can
> see some kind of trend, upward trend. But the trend is probably driven
> by between-treatment differences. In other words, in these trials, the
> adefovir trials, you see better response in both arms, HBV DNA and
> also on the Knodell score. But, in the placebo arms, you see a
> worsening response on both scores. That has pretty much driven the
> correlation here.
>
> \[Slide.\]
>
> This is the same plot but it is for the ALT change. One notable
> difference from the previous graph is the overlapping of lamivudine
> and adefovir arms. Both of them are now here. Both graphs show that,
> overall, the lamivudine or adefovir arms showed a better response in
> Knodell score, viral load and ALT compared to the placebo. That has
> pretty much driven the correlation here.
>
> The interferon-containing arms are somewhere in between but closer to
> the placebo arms.
>
> In the next few slides, I will go through the validation units
> measured; that is, to plot the treatment-effect size of each trial for
> the surrogate versus this Knodell score.
>
> \[Slide.\]
>
> The first two slides are for the viral load at the end of one year
> versus a Knodell score change. In this slide, we only show the
> adefovir trials and the next slide is for the lamivudine trials. The
> two drugs were not shown on the same graph because of the
> assay-limited issue.
>
> Each number in the plot stands for one trial. That is the trial we
> broke down from the six studies. So 7s are from Study 437 and 8s is
> from Study 438. Again, the size of the symbol represents the size of
> the trial.
>
> For example, this would be one of the trials which has a treatment
> effect on the Year-1 HBV DNA about 3.7, roughly there. For the Knodell
> score, it has an improvement of about 4.3 points. That is relative to
> the placebo arm.
>
> We see the range for the response for the HBV DNA is somewhere between
> a negative 1.something to 4.something indicating improvements in all
> these smaller trials. For the Knodell score, it ranges from somewhere
> between a negative 1 to a negative 5. Again, all of them are showing
> improvements. So all these trials show improvements both in the HBV
> DNA and also on the Knodell score.
>
> The red line is indicating the average. That is the same as we have
> seen before. So it indicates an uptrend, so that means that the trials
> that have a better response on the HBV DNA tended to have a better
> response on the Knodell score. But, also, you see lots of variation
> around this line which means the correlation may not be great.
>
> One measure for this kind of correlation is r-square. That is 25
> percent which is not significantly different from 0.
>
> \[Slide.\]
>
> So this is the same plot but for the lamivudine trials. The r-square
> is 6 percent here. It is not significant again.
>
> \[Slide.\]
>
> This is for the ALT. Here I combined the adefovir and the lamivudine
> trials because we no longer have the assay-limited problem. The
> r-square here is 24 percent. Again, it is not significantly different
> from 0.
>
> In this graph, it is only the lamivudine 100 milligram, lamivudine 25
> milligram, adefovir 10 milligram, adefovir 20 milligram. There are no
> interferon arms.
>
> \[Slide.\]
>
> If I add the interferon arms, the interferon comparisons are here, the
> 2s and the 4s from the interferon arm, the comparison with interferon.
> That is generally located in this corner, indicating probably not much
> response on the Knodell score in these trials.
>
> But the treatment-effect size on the ALT varies from trial to trial so
> two of these trials probably are showing worsening, actually. This
> trial is showing some kind of improvement, about 0.25 log10 ALT
> improvement. Despite this variability, because this points seem to be
> conforming to the trend that is a lower response on the ALT, has a
> lower response on Knodell score. So it is actually an increase in the
> correlation here to 33 percent, the r-square to 33 percent and the
> lower bound is 80 percent here. It is significant.
>
> So, from these four plots, we see r-square is typically is less than
> 33 percent and this is the best r-square we see among the four graphs.
> The question is why are we seeing what we are seeing here? What are
> the factors that are influencing this association?
>
> I will discuss a few factors next.
>
> \[Slide.\]
>
> One potential factors is the variability of the biopsy. This
> variability could arise in several ways. If you repeated the same
> biopsy on the same patient, you could get a different piece of liver
> that have been affected by the disease differently. Plus the same
> sample may be rated by different readers or maybe even the same reader
> reading the same sample could have different numbers at different
> times.
>
> Collectively, with-patient variation measures variability of doing the
> biopsy two or more times on the same patient at a given time by
> following the same procedure. The total variability in the Knodell
> score we observe arises from both within-patient variability and also
> the true difference between the patients.
>
> For these trials, the total variability, if you use the standard
> deviation as a measure for this variability, it is about a 3. The
> adefovir trials have slightly smaller variability.
>
> If the ideal situation, the biopsy variability is not influenced by
> the magnitude of the actual biopsy measurement, then the relationship
> can be formulated here, the observer correlation is the true
> correlation multiplied by the factor here. By true correlation, I mean
> the true biopsy. Suppose you can do the biopsy an infinite number of
> times, if you take the average and that is going to be the true liver
> biopsy.
>
> The correlation of the true liver biopsy, which is the surrogate
> endpoint, that is the true meaning of true correlation here. This
> factor is determined by the within-patient variability with a total
> Knodell score variability between the patients you have observed.
>
> So the question is, how different will be the two biopsies on the same
> patient at the same time.
>
> \[Slide.\]
>
> So I will give you some numbers to see how\--because we don\'t have
> data to say how much variability in the biopsy, so I will go over
> several different scenarios.
>
> The first case is where there is no variability. That means if you do
> the biopsy on the same patient twice, you are going to get identical
> results. In this case, the true correlation will be the same as the
> observed correlation. For the HBV DNA, it is 0.3 and for the ALT is it
> about 0.43.
>
> If you assume the correlation, the standard deviation for the
> within-patient variability is about 1.5, 1.5 roughly means that, if
> the patient\'s true Knodell score is 7, let\'s say, one would have
> about two thirds of a chance to observe a score that is between 6 and
> 8. In the other one-third of a chance, you are going to see a score
> not between 6 and 8, something either smaller or larger.
>
> If that is the case, then the true correlation for the HBV DNA would
> be about 0.35 and for the ALT it would be 0.50. In the other case, if
> you believe the standard deviation is larger, let\'s say 2.25, this
> would roughly correspond to the case where, if the subject\'s biopsy
> is truly seven points, you would have about two-thirds of a chance to
> observe something between 2 and 12.
>
> In this case, the correlation for the HBV DNA versus\--for the Knodell
> score is 0.45. For the ALT, it is 0.65.
>
> \[Slide.\]
>
> You have seen the rather weak correlations on the individual levels,
> but how does that translate into the trial-level correlation. To fix
> the idea, let\'s imagine that you have followed the same protocol,
> doing the same trial, let\'s say, one-thousand times. Among these
> one-thousand times, you are going to get a treatment effect on a
> surrogate, you are going to get treatment effects on the Knodell
> score. How will those treatment-sizes will correlate?
>
> We really cannot the same trial one-thousand times so, instead, I did
> some simulation here.
>
> \[Slide.\]
>
> This is the further study, nonresponder study. I picked lamivudine 100
> milligram plus interferon versus placebo. I put this on because, for
> this group, lamivudine 100 plus interferon, the individual correlation
> is 0.74 and the placebo correlation is 0.31. They seem to be
> different.
>
> If I repeat the trial one thousand times, you get this plot. Each
> point is one trial and the X axis is the effect size on the log10 ALT
> and the Y axis is the effect size on the Knodell score.
>
> So you can see a trend here, but also the variability is around this
> line. The correlation for this graph is 0.56. So it is somewhere in
> between these two individual correlations.
>
> \[Slide.\]
>
> This is another scenario. This is Study 437, e-antigen-positive study,
> adefovir 10 milligrams versus placebo. In this case, the two
> correlations are roughly the same in the two arms. So if we do the
> trial one-thousand times, this will be the pattern we are going be
> seeing. The trial-level correlation in this case would be 0.44. It is,
> again, somewhere fairly close to the individual-level correlation.
>
> So these two simulations show that, when you have the trials, when the
> effect sizes are similar, almost like a replicate of a single trial,
> then the trial-level correlation will be similar to the
> individual-level correlation.
>
> \[Slide.\]
>
> That comes back to what we have seen for the adefovir and lamivudine
> studies. In these trials, the effect sizes are somewhat similar,
> actually. For example, the effect size on the ALT, given only the
> lamivudine 100 or lamivudine 25 milligrams versus placebo, it ranges
> from about 0.25 reduction to 0.35 reduction. So it is a fairly narrow
> range.
>
> For the HBV DNA, in the Epivir trials, it ranges from a 0.67 reduction
> to 1.16. For the adefovir trials, it ranges from -2.5 to -3.39.
>
> So, given the similarity of the effect size between these trials, it
> would be very difficult to have a trial-level correlation which is
> much better than the individual-level correlation.
>
> \[Slide.\]
>
> Given that difficulty and the limitation of the data, I will go
> through another concept for the validation. It is called the
> proportion of the treatment-effect size explained. Briefly, I will
> call this PTE.
>
> This method has a longer history and has been used widely for HIV
> trials.
>
> \[Slide.\]
>
> Contrary to the trial-level-correlation method, which utilizes many
> trials for analysis, the PTE method can be computed for each
> individual trial. In the PTE analysis, the overall treatment effect on
> the Knodell score is decomposed into two components, the component
> that was not predicted by the surrogate endpoint and the component
> that was predicted by the surrogate endpoint.
>
> This decomposition relies on the modeling, typically linear models.
> The PET is the ratio of the effect that is considered to be due to the
> surrogate endpoint over the total effect size on the Knodell score. So
> it measures the percent of the overall effect that is probably due to
> the presence of the effect on the surrogate endpoint.
>
> Ideally, this number should be 1.0. That would mean that the treatment
> effect on the Knodell score is mediated through the surrogate
> endpoint. This method has been used for a long time but also has been
> widely debated.
>
> \[Slide.\]
>
> This table shows PTE for the year-one HBV DNA as a surrogate and the
> change in the Knodell score. The first three columns are the study
> drug name and also which study and also which treatment comparisons.
> The left column is the PTE and this is the 95 percent confidence
> interval for this PTE.
>
> Let\'s go through the e-antigen-negative study first. For this study,
> the comparison of adefovir 10 milligram versus placebo, the PTE is 15
> percent. The confidence interval is from a -8 percent to 39 percent.
> So we are not sure if there is anything that is going through the HBV
> DNA for this population.
>
> For the e-antigen-positive studies, that is adefovir Study 437 also
> all the lamivudine studies, for the 10 milligram versus the placebo
> comparison, the PTE is 65 percent. For the 30 milligram versus
> placebo, it is 78 percent. The confidence interval is 41 to
> 100 percent, 49 to 110 percent. So it appears, at least the proportion
> of effect is mediated through the HBV DNA.
>
> If you go to the Epivir studies\--first, we look at the rows in white.
> Those are the comparisons that do not involve the interferon arms. The
> numbers are 33 percent, 37 percent, 40 percent, 48 percent. The lower
> bounds range from 6 percent to the highest is 22 percent. But we also
> see that the upper bounds in three of the comparisons are less than
> 100 percent.
>
> So all this is saying that probably there is something, at least a
> fraction of the treatment-effect size on the Knodell score, is going
> through the HBV DNA at one year. But, also, definitely not all the
> effects.
>
> The green rows are the comparisons involved in the interferon arms. If
> you look at the confidence interval, it is very wide, extremely wide.
> So it is fairly noninformative for this purpose.
>
> \[Slide.\]
>
> Next we turn to the change of ALT versus the Knodell score, the same
> order. We look at the e-antigen-negative population first. The PTE is
> 17 percent but, in this case, it has a positive lower bound from 7
> percent to 31 percent. So there may be a small fraction of the effects
> that are going through the ALT.
>
> For the e-antigen-positive study, the numbers are 43 and 40 percent,
> again with a positive lower bound but, also, the upper bound is less
> than 1.0. For the Epivir trials, the numbers are 6, 5, 27, 42 and 49.
> Again, the lower bounds range from 13 to 30 percent. Three of the
> upper bounds are less than 1.0. So, again, it is showing that maybe a
> fraction of the effects on the Knodell score is going through the ALT,
> but certainly not all the effects.
>
> \[Slide.\]
>
> Finally, a summary of the presentation.
>
> \[Slide.\]
>
> First, we summarized the efficacy and described both variability
> between the patients and the variability over time for each patient.
> Specifically, we saw effects on the Knodell score and its correlation
> with the baseline Knodell score. We saw effects on the HBV DNA, ALT
> and the e-antigen loss and all three measures vary over time.
>
> For e-antigen loss, one-quarter to one third of patients cannot
> maintain the status.
>
> \[Slide.\]
>
> We studied the correlation of the e-antigen HBV DNA and the change in
> ALT versus the Knodell score. We saw that the overall correlation for
> the HBV DNA is about 0.3 and for the ALT it is about 0.45. But, for
> the e-antigen-negative population, these correlations are weaker,
> especially for the HBV DNA. It is not even certain if that has any
> correlation.
>
> Combining these various predictors did not improve the prediction
> much.
>
> \[Slide.\]
>
> The two validation measures. The first validation is the trial-level
> correlation where we didn\'t see much correlation at all. That is
> probably due to several factors. One could be partially influenced by
> the biopsy variability. Another factor is the similarity of the trials
> between the lamivudine and the adefovir trials.
>
> \[Slide.\]
>
> Finally, the PTE method which showed that maybe a proportion of the
> effects is going through the HBV DNA and also the ALT but certainly
> not all the effects.
>
> That\'s it. Thank you.
>
> DR. GULICK: Thanks.
>
> Are there one or two quick questions? We are certainly going to have
> time to discuss these so, if there are no questions at this point, as
> someone famous once said, \"It\'s lunchtime.\" It is ten of 1:00. We
> will reconvene at twenty of 2:00. Thanks.
>
> \[Whereupon, at 12:50 p.m., the proceedings were recessed to be
> resumed at 1:40 p.m.\]
>
> [A F T E R N O O N P R O C E E D I N G S]{.underline}
>
> \[1:45 p.m.\]
>
> DR. GULICK: There were a couple of members of the committee who wanted
> to ask a couple questions of Dr. Soon.
>
> Dr. DeGruttola, you had a couple of questions?
>
> DR. DeGRUTTOLA: First of all, just to make sure I understand the
> goals, the goal here is to see if we can predict at the individual
> level and at the trial level what the Knodell score or the
> histological results will show and also to see if there is variability
> in that ability to predict across different treatments and different
> groups.
>
> Dr. Soon, is that a fair statement?
>
> DR. SOON: Yes.
>
> DR. DeGRUTTOLA: So one question I have is do you see evidence of
> variability in the associations between Year 1 bDNA and Knodell-score
> change across different treatments and groups, or do you see them as
> being, although, of course, the numbers are different because of
> random variation, essentially fairly similar?
>
> DR. SOON: Unfortunately, I don\'t have the numbers for the HBV DNA but
> I do have the numbers for the ALT versus the Knodell score testing the
> significance of the homogeneity of the correlations.
>
> For the Epivir trials, the overall homogeneity of the correlations
> between the treatment groups and also between studies has a p-value of
> 0.013. That is significant.
>
> DR. DeGRUTTOLA: So that is showing that there is heterogeneity.
>
> DR. SOON: Correct. Yes.
>
> DR. DeGRUTTOLA: Which is very relevant. And for the bDNA, you don\'t
> have it, but I think that is\--
>
> DR. SOON: I don\'t have the p-values; correct.
>
> DR. DeGRUTTOLA: But I think that would be at least of interest to me
> and, perhaps, others on the committee as well to find out if there is
> variability in that association because the question is, obviously, is
> it relevant in some settings and not others to use DNA as the
> endpoint.
>
> In your discussions about the within-patient variability, I just want
> to understand the goals of those analyses a little bit further. Was
> the point there to show the way in which our ability to detect
> association between the predictor bDNA and the Knodell score degrades
> as the within-patient variability increases or were there other points
> as well, because that struck me as being very relevant to what the
> committee needs to address.
>
> DR. SOON: Your question is about if the assay variability on the
> biopsies, how that is affecting the individual-level correlation;
> correct?
>
> DR. DeGRUTTOLA: Yes.
>
> DR. SOON: We have looked at the range of values, as you have seen in
> the presentation, from with no correlation to there is some
> correlation to maybe some large correlation\--sorry; variations in the
> biopsies. That is affecting the correlations of either the HBV DNA or
> the ALT versus the Knodell score you are observing.
>
> When you have more noise in any of the measurements, that is going to
> drive the correlations lower.
>
> DR. DeGRUTTOLA: So, for example, in your table, what you were saying
> is if the within-patient standard deviation was 2.25, then you would
> need to have a true correlation of 0.45 to observe a correlation of
> 0.3? Is that the correct way to read that table?
>
> DR. SOON: That\'s correct.
>
> DR. GULICK: Victor, which table are we talking about?
>
> DR. DeGRUTTOLA: I\'m sorry. It is variability in correlation on Page
> 33.
>
> DR. SOON: Maybe you can show the slide if you know the slide number.
>
> DR. GULICK: 66.
>
> DR. DeGRUTTOLA: It is probably 66, doubling 33.
>
> DR. SOON: Slide 66, maybe. In any case, that is correct. With some
> exceptions here, the variability is homogenous across the different
> values of biopsy. Then you can say in order to observe a correlation
> of 0.3, we need a true correlation coefficient of about 0.45 for the
> HBV DNA.
>
> DR. DeGRUTTOLA: I see. Then, one final question. We saw the two
> different assays were being used, the PCR and the bDNA, I believe.
> When you plotted the trial-level data from trials that were using the
> two different assays, we saw the datapoints from the different studies
> sort of clustered. But, do you have any sense that\--and it is
> confounded because there were different both different assays and
> different drugs used in those two different studies.
>
> Do you have any sense of whether the difference between the two
> different treatments\--I believe it was interferon and
> adefovir\--whether there was truly a difference there or whether it
> was an artifact of the fact that different assays were used?
>
> DR. SOON: Dr. DeGruttola is referring to the difference between the
> lamivudine and the adefovir treatments. There is a cluster difference
> for the HBV DNA versus Knodell plot where you see a separation of the
> two clusters. It is hard to tell if that is really all due to the
> difference in assay. Sometimes, the assay difference is a contributing
> factor because, for the lamivudine trials, there is no chance for them
> to exceed the lower limit of the assay for the response whereas, for
> the adefovir arm, all the responses are below that limit of the Epivir
> trials.
>
> So, certainly, it is responsible for the separation of the two
> clusters, but it is hard to tell if it is solid due to that reason.
>
> On the other hand, if you look at the ALT plot, the lamivudine and
> adefovir arms overlap so it is sort of suggesting that maybe it is due
> to just the assay limit.
>
> DR. DeGRUTTOLA: Okay; so there isn\'t really any evidence there that
> there is a difference between the lamivudine and adefovir in these
> associations.
>
> DR. SOON: Right.
>
> DR. GULICK: I am going to suggest that we hold the rest of the
> questions because I will guess that many of them will come out in the
> discussion of the charge questions to the committee.
>
> So I would like to move this time to the open public hearing. We have
> two people that have signed up. the first is Lee Crooks from the
> Hepatitis B Foundation.
>
> **Open Public Hearing**
>
> MR. CROOKS: My name is Lee Crooks. I am here as the patient
> representative of Hepatitis B Foundation. I would like to take a few
> minutes to tell you about my experiences with hepatitis B and the drug
> adefovir.
>
> I was first diagnosed with hepatitis B in 1994. Prior to that time, I
> had no symptoms of any kind that I could recall. As my disease
> progressed and as I look back now on what people have experienced, I
> probably did have fatigue but I wrote most of it off as low blood
> sugar because I had had that problem for some years.
>
> But, after my doctor diagnosed me, he did a biopsy and said that the
> bad news was that I did have hepatitis B, and the good news was that I
> didn\'t have cirrhosis. So he put me on interferon and I was on that
> for only about six weeks. I came off of interferon because of my white
> blood cells dropping below the protocol.
>
> It seems, though, that just the six weeks of being on interferon had
> some effect because my viral load did drop and my ALT went down. So my
> physician suggested that we just track it for a while. So, for about
> three months, I had monthly lab work done and things seemed to be
> somewhat stable. He moved me to a three-month review period.
>
> At the end of that first three-months review period, he was astonished
> at the change, and not for good. My viral load had jumped dramatically
> and so did my ALT. At that time, he felt that there was nothing more
> that he could for me and suggested that I go to the University of
> Miami and see either Dr. Reddy or Dr. Schiff.
>
> So I did that. I saw Dr. Reddy. Seeing Dr. Schiff, you need an
> appointment like two years in advance. But the studies, of course,
> that are ongoing are under Dr. Schiff. Anyway, I did see Dr. Reddy. He
> did lab work. He did not do another biopsy. What he said was, with an
> ALT score as high as I had and the high viral load, that he was
> certain that I had to have cirrhosis.
>
> This is kind of surprising because, between the time I was first
> diagnosed as having no cirrhosis and seeing Dr. Reddy, no more than
> eighteen months has passed. Dr. Reddy told me that there was something
> they could do for me and that was a new drug called lamivudine.
>
> However, he didn\'t think that lamivudine would be the total answer,
> that the total answer would be to receive a transplant, which was sort
> of a shock to me because I was still bouncing back and forth with,
> \"I\'m not that sick.\" But I did go on the transplant list in June of
> 1995 and I started treatment with lamivudine.
>
> My condition did worsen. I live five hours away from Miami so I had to
> drive back and forth every couple of weeks for an evaluation. As my
> condition deteriorated, I was unable to do that drive so I ultimately
> relocated temporarily to the Miami area and I always say just in time
> because my condition got worse. I ended up in the hospital. I had
> edema and ascites and the fluid buildup was pushing through my abdomen
> up through the diaphragm and filling up my chest cavity so I couldn\'t
> breathe.
>
> I was in the hospital for seven days like that and every day I was
> tapped, and, every day, they removed two liters of fluid. So, to this
> day, I can\'t stand to see liter bottles of drinks because I think of
> all that fluid being in me.
>
> That went on for seven days straight. Dr. Reddy was very concerned
> with the possibility of infection because of sticking me every day. I
> said, \"Maybe we should put a drain in.\" He said, \"That is a
> possibility but there is even a bigger chance of infection with
> that.\" He said, \"The only real solution to this problem is for you
> to get a transplant and get it very soon.\" Two days later, I was
> transplanted.
>
> I came out of the transplant feeling better. I knew right away, as
> soon as I was alert enough, to know that I was feeling good. I
> continued on lamivudine and, for about two years after the transplant,
> everything seemed fine. Then I started having some symptoms and some
> of my numbers were going up and they determined that I had the
> mutation.
>
> At that time\--this was, like, \'97\--at that time, they thought that
> the mutation was so mild that it wouldn\'t do much damage to the new
> liver. But, as time went on, there was more and more concern that my
> new liver was being attacked.
>
> Trials for adefovir had been announced but they had not put the
> protocol together yet. Dr. Schiff, talking with Gilead Sciences, they
> approved me to get adefovir on a compassionate-use basis. I was one of
> two or three transplant patients who got that.
>
> So, in the long run, I have been on adefovir for almost four years.
> Initially, when I started with it, I had one relatively minor symptom
> and that was simply loose stools, not diarrhea but just loose stools,
> something that you are just aware of. That lasted about two months and
> then it went away.
>
> So I went on adefovir in September of \'98 and I was on 10 milligrams.
> Because I take Prograf, which is my anti-rejection medication and that
> happens to be somewhat toxic to the kidneys, there was some current
> concern about the combination of 10 milligrams of adefovir and the
> Prograf, and my dose was reduced to 5 milligrams.
>
> I have been on 5 milligrams since July of \'99 until just three months
> ago when I was moved back to 10 milligrams. My understanding of that
> was it was in order to develop a standard dosing. I don\'t feel any
> changes. I feel fine. However, my creatinine level has increased from
> 1.5 to 1.9 in the last couple of months and it is my understanding
> that that dosing change will be changed based on my creatinine
> clearance.
>
> But, overall, what I would like to say is that, when I got a
> transplant, I felt like I got the gift of life again. I came out of
> that feeling like a whole new person. I sometimes did things that I
> didn\'t used to do and I think that was probably from my donor, but
> there are no studies being done on that. I am a chocoholic now and I
> never ate chocolate before. So, go figure.
>
> So my second gift, to me, was adefovir because it was obvious that the
> way the liver was being attacked that I was going to be back in the
> same situation that I was originally. So adefovir is my second gift
> and I am very appreciative to have had it.
>
> Recently, I attended a patient conference held by Hepatitis B
> Foundation in Pennsylvania. At that meeting, I met a lot of other
> people who have hepatitis B and they were all interested in hearing me
> talk about my experience with adefovir because they are all looking
> for something like that. I am hoping that adefovir will prove to be
> the help that a lot of people in this country as well as other
> countries need.
>
> Those are my prepared comments. If you have any questions, I would be
> happy to try and answer them.
>
> DR. GULICK: Thanks very much.
>
> The next person to sign up for the open public hearing is Dr. Michael
> Wulfsohn from Gilead Sciences.
>
> DR. WULFSOHN: I am Michael Wulfsohn. I am Vice President of Biometrics
> at Gilead Sciences. We have done a lot of work in parallel with the
> agency and I would like to confirm much of what Greg has presented and
> summarize our own findings which are pretty much in sync with Greg
> Soon\'s analyses.
>
> I would like to talk about three areas, firstly baseline predictors,
> secondly, surrogate markers and, thirdly, the issue of delta with
> active-control studies.
>
> In terms of our multivariate models looking at baseline predictors, in
> both of our pivotal studies, the e-antigen-positive\--that is the 437
> study\--as well as the e-antigen-negative study, 438, we found that
> the two variables that were predictive of histologic outcome were
> baseline HBV DNA and baseline total Knodell score.
>
> The baseline ALT, although it was a univariate predictor for outcome,
> was not a predictor in the multivariate model. As you could see from
> one of Greg\'s slides, he started out with the baseline ALT and DNA
> and when he put in the baseline Knodell score, the percent of the
> variability explained when up to 47 percent. I am sure that if you
> look at the pairwise DNA in Knodell score, we will probably have
> identical results in terms of that pair explaining the most of the
> histology improvement.
>
> One thing we were also curious about in terms of baseline predictors
> is the question of who to treat. For each of these three variables, we
> found that the patients that responded least to treatment were
> patients with, as you would expect, low baseline ALT, high baseline
> DNA and low baseline Knodell score.
>
> In each of these three subsets, the low ATL, et cetera, we found that
> treatment had a significant effect on histology outcome which our
> preliminary assessment of this is we were unable to find a subset of
> patients that is not responding to treatment. These are unadjusted
> analyses and further work needs to be done adjusting these subset
> analyses for the other known predictors.
>
> In other words, when we looked at the low ALTs, we didn\'t adjust for
> Knodell and DNA but that is the next set of analyses that we will do.
>
> Moving on to surrogate markers, I certainly have, and my group have,
> found results very much in sync with what Greg found. Specifically, in
> 437, the e-antigen-positive study, DNA is a slightly better predictor,
> or, rather, surrogate, of treatment outcome than ALT. The results you
> saw earlier looked at absolute levels of DNA and that was a moderately
> good surrogate. It was, I think, explaining two-thirds of the
> treatment response.
>
> We looked at change in HBV DNA from baseline and we looked at various
> time points. The change at Week 16 appeared to be the strongest
> surrogate for histologic outcome. Specifically, the change at Week 16
> explained 100 percent of the histologic outcome where histologic
> outcome is defined as we defined it in our primary endpoint, the
> two-point improvement with no worsening in fibrosis.
>
> The confidence interval on the surrogacy of 100 percent was pretty
> narrow. I can\'t remember exactly what it was, but it is somewhere
> like 85 to 115. In the e-antigen-negative study, we got very different
> results, similar to what Greg presented. In other words, the HBV DNA
> change at Week 16 explains less than half of the treatment effect.
>
> We also observed a wide confidence interval including both 0 and 100
> indicating that there is no confidence at all in that particular
> population that HBV DNA is a surrogate for treatment effect. We don\'t
> have a rationale for these discordant findings and it is something
> that we are certainly intrigued by and we would like to see it
> confirmed in additional studies before we get too excited about it.
>
> On the face of it, it would seem that it is certainly possible that
> HBV DNA change from baseline could be a surrogate in a specific
> population, specifically the e-antigen-positives, and this would at
> least allow studies to be done in that population without histology as
> a primary endpoint.
>
> The third area I would like to talk about is the delta for
> active-control studies. The delta refers to the percent of, or rather
> the magnitude of, your treatment of effect that you are prepared to
> give up and still claim that your new drug is noninferior to some
> active control.
>
> Generally, the delta is what you would call a clinically insignificant
> amount of treatment effect. The so-called Bob Temple rule for how
> deltas are calculated is that firstly you need to know what your
> active control is contributing to the active-control group and, in
> your new treatment arm, you shouldn\'t be give any more than half of
> your active-control effect.
>
> Clearly, even giving up half of your effect may be more than you would
> want to give up and half of your effect may be highly clinically
> significant. We have looked at designing new studies based on deltas
> and, in fact, since we observed a net treatment effect of three logs
> relative to placebo, even giving up one log which is a pretty large
> amount and only a third of your treatment effect would result in
> extremely small sample sizes of the order of ten patients per arm.
>
> Clearly, we should even think of giving up way less than half of the
> treatment effect or even a third. Probably we could get by with 10
> percent of the treatment effect. Our results would only suggest that
> you would want to use this in e-antigen-positive studies, of course.
>
> Where histology is the primary endpoint, the effect of the delta
> becomes much more obvious in that, even giving up half of your
> treatment effect or\--well, even giving up half or a third of your
> treatment effect would result in enormous sample sizes. In other
> words, you would be dealing with more than 1,000 or 2,000 patients per
> clinical trial. So careful thought needs to be given to how we propose
> endpoints for clinical trials.
>
> Thank you.
>
> DR. GULICK: Thanks very much.
>
> That concludes the people that signed up for the open public hearing.
> Is there anyone else who would like to make a statement who did not
> sign up? If not, we will close the open public hearing. That puts us
> almost right back on schedule.
>
> Dr. Murray wants to lead the charge to the committee.
>
> **Charge to the Committee**
>
> DR. MURRAY: I think we had an ambitious schedule and there are
> questions that we do want to get through. I probably will reorder them
> and kind of prioritize what are the most important issues.
>
> \[Slide.\]
>
> As I said before, these are the key issues. I think, as was suggested
> by Dr. Brown, from what the industry was interested in, clearly
> selection of controls, active versus placebo and then the choice of
> primary endpoint. I think we will try to address these questions which
> I will read off to you in just a moment.
>
> Probably, when talking about choice of primary endpoint beyond that
> primary-endpoint assessment, what kind of other long-term follow-up
> data collection would you think that is essential.
>
> Just a couple of things that I did want to get through. First of all,
> I wanted to thank all of the pharmaceutical sponsors for their
> submissions. They did help us greatly in planning for this meeting and
> in preparing the backgrounder.
>
> We also got one additional analysis from collaborators at Triangle
> looking at a meta-analysis of HBV DNA as a surrogate for histology
> outcome. I did want to show that. This is an article that has been
> submitted for publication and there was one important figure there
> that we have gotten permission from Triangle to show.
>
> So if you could skip a couple of slides.
>
> \[Slide.\]
>
> There was a meta-analysis that was done from research from looking at
> all of the studies in the literature, a pretty thorough list of
> prospective studies. For the particular analysis looking at HBV DNA
> and histology, several studies were selected.
>
> Actually, go back one slide.
>
> \[Slide.\]
>
> This is an article by Drs. Mommeja-Marin, Mondou, Blue and Rousseau
> looking at serum HBV DNA as a marker of efficacy during antiviral
> therapy for chronic hepatitis B infection.
>
> \[Slide.\]
>
> Five studies with several treatment arms including lamivudine at
> several doses, famcyclovir at a couple of doses, placebo, and
> lamivudine and interferon in both e-antigen-negative and
> e-antigen-positive subgroups in this last study
>
> \[Slide.\]
>
> On your X axis here, each of these treatment arms from these five
> studies, so there are eleven or twelve datapoints here, were plotted.
> X axis is change in median viral load from baseline. The Y axis is the
> change in histology activity index and the necroinflammatory score.
> This data was reported in these studies.
>
> For this correlation, I guess the datapoints at the right upper side
> of the graph are the lamivudine and interferon. In the middle, some
> lamivudine arms. In between, the famclyclovir arms and, kind of down
> near the ordinates, are the placebo arms.
>
> In this particular analysis, this meta-analysis, there was a
> relatively good correlation, a good fit of the data, between changes
> in viral load and histology grading with a pretty good r-value here
> that was highly statistically significant. So, in addition to the
> analysis of the datasets from adefovir and lamivudine, we did look at
> a lot of other data and, in fact, I want to thank the authors of this
> particular publication, I guess, for submission in reviewing the
> literature in this regard. That was also very helpful.
>
> Let me see if I can prioritize the questions
>
> \[Slide.\]
>
> I think that, if we have time, we will deal with the patient
> population issues. These are what would be the essential patient
> populations for study.
>
> \[Slide.\]
>
> So these are Questions 1 and 2. Let\'s go on to the next section here.
>
> \[Slide.\]
>
> Control arms. We wanted you to discuss the role of the following
> controls in the compensated liver-disease group, placebo controls,
> delay of initiative treatment and for what duration would be
> appropriate, if an active control, lamivudine or another antiviral
> drug, I guess and, if monotherapy is appropriate for drugs like
> lamivudine or other antivirals, or another choice of control arm could
> be interferon.
>
> \[Slide.\]
>
> We also want you to discuss controls for patients with decompensated
> liver disease or those who have failed previous regimens. So I think
> we will have you address Questions 3A and B first.
>
> \[Slide.\]
>
> Then, as far as study endpoints and timing of the evaluation, we want
> you considering the patient populations in Question 1 and the
> information presented today and the necessity that endpoints for
> registration be clinically meaningful. Please answer the following.
> Here is where they are divided up into a, b and c.
>
> Which endpoint, or combination of endpoints, should be the primary in
> clinical trials. Please discuss histology, serologic, meaning
> seroconversion, biochemical, meaning ALT, and virologic, meaning HBV
> DNA. In addition to the choice, of course, the timing is appropriate.
> We saw yesterday where, with longer-term data, that there was more of
> a viral-load decrease and a higher seroconversion rate going out from
> 48 to 72 weeks.
>
> So, when should the assessment of the primary endpoint be made, b. And
> list the most appropriate secondary endpoints and try to rank order
> them in order of importance.
>
> For histologic endpoints, what is the preferred method of histologic
> scoring? I might say that the endpoint, I think, for lamivudine was a
> two-point change in Knodell score. That was modified for the adefovir
> development program to include no worsening in fibrosis. Then,
> yesterday, we saw that actually, by looking at a fibrosis score that
> could discriminate different levels of fibrosis a little bit better
> than the Knodell score that changes in fibrosis could be visualized
> within a year. So we might want you to address that based on data you
> have heard yesterday and today.
>
> For virologic endpoints, which assay is best suited for clinical trial
> and what do you think the most appropriate cutoff for HBV DNA
> suppression should be, 10^5^ which is kind of based on the assay limit
> of some of the other assays.
>
> I think we will leave off, should viral genotyping be done and why at
> this point, unless somebody specifically wants to address that.
>
> For patients with decompensated liver disease, please discuss the
> feasibility, validity of the following endpoints. These are some of
> the endpoints that Dr. Lok and others had listed on their slides;
> mortality, Child-Pugh, MELD score, time to transplant or occurrence of
> liver-disease complications.
>
> So I think those are the questions. The endpoint and the controls that
> you are going to address in your discussion, if you can, of the
> endpoints, also address, beyond the assessment of the primary
> endpoint, what else would you like to see in longer-term studies.
>
> The primary endpoint could occur at 48 weeks but it should not be
> limited to that. Maybe 72 weeks is better. Maybe a shorter time period
> is better. For studies of HIV and hepatitis B, 48 weeks has been
> arbitrary so don\'t feel like you have to be limited to that time
> point.
>
> Why don\'t you go back, then, to Question 3a and 3b, which deals with
> control arms.
>
> DR. GULICK: Thank you.
>
> **Discussion**
>
> DR. GULICK: The first topic we are going to take up as a group, once
> again, is the control arms. Let\'s start with, discuss the role of the
> following controls in the compensated liver-disease group; placebo
> controls, monotherapy with lamivudine, interferon. I suppose we could
> add adefovir to that list at this point.
>
> Who would like to start? Compensated liver disease, controls for
> future studies. Thank you, Dr. Sherman.
>
> DR. SHERMAN: There are several competing issues in trying to make a
> decision about the use of controls and whether placebo controls are
> indicated in the compensated patients. Clearly, the use of
> placebo-controlled study is the most satisfying for a clinical
> trialist in terms of trying to make a determination about efficacy of
> an agent.
>
> You also have the problems related to the natural history, as you
> heard this morning, of hepatitis B, that there is some degree of
> variability in certain endpoints, particularly in HBE conversion
> associated with spontaneous occurrence of that in the untreated
> control arms and that that occurs at different rates and we are not
> completely sure what controls those rates.
>
> One of the things may be the duration of chronic infection in an
> individual patient. Patients that have been chronically infected for
> many years are going to be less likely to spontaneously convert than
> one that was infected four years ago and became a chronic carrier.
>
> So, for endpoints that include the serologic parameters, it seems that
> we really are still forced to use control arms that are
> placebo-controlled.
>
> The other endpoints including DNA and use of histology
> characterization may not require that as much at this point. So I
> think, that to answer this question, we are really going to have to
> first answer what do we define as the key endpoint for response in
> these patients.
>
> Ethically, it is now getting more difficult to take compensated
> patients and give them placebo when you have determined that they have
> an activity of disease that is reasonable to merit treatment. Part of
> that is related to the ease of administration and the relative
> tolerability of the drugs that we currently have available. So it both
> gets hard to find the patients and, when you sit and face that
> patient, it is very difficult to say, \"I think you should be on a
> placebo control.\"
>
> So I think that, really, the discussion of this is related first to
> the discussion of the endpoints that we will use and to choosing
> endpoints that may not be as determinate or as variable when we decide
> to use an active control rather than a placebo control.
>
> DR. GULICK: Let me suggest that the endpoint question we are certainly
> going to get to next. Let\'s try to stay with the control question
> although I appreciate your point, that it may differ for different
> endpoints.
>
> Dr. Schapiro?
>
> DR. SCHAPIRO: Actually, to continue that thought, looking also at the
> other options of delaying therapy, since we are having trouble
> deciding how long we have to treat, I think we are going to get,
> again, into the same problem and I think, once again, until we really
> define how long we are going to have to treat delaying, let\'s say, a
> year but then, again, that patient starts therapy, we are not going to
> be able to do a comparison.
>
> So I think that is going to make that option very difficult and I
> think, again, if there is a finite number of biopsies we can do on a
> patient, and I think, as the consensus is that you do have to do
> biopsies, it is going to get very, very difficult to take those
> options.
>
> I think, although those sound like possibilities, I don\'t think that
> we will be able to do any of those in trials.
>
> DR. GULICK: Would others like to weigh in on either placebo controls
> or the option of delaying treatment, delaying active treatment, being
> randomized to that?
>
> Dr. Hoofnagle?
>
> DR. HOOFNAGLE: Well, I think this has been an ongoing problem for a
> long time, the use of placebo controls in studies of hepatitis B when
> there are licensed treatments for hepatitis B. The issue is what is
> the standard of care? Are you not following the standard of care when
> you enroll a patient in a trial and they are going to get a placebo
> for a year and have two liver biopsies.
>
> The trouble is the standard of care hasn\'t been clear as we kind of
> made out to you today. There are many people who don\'t think
> interferon should be used in anyone. There are people like us at the
> NIH who don\'t enroll patients into nucleoside or nucleotide studies
> unless they have failed interferon or refused to take it.
>
> So, it is kind of based upon what you think the standard of care is.
> But I think we heard today early results from a study in China using
> lamivudine in compensated cirrhosis that the advisory board told them
> to stop because there was evidence of benefit.
>
> So how could you enroll a patient with cirrhosis on liver biopsy into
> a trial where there is a placebo arm. I agree. It is become more and
> more difficult and I think if patients are to be treated with a
> placebo for a year, there has to be some cutoff of clinical severity
> to allow for that. That is my personal feeling.
>
> I agree about long-term therapy, but maybe for mild disease on biopsy.
> I kind of agree that it might be worthwhile kind of wading through the
> results of the study before you really commit them to a long-term
> therapy. But in a patient with bridging fibrosis or with cirrhosis, I
> think we should be concerned that they not be treated with one of the
> three agents that will be available after the next couple of months,
> we think, at least.
>
> DR. GULICK: Dr. Stanley and then Dr. Mathews
>
> DR. STANLEY: I just want to concur with that. I think we have
> now\--and I am going to separate them. You have got interferon which
> is one mechanism of action. Now you have got two antivirals that we,
> by voting for them, have said are effective. If you have made the
> decision that this patient likely needs to be treated, then how do you
> randomize them to a non-treatment arm.
>
> And I have some concerns about what you said, Dr. Hoofnagle, about,
> then, maybe they are the mildest ones. Now you are skewing your arms
> and they are not going to be equal arms for the treatment arm and the
> placebo arm, and how do you do that blinded, anyway? So I just think
> we are in an age where we can\'t deny treatment to the patient if the
> decision has been made that they ought to be treated.
>
> DR. GULICK: Dr. Mathews?
>
> DR. MATHEWS: It might be useful to draw a distinction between the
> phase III trials for long-term efficacy and earlier trials to look for
> drug activity because, in my mind, it might be justifiable, at least
> in e-antigen-positive patients if you were going to use a placebo
> control with short-term follow up to look for virologic response
> since, in both the lamivudine trial and the adefovir trials, the
> initial virologic responses seemed to be very rapid.
>
> But in the longer-term efficacy trials, which, obviously, would be
> studying the development of resistance also, I agree that placebo
> controls are problematic for the same reasons others have mentioned.
>
> DR. GULICK: Dr. Sun and then Dr. Lok.
>
> DR. SUN: I agree that the fact that there are available drugs and even
> available drugs that have been shown to have benefit weighs into the
> consideration, but I don\'t think those automatically negate the
> possibility of doing placebo-controlled trials as long as you can
> articulate a downside to therapy.
>
> I think that we know that there are known downsides and potential
> downsides related to all of the drugs that are available, toxicity,
> long-term outcome and resistance. So if you can reasonably define a
> population in which there is a risk-benefit to be had with or without
> therapy, I think that you can proceed.
>
> I would just refer us all back to HIV where, given where the treatment
> guidelines are today, you could do a placebo-controlled trial in
> patients that are HIV-positive that have high CD4 low viral load. That
> might not have been possible a few years ago.
>
> DR. GULICK: Dr. Lok?
>
> DR. LOK: To some degree, I agree with what has just been mentioned. I
> think, in general, you want to have placebo-controlled trials because
> that is cleanest and because hepatitis B, unlike hepatitis C, does
> have these spontaneous variations.
>
> It is becoming more and more difficult to do placebo-controlled trials
> because of all the reasons that were mentioned and with approval of a
> second orally administered drug, that will make it even more difficult
> to enroll patients.
>
> But all this is predicated on the study design, what patients you are
> going to enroll, how long the patients are going to stay in the study
> and what involvement is required of the patients. So, for example, I
> agree that, phase II clinical trials where you just are doing a
> dose-response study or where you are testing only a very limited
> duration, it is still possible to still include some placebo controls
> because there you are looking at a much shorter duration and you are
> deferring treatment for a very short duration of time.
>
> The phase III clinical trials are more problematic because you are
> talking about at least one year. If we still want to use histology as
> an endpoint where you are going to do paired biopsies, it is very hard
> to actually tell a patient, \"You can be enrolled into the trial, get
> randomized to placebo. We are going to do two biopsies and it is going
> to be a year,\" when, in fact, you can go to any doctor and get
> treated right now.
>
> It also is dependent on whether we are going to stick to selecting
> patients with moderate to severe disease to be enrolled into clinical
> trials or whether we will continue to have, for example, in the
> e-antigen-positive patients, allow people with normal ALT who
> basically won\'t benefit from the treatment anyway.
>
> For those patients with very mild disease and who are not going to
> progress in a short period of time, deferring for a year is, perhaps,
> not as critical. But if we decide that the treatment trials should
> cater to patients with more severe disease, then deferring becomes
> more problematic.
>
> DR. GULICK: Dr. DeGruttola?
>
> DR. DeGRUTTOLA: I think the issues about whether to choose placebo
> control or delayed treatment would depend, obviously, on the standard
> of care as has been mentioned. But I think it also depends on the
> scientific question that is being answered.
>
> It might depend on whether the goal was to do an equivalence trial to
> show that a new treatment was equivalent to some other treatment but,
> perhaps, had some other benefit or whether you were planning to do a
> superiority trial where you are showing that a new treatment is
> superior to what is currently available.
>
> I think it partly depends on what the standards of this committee and
> the FDA will be about new treatments, do they only need to be
> equivalent to what is available or do they need to be superior in
> terms of toxicity or resistance profile to what is currently
> available.
>
> So I think that this design question is going to be influenced by the
> overall scientific question.
>
> DR. GULICK: Could we have some comments on the possible act of control
> arms, assuming that that is\--certainly, that is a possibility. So, to
> consider lamivudine as the active control, interferon, or adefovir as
> the active control in a new study.
>
> Dr. Lok?
>
> DR. LOK: This is a relatively simple question because, if the new
> treatment that you are looking at is an orally administered, one pill
> a day, your control should be very comparable, since, when we look
> down the pipeline, that is what we are going to get mostly. So you
> would not be using interferon as a control where it is going to be
> parenterally administered with a completely different side-effect
> profile.
>
> There are certainly ongoing trials where lamivudine is used as active
> control. The question that is going to come up in the future would be,
> now that there would be adefovir, should lamivudine be the active
> control or should adefovir be the active control.
>
> This is going to be a key thing in terms of talking about superiority,
> what is the question that is being addressed. In some ways, using
> lamivudine as an active control, if you do the study for long enough,
> it is easy to show a difference because of the issue of drug
> resistance. So, whereas, at one year, it is going to be hard to
> actually show a significant advantage, but if the new drug has very
> little issue of drug resistance, by two years, you would be able to
> show an advantage.
>
> However, if eventually we choose adefovir, for example, as an active
> control and it continues not to have problems with resistance, then it
> would be very hard to actually show a difference or superiority.
>
> DR. GULICK: Dr. Block?
>
> DR. BLOCK: I was just going to say that it will depend on what the
> mechanism of action of the drug to be tested is and the endpoints to
> be used, really echoing what Dr. Lok was saying, that if this
> committee would anticipate a time when new immune modulators will be
> used, that would require\--at least until clear endpoints are decided,
> that would require one kind of active control arm whereas antivirals
> that work against the viral polymerase would require another one, and
> you can anticipate using resistance as a factor. So it will depend on
> the study. I imagine the committee would have to anticipate that.
>
> DR. GULICK: Other thoughts on choices of active control arm? Dr.
> Hoofnagle?
>
> DR. HOOFNAGLE: We have a lot of statisticians here but I don\'t see
> much wrong with using historical controls. You have a large amount of
> data from Glaxo and Gilead on non-treatment for a year and two liver
> biopsies. So you know what happens in a year.
>
> You will say, the patients we enroll next year are not going to be the
> same, but you can also do these multivariate analyses where you look
> at the determinants of outcome or the predictors of what will happen
> and can adjust for these. This is exactly what the MELD score is all
> about and how that can be used as a control in treating patients with
> decompensated liver disease.
>
> The MELD score predicts the rate of death, decompensate and death,
> given a patient with decompensated liver disease\'s rate of death. So
> one can use the MELD score to predict, align the estimate rate of
> liver transplantation or mortality and use that as the control.
>
> So I think the data that you have is very valuable. I guess it now
> belongs to the FDA and you can use it in the future, but I am sure
> that Glaxo and Gilead would also be willing to allow you to mine this
> very valuable information.
>
> DR. GULICK: Dr. DeGruttola.
>
> DR. DeGRUTTOLA: Let me comment on that point because I think that it
> is certainly true that you can try and do statistical adjustment for
> differences in populations when you do historical controls. But I
> think the issue that you have to be able\--I, personally, think you
> need to be able to explain most of the variability in the response in
> order to be able to do that with a fairly high degree of assurance
> that you are going to get the correct answer because historical
> controls are notoriously problematic.
>
> I think we saw, from some of the analyses that Dr. Soon presented,
> that it is difficult to capture most of the variability in the
> responses. So I think that we have to be cautious about believing that
> we understand mechanisms of disease well enough so that we can
> properly adjust in a statistical model for differences among
> populations and get valid responses.
>
> I think it is a very valuable thing to do to try and understand the
> data processes and mechanisms of action of drugs and I think it is
> great secondary analyses. As primary analyses have concern, the great
> advantage of randomization, of course, is that it adjusts for
> confounders you know about and it adjusts for confounders you don\'t
> know about.
>
> It is always the things that you don\'t know about that I think we
> need to be concerned about.
>
> DR. GULICK: Dr. Wong?
>
> DR. WONG: I guess, just on that last point, we have seen a few studies
> here within the last couple of years that used historical controls
> some of which were done really with exhaustive care. But I think the
> consensus around the table every time is that those studies have been
> unsatisfactory for a number of reasons.
>
> They just weren\'t as believable as they should have been. So I,
> personally, would counsel that we accept or advise acceptance of
> historical controls only in situations where there is a profound
> ethical reason not to do it any other way, such as, for example\--I
> mean, you could probably make a very good case that, in the
> decompensated patients with advanced cirrhosis who are expected to die
> at a certain defined rate, that a placebo-controlled study in that
> group almost surely would be unethical.
>
> But, on the other hand, in the patients with compensated chronic
> hepatitis B, we have seen evidence, I guess, for three different drugs
> now, that, at an assessment of one year, we can demonstrate a benefit
> of therapy. But I haven\'t seen any evidence except just what we heard
> from Jeff about the cirrhosis study that there is any evidence that
> any group of patients needs to be treated now as opposed to in several
> months or maybe one year.
>
> Until we have evidence that treatment really must be immediate, I,
> personally, would be pretty reluctant to rule out having a placebo
> group. Now, that is not to say that the best design for a particular
> question might be a comparative study with an active control group.
>
> But I, also, wouldn\'t be willing to say that we can\'t do
> placebo-controlled trials in hepatitis B. I haven\'t seen any evidence
> that would suggest that.
>
> DR. GULICK: Let me try to sum up what we have said about the role of
> controls in compensated liver disease; consensus that controls
> continue to be important particularly because of the natural history
> and variability of the disease. However, people thought the controls
> may actually be different with different endpoints or different
> severity of the disease. You might think of mild patients differently
> than moderate or severe.
>
> Late in the conversation, what about the issue of historical controls.
> We heard some of the traditional debates about the acceptability of
> that.
>
> Considering placebo controls; a consensus forming that it is less
> desirable, given that we have current approved effective options for
> treatment. However, it was noted that the standard of care is quite
> unclear, that, perhaps, there is a risk-benefit ratio that needs to be
> concerned with traditional elements of effectiveness versus toxicity
> resistance and long-term results of these.
>
> The analogy was made to HIV disease regarding the long-term pros and
> cons. Pragmatic issues about the fact that these drugs are available
> so it might be difficult to enter someone into a placebo-controlled
> trial when they could certainly get an effective treatment from their
> physician.
>
> Then some thoughts that, in some cases, placebo controls might be
> okay, particularly short-term use, particularly in patients with early
> disease. The thought was that may be a phase-II-like study would be
> more appropriate for a placebo control because it is of shorter
> duration.
>
> In terms of the strategy of delaying treatment, the big question is
> how long. We don\'t have good data, or there is as lot of uncertainty
> about how long it is appropriate to delay. The cutoff, or the actual
> time period, is critical, no consensus on what that might be. Again,
> this might be an appropriate strategy in mild disease.
>
> So then considering active control, the basic issue is what is the
> standard of care. There is not a good answer for that. Dr. DeGruttola
> brought up the point that you have to think about equivalence versus
> superiority. Others brought up very pragmatic issues about which
> choice of active control you make. It might be based on the mode of
> administration or the mechanism of action or the endpoint that you are
> trying to look at.
>
> With the three specific agents that we talked about, interferon,
> probably not the best choice given its parenteral administration and
> unique immunologic mechanism of action. Lamivudine is the current
> standard of care, at least it is being used as an active control in
> some studies although the point was made that resistance, of course,
> is an issue with this drug, particularly long-term.
>
> Adefovir, thought to be as suitable a control as lamivudine, might
> have the potential benefit of less resistance although Dr. Lok made
> the point that, perhaps, you couldn\'t detect a difference as easily
> with that agent.
>
> Let\'s move to the second part of the question which is what is the
> best control for patients with decompensated liver disease. That is
> one group. Or those who have failed prior regimens.
>
> So let\'s take those two separately. What is the optimal control for a
> patient group with decompensate liver disease for a new agent.
>
> Dr. Lok?
>
> DR. LOK: I think that decompensate cirrhotic patients, it is very hard
> to really have controls. Certainly, not placebo controls. I just
> don\'t think that, ethically, it is possible\--you are not going to
> get through any IRB so you can forget about doing the study.
>
> The question is whether you can have active control. For example,
> lamivudine has been used for these patients for several years now.
> Whether we can use lamivudine as an active control or whether we will
> just say study a new drug on its own and compare the patients based
> on, as Dr. Hoofnagle pointed out, predictions based on model\--based
> on other historical studies. But I don\'t think the placebo control is
> going to be a viable option.
>
> DR. GULICK: Dr. Englund?
>
> DR. ENGLUND: I feel that it is quite clear that in the decompensated
> liver disease that they need active control and that any other step
> would be unethical and unable to be done, and that it a perfect
> situation to actually be investigating the questions and get answers
> in a shorter period of time than we might even be able to get in our
> uncompensated liver disease.
>
> DR. GULICK: Dr. Mathews?
>
> DR. MATHEWS: Again, I think it is going to depend on what other
> options the patient has and the toxicity profile of the drugs,
> particularly with nucleoside analogues which might have the potential
> for mitochondrial toxicity. There may be a subset of patients where
> actually no treatment would be preferable to known treatment with
> certain potentials to worsen the patients.
>
> So, while, in general, I agree with that, there are circumstances
> where I think no treatment compared to a new active drug might be an
> ethical option.
>
> DR. GULICK: Other thoughts on the decompensated liver-disease group?
> Dr. Wong?
>
> DR. WONG: Can we just ask our hepatology colleagues, is it generally
> accepted that 3TC is effective in this situation and is that the
> current standard of care?
>
> DR. HOOFNAGLE: Yes; that is the generally accepted view and, in view
> of the data of the so-called Fontana study where survival is excellent
> in decompensated patients, after they get through the first six months
> of treatment. The treatment for decompensated liver disease is liver
> transplantation, referral for liver transplantation. So that really
> should be the first act.
>
> Now, there is a downside to the use of lamivudine in decompensated
> liver disease and that is, okay, you treat a patient. Let\'s say they
> get a little bit better and they hang on, they don\'t need a
> transplant right away. But, a year later, or two years later, they
> develop viral resistance and they end up with high levels of virus and
> then they need liver transplant.
>
> The risk of reinfection after liver transplant is directly related to
> the level of virus that you have when you go into transplant.
> Reinfection can be prevented by high doses of hepatitis-B
> immunoglobulin. But, of course, there is a limitation. The limitation
> is high levels of virus. So, if you have a patient with lamivudine
> resistance going into liver transplantation, he has a strike against
> him, right there.
>
> This would have been the advantage, if you know when the patient is
> going to get a transplant, to start the lamivudine maybe four months
> or six months ahead of time and not two years ahead of time. But you
> never know when you are going to get a liver transplant unless you are
> doing living-donor liver transplant. So this is a real problem and
> this is actually where a major use for adefovir will be, in this
> situation of lamivudine resistance before transplant.
>
> Anna knows a lot about this. What proportion of patients coming to
> transplant, at the time of transplant, have lamivudine resistance? It
> is probably a very high rate.
>
> DR. LOK: It is a high rate and it is increasing. Like it or not,
> lamivudine is widely use in practice for patients with decompensated
> cirrhosis although we try to educate gastroenterologists who refer the
> patients to us for liver transplant. We have no control over when
> transplant is going to occur. Everyone has to wait for a certain
> period of time.
>
> As you see the patients deteriorating while they are on the waiting
> list and you have a treatment that could temporize things and
> stabilize the patient, it is impossible to say, \"Well, I\'m worried
> about something bad is going to happen to you a year from now when you
> develop resistance.\" If the patient is going to die in three months,
> why do we worry about something that is going to happen in twelve
> months?
>
> So, in some ways, you are compelled to put the patients on treatment.
> It has been a very effective treatment for patients who come to you
> who are not beyond the point of no return and they get stabilized and
> improved for a while.
>
> But then, after a period of time, we now have to deal with the issue
> of worsening of liver disease as a result of resistance. So I think it
> is hard to do a placebo-controlled trial. This is the situation where
> we will have to say what actually is the right active control. Maybe
> lamivudine is not an appropriate active control in this situation
> because resistance is almost invariable.
>
> Unfortunately, although there is an enormous amount of data of
> adefovir as a salvage therapy for those patients, we really don\'t
> have any data on adefovir as a first-line treatment in those patients.
> Is adefovir the right first-line treatment for that subset of
> patients? We really don\'t have any data.
>
> What I am anticipating is going to happen is that, once it is
> approved, there would be many different people doing their own little
> trial on their own one patient.
>
> DR. GULICK: Dr. Hoofnagle?
>
> DR. HOOFNAGLE: I think, before you know it, what you will really be
> dealing with here is the controls for patients with decompensated
> liver disease and lamivudine resistance. That is what is going to
> happen. There is not much control that we have over it.
>
> DR. GULICK: So let\'s consider that, then, which is the second part of
> the question, what to do with lamivudine-experienced patients, what is
> the optimal control for them. Is it worth considering
> interferon-experienced patients as a separate group? It sounds like it
> is probably not, given where we are today.
>
> DR. HOOFNAGLE: They are a little bit different. But, if you have a
> controlled trial, you can stratify for previous therapy. I think you
> have to include people who have previously received interferon in
> registration trials. But that is one of those things that probably
> should be stratified for in the randomization.
>
> DR. GULICK: Sure. I didn\'t mean to be unclear.
>
> Let\'s focus, then, on what is the appropriate control in the
> lamivudine-experience group. So you are testing a new agent in the
> lamivudine-experienced group.
>
> DR. LOK: This is a difficult question. Until now, a lot of the
> recommendations have been to leave the patients on lamivudine. So that
> is how we are managing most of these patients because, unless you can
> get the patient into a clinical trial, your option is either to take
> the patients off lamivudine and hope for the best or leave them on
> lamivudine and also hope for the best.
>
> Either way, you sort of have to able to pray and pray effectively. But
> now, as the scene changes, it gets a little complicated because you
> now have another new drug comes along. Like it or not, there is
> another drug that we haven\'t been mentioning but is widely use in the
> community already and that is tenofovir because it has become
> available as an HIV treatment for several months.
>
> For physicians in the community who do not have access to a clinical
> protocol and access to adefovir, people have heard about it, read
> about it and have put patients on it. Hey; if you have a patient who
> is dying and they cannot get into a clinical trial, that is going to
> happen.
>
> So it gets complicated now that you have more options. So you can
> leave the patients on lamivudine. You can use adefovir as a control. I
> guess tenofovir is somewhere as an option, although we have far less
> data on it.
>
> Of course, one of the issues has been when you add on a new drug, do
> you need to leave the patients on lamivudine or can you take the
> patients off lamivudine and get your hands on some of those data. I
> wasn\'t here yesterday. I wasn\'t sure if they showed all that data.
> But the data would suggest that perhaps you can just stop lamivudine
> and add the patients on adefovir.
>
> So, as a third drug comes along\--for example, with entecavir\--if
> they want to do a study like that, should they be comparing against
> adefovir? Should they be comparing against lamivudine? Again, it comes
> back to the question that was asked; do you want to show superiority?
> Do you want to show comparability because, if you want to show
> superiority, comparing it against a drug like adefovir that has
> already been shown to be effective against lamivudine-resistant virus,
> I think it will be very hard to show superiority.
>
> You are lucky if you can actually show that there is some
> comparability. So I don\'t know. I don\'t know what the right answer
> is.
>
> DR. GULICK: Let me push you a little bit on this. Is it ethical today,
> given yesterday\'s meeting, that a trial is designed of
> lamivudine-experienced patients with a new drug and they are
> randomized to continue lamivudine as one of the arms of the study? Is
> that an appropriate study at this point given what we saw with
> adefovir yesterday?
>
> DR. LOK: I think it would be inappropriate, particularly in patients
> with decompensated disease. In patients with decompensated disease who
> are very fragile, in patients with recurrent hepatitis B
> post-transplant at home, if they deteriorate, the outcome is very
> serious.
>
> I think to leave them on lamivudine or to randomize them to continue
> to stay on lamivudine would be inappropriate.
>
> DR. GULICK: Again, I will push you\--and it doesn\'t have to be you,
> Dr. Lok, but thanks. Suppose it is a person with compensated liver
> disease who is lamivudine-experienced. Again, you have a new drug and
> what is the appropriate control arm there? Is it okay the randomize
> that group to lamivudine versus the new drug? Anyone else can chime in
> also.
>
> DR. HOOFNAGLE: There is this evidence that patients with lamivudine
> resistance have a somewhat milder course than patients with the wild
> type that, despite resistance, there is an improvement of the course.
> So, in that situation, patients with lamivudine resistance, I think a
> control trial of placebo versus adding the second drug is reasonable
> with suitable ways out if there is evidence of deterioration.
>
> Some people\'s lamivudine resistance\--I think they fall into two
> categories, those who have a continuing effect of lamivudine\--their
> levels of virus are lowish and they usually have minimal enzyme
> elevations or normal enzymes\--and those who really kind of\--the
> lamivudine-resistant gets nasty and these people have very high levels
> of virus, close to where they started and very active disease.
>
> That is the group that probably need to be taken off of lamivudine,
> needs to be taken off of them. There have been reports of virus that
> grows\--that replicates better in the presence of lamivudine than
> without lamivudine, lamivudine-dependent strains. I think that is the
> situation where you see very bad disease, I suspect.
>
> So I think it is appropriate, with sufficient ways of getting out if
> the patient deteriorates, breaking the code, transferring them,
> calling it a failure, and so forth, to use a placebo in
> lamivudine-resistant disease.
>
> DR. GULICK: Dr. Goldberger?
>
> DR. GOLDBERGER: I just wanted you to clarify. When you spoke of
> lamivudine-experienced, were you implying that those were patients no
> longer being adequately treated by it or were they simply patients who
> had been on it for some period of time?
>
> DR. GULICK: I didn\'t make that distinction. I guess that is what came
> up in the fact that some people actually may still be benefitting or
> have benefitted from lamivudine versus those with frank resistance.
> Clinically, sometimes maybe you don\'t know the difference between
> those two groups. So I was intentionally vague about that.
>
> Dr. Sherman?
>
> DR. SHERMAN: Going back to the decompensated lamivudine-resistant
> patient, I think that, based on the data that was seen yesterday and
> the discussions, it is going to be very, very difficult to have any
> patient that you don\'t choose to use adefovir in that setting at this
> point versus, perhaps, another agent.
>
> In that group of patients, we also recognize, based on the data
> yesterday, that that is the group that probably presents the highest
> risk for complications from renal toxicity and, therefore, the bar
> today is adefovir as the standard comparator for that group. Someone
> else will have to show, perhaps, equivalence.
>
> If someone comes in for a specific identify saying, \"I want to test
> this drug in decompensated lamivudine-resistant patients,\" then the
> bar today is adefovir and a comparison of equivalence and, perhaps, a
> better toxicity profile. That is where we stand right now and, yes,
> people may put people on tenofovir but, if you are doing a formal
> study, you have to make a choice and the choice is the drug that is
> approved for the hepatitis-B indication.
>
> DR. GULICK: Let me see if I can summarize where we are. The situation
> controls for decompensated liver disease is quite different for with
> compensated liver disease. There was a consensus that controls are
> desirable in this group. Dr. Wong made the comment yesterday about the
> 435 study, actually.
>
> It was generally felt that placebos are unethical in this particular
> in this particular group given the risk of progression of disease.
> Historical controls was once again raised as a possibility.
>
> Active control, it was pointed out that, practically speaking,
> probably most people in this group had have had 3TC experience and
> that that drug is actually the standard of care for someone with
> decompensate liver disease right now and that would limit the options
> for the active control in this group. As Dr. Sherman just said, that
> really leaves adefovir as the standard drug to be used as the control
> in this group.
>
> Also pointed out was the risk of delaying liver transplant and the
> complications that may ensue because of treatment of this particular
> group.
>
> When we considered those who had failed prior treatments, Dr. Mathews
> mentioned maybe no-treatment might be appropriate in that group, in
> particular. No; I\'m sorry. That is not what you said. Take that one
> back. It was important to include interferon-experienced people, that
> that could be dealt with by stratification, that when you got to 3TC
> experience, you needed to distinguish between people with experience
> versus those with resistance.
>
> As Dr. Hoofnagle made the important point that there may be continued
> effects from 3TC lamivudine in some patients, versus those who have
> frank resistance and highly active liver disease. In that particular
> group, we heard a couple of thoughts. Leaving on lamivudine was
> thought to be inappropriate for those with decompensated liver
> disease. It might be appropriate with appropriate safety measures for
> a compensated group.
>
> Adefovir, obviously, is the drug that has shown activity in 3TC
> experience and that kind of rose to the top of the list as, perhaps,
> the active control of choice. It was mentioned that tenofovir is being
> used in the community and then Dr. Lok reminded us that prayer is also
> important in that case.
>
> Dr. Block?
>
> DR. BLOCK: I would just like, before we leave this question, to add
> one more thing to Question 3a, or one response, very briefly. For
> myself, it is important to make this point. I think we should
> anticipate, or this committee should anticipate or have the
> imagination to anticipate therapies other than those that have been
> approved or are immediately in the pipeline.
>
> It is easy for the committee to focus on those because obviously the
> nucleoside analogues and interferon are the two drugs that we have
> dealt with. Placebo controls are still, to my mind and, I\'m sure, to
> everyone\'s mind here, the best way to conduct a clinical trial or
> design a clinical trial. Whether or not that is ethical or appropriate
> will depend on the patient population.
>
> The patient populations for which the current designs have been made
> now may demand\--I don\'t think they will, but may frequently demand
> the standard of care that calls for therapy. However, often, or you
> can anticipate drugs choosing other patient populations for which
> placebo controls are entirely appropriate.
>
> Moreover, the active control that would be used or dictated the
> relevance of it is also going to be influenced by the mechanism of
> action of the test drug. If the test drug is another DNA polymerase
> inhibitor that is going to reduce DNA levels, well, then, of course,
> it makes sense to have the active control if there is going to be one,
> a like drug.
>
> If it is going to work by another mechanism of action, particularly
> when you talk about endpoints, you may talk about sixteen-week
> analyses for predictions, then DNA polymerase inhibitors might not be
> the relevant ones.
>
> I know that saying a lot, but I just wanted to at least reserve that
> bit of real estate to imagine mechanisms of action other than
> polymerase inhibitors.
>
> DR. GULICK: Shall we move on to endpoints?
>
> DR. MURRAY: At your discretion, you can open it up five minutes.
>
> DR. GULICK: Oh, right; thanks.
>
> DR. MURRAY: If you think there is still time.
>
> DR. GULICK: Okay. I do.
>
> At the suggestion of the agency, we would like to open it up for
> public comments on the subject of appropriate control arms. This is
> going to relatively limited, but is there anybody sitting behind me
> that would like to make a comment about control arms?
>
> DR. BROWN: Dr. Nat Brown, Idenix, guest of the panel today, I guess,
> in some form. I can speak to an experience that I think some here are
> aware of. We recently put two proposals for a phase III trial program
> to about 120 clinicians worldwide. One of them was an intricate
> 9-to-9-to-2 randomization with the 2 on placebo resulting in about 10
> percent of patients getting placebo for one year and putative active
> drug in Year 2, so had one year of deferred treatment.
>
> Putting that proposal with a straight head-to-head active\--this was
> in compensated liver disease. The other proposal was straight active
> control. There were only four hepatitis specialists, clinicians, out
> of 120 that we put that proposal to that liked the placebo control.
> The rest said they either couldn\'t do it or their patients wouldn\'t
> enroll.
>
> So we came to the conclusion that placebo controls in compensated
> liver disease are really not practical at this point.
>
> DR. DUNKLE: Lisa Dunkle from Achillion. I would certainly concur with
> what Nat has said, but the one point that has not come up which I
> think\--this may not be as pressing in the U.S. as it is outside the
> U.S. is the understanding of how a new drug compares clinical to
> existing drugs on the market and what drugs should be reimbursed and
> what drugs should be supported.
>
> Many regulatory authorities outside the U.S. not only wish for but
> demand active comparators to understand how a new drug compares to
> existing drugs.
>
> DR. DIENSTAG: Jules Dienstag, Mass General Hospital, Boston . The one
> point that hasn\'t been mentioned here is that when lamivudine was
> studied and when adefovir was studies, the placebo-control groups
> studied for a year had 20 to 30 percent progression of fibrosis which
> is the most important histologic landmark.
>
> I, personally, can\'t recommend to a patient that he go, or she go, on
> a year\'s worth of therapy with a 30 percent chance of progressive
> fibrosis. My IRB won\'t allow it and I think that Nat basically
> expressed what happens in real life.
>
> DR. GULICK: Anybody else?
>
> On to endpoints. You are shaking your head because you like the
> format; is that right?
>
> DR. BIRNKRANT: We thought the comments were very helpful, actually.
>
> DR. GULICK: Yes; I did, too.
>
> Dr. Stanley?
>
> DR. STANLEY: Some of us talked about this at lunch. As we move on to
> endpoints, I need some clarification from maybe our hepatologists. Dr.
> Lok and Dr. Hoofnagle both said, in their talks, that seroconversion
> of e-antigen is really kind of a gold standard, agreed-upon, helpful
> thing to look at.
>
> Yet, when Dr. Soon presented his data, he apparently showed patients
> that went back and forth and back and forth and back and forth during
> the course of the study. So, do you all really see that or was this an
> anomaly, or did I misunderstand something? Can somebody clarify that
> for me, please?
>
> DR. GULICK: Dr. Soon, can you review\--a number of us were surprised
> at that one slide.
>
> DR. SOON: I think the difference is in the definition. What I looked
> at was the e-antigen status, that is when you have e-antigen alone as
> a component. The seroconversion refers to three components. Maybe
> other people can comment on that.
>
> DR. LOK: Actually, I was very surprised with that, also. Having
> managed a lot of hepatitis-B patients, you do see that some patients
> go from e-antigen-positive to e-antigen-negative and then revert back.
> But, if I understood that slide correctly, you showed that the
> majority of the patients flip-flopped. It is only a minority of the
> patients after they became e-antigen-negative that they stay
> persistently negative from that time onwards, which is really an
> anomaly, from my personal experience in fifteen, twenty years, that
> the people who flip-flop are really a minority.
>
> You see it anywhere between 10 to 30 percent of patients, but,
> certainly, not 70 to 80 percent.
>
> DR. GULICK: It is Slide No. 40, I think.
>
> DR. SOON: The majority of patients maintain their status. Two-thirds
> maintain their status. About a quarter to one-third rebound.
>
> DR. LOK: So one-third of the patients flip-flopped but two-thirds of
> the patients, once they become e-antigen-negative, they stay
> e-antigen-negative.
>
> DR. SOON: Correct.
>
> DR. LOK: Okay.
>
> DR. SOON: If you look at this slide, if you look at the placebo arm,
> we have 364 patients. 14 percent become negative sometime in the 48
> weeks, or the 52 weeks, for the period of the trial. So that is about
> 50 or 60 patients. Among these patients, 37 percent will go back to
> positive again. That means, the other 63 percent will maintain their
> status until the end of one year.
>
> So two-thirds maintain their status one-third will go back. Among
> those who go back, about a quarter will go down again to the negative.
>
> DR. HAMERSTROM: Those numbers become progressively smaller.
>
> DR. SOON: Right.
>
> DR. HAMERSTROM: That 52 people. That 37 percent is about fourteen
> people.
>
> DR. GULICK: Can you come to the mike, please.
>
> DR. HAMERSTROM: The rest of those numbers are so small\--
>
> DR. GULICK: Can you come up so that everyone can hear your comments?
>
> DR. HAMERSTROM: Tom Hamerstrom, statistician, FDA. You should
> remember, in interpreting this table, that those numbers have to be
> multiplied progressively. So you start with 364. 14 percent\--that\'s
> 52 people\--go from plus to minus. To go from plus to minus to plus,
> that is 37 percent of 52, which is about\--
>
> DR. SOON: Seventeen patients.
>
> DR. HAMERSTROM: Seventeen. The next group, the 26 percent, that is 26
> percent of 17.
>
> DR. SOON: Four patients; yes.
>
> DR. GULICK: So, perhaps, that is not the best way to\--
>
> DR. SOON: The same pattern for the other patients, actually.
> Two-thirds will maintain their status, one third will rebound. Among
> those who rebound, one-third will go back again. So it is always the
> traditional probability is about one-third from one status to the
> other state for any given patient.
>
> DR. GULICK: So that is somewhat confusing way of portraying that data,
> I would say.
>
> DR. HOOFNAGLE: Was the 14 percent at Year 1 the Year-1 specimen or any
> time during Year 1?
>
> DR. SOON: 14 percent of those 364 patients will become negative in the
> one-year period of time.
>
> DR. HOOFNAGLE: Oh; during the period of one year.
>
> DR. SOON: Correct.
>
> DR. HOOFNAGLE: I guess this shows that, with the spontaneous
> seroconversion, there is about maybe a 25 percent relapse rate that is
> persistent.
>
> DR. SOON: Yes; so the same pattern here. Once they become negative, in
> all the groups of patients, one-third will go back in the one-year
> period of time. Among those that go back, one-third of that group will
> go down again to negative. So it will still be in that window.
>
> DR. LOK: On second look at this slide, if I understand it correctly,
> if you look at the three groups of patients who received treatment,
> once they have become e-antigen-negative, the chance that they will
> revert back to e-antigen-positive is between 72 percent and 80
> percent. Of those, they might sometimes still become negative again.
>
> It is the minority that flip. It is between 20 to 28 percent that
> flip, but 72 to 80 percent will stay e-antigen-negative. So it is the
> majority.
>
> DR. SOON: Yes.
>
> DR. GULICK: Does that replicate your clinical experience?
>
> DR. LOK: That replicates clinical experience. What happens is when you
> see patients develop e-antigen loss or e-antigen seroconversion, you
> tend to get about 10, maybe 20, percent of the patients who would lose
> their response. Sometimes, they lose their response transiently and
> then they sort of get back to the response state. Sometimes, they just
> lose their response forever. So 10 or 20 percent is not too
> surprising.
>
> And, yes, we do agree that, at least for the e-antigen-positive
> patients, if you see a sustained e-antigen loss with or without the
> detection of e-antibody, that has been shown to correlate with
> histological improvement. That has been shown to correlate with
> improvement in clinical outcome.
>
> But, as Dr. Hoofnagle pointed out, we now know that some patients,
> when they go from e-antigen-positive to e-antigen-negative, they may
> be selecting for the precore mutant. So now we should qualify a
> e-antigen response as e-antigen loss with suppression of viral DNA
> with normalization of liver enzyme so that if you lose the antigen but
> your DNA still at 10^7^, your ALT is still high, then we shouldn\'t
> call that a response.
>
> DR. GULICK: May I take a step back now that we have clarified this
> particular slide, to go back to what the actual question is to us? Can
> we go back to Question 4?
>
> DR. WOOD: Before we do, may I ask one more question about e-antigen
> loss?
>
> DR. GULICK: Yes.
>
> DR. WOOD: This is, again, a question for Dr. Lok and Dr. Hoofnagle.
> For those patients who have e-antigen loss, what percentage of them
> have seroconversion in terms of a gain of antibody? Does everyone who
> loses their e-antigen gain antibody?
>
> DR. HOOFNAGLE: No, they don\'t. A large proportion do, that do it
> spontaneously or with interferon treatment. It was my impression with
> lamivudine that a lower proportion actually made antibody. But maybe
> Nat Brown can comment on the proportion of patients who lost e who
> made antibody, who lost e and it was sustained over not just these
> flip-flops.
>
> DR. BROWN: There are probably some Glaxo people here who might speak
> to that. Do you want to try that, or do you want me to try it out of
> my memory? I could be rusty and if I say something wrong, hopefully,
> they will correct me.
>
> My impression was, in the Western studies, e-loss rate was in the 30
> percent range essentially and the antibody gain rate was only around
> 18 percent, as you saw. That is a rather broad generalization.
> Whereas, if you noticed, in the multicenter Asian study, the e-loss
> rate was, what, only, still, 17 or 18 percent and the e-conversion
> rate was 16 percent.
>
> So, for whatever reason, in the Asian study, almost all the e-losers
> gained antibody whereas, in the Western studies, only about two-thirds
> gained antibody and the 18 percent gain of antibody actually checked
> out very nicely with the table in the meta-analysis, the first Wong
> meta-analysis, where the gain of antibody in interferon was about 18
> percent listed in one of the tables in that paper.
>
> DR. GULICK: Dr. Hoofnagle?
>
> DR. HOOFNAGLE: I have to also say something about\--the tests for e
> and anti-e are not great tests. Furthermore, the FDA, in their
> brilliance, actually did away with the company that was doing the test
> for many years and we had to switch to a new company. I, frankly,
> don\'t have a good feel for the reliability now.
>
> But the test for anti-e was not a very good test. Basically, to test
> for anti-e, you have a control sample that has e and you mix your
> sample in it at 50 and you see if you drop the counts per minute. So,
> it isn\'t a very good test for anti-e.
>
> Furthermore, you can\'t have both\--using this test, you really can\'t
> have both e and anti-e because of the way the test is done. It is not
> a very good test.
>
> DR. BROWN: Do I need to identify myself again? I agree with Dr.
> Hoofnagle. It may be somewhat assay-dependent. What is it called, the
> IMAX, the automated version of some of the Abbott assays may give a
> little different readout on this proportion than the older assays. So
> I agree. It could be somewhat assay-dependent.
>
> DR. GULICK: Dr. Kumar?
>
> DR. KUMAR: I have a follow-up question. Once, in patients who lose
> their e-antigen and develop an e-antibody, can we conclude that our
> prayers have been very effective and they will not go back to the
> e-antigen status?
>
> DR. LOK: The challenge of hepatitis B is that this is a highly
> unpredictable disease and nothing is permanent. In general, actually,
> Dr. Lao from Taiwan was the first to describe the so-called e-window
> period way back about fifteen years ago. You could have patients who
> lose e-antigen and some of the patients you would detect e-antibody
> pretty much at the same time.
>
> The first time, they become e-antigen-negative, you really show up
> e-antibody. Some of these patients, the e-window period is very long.
> He showed that a majority of these patients, the e-antibody shows up
> within twelve months but some patients can be as long as five years or
> six years later, you still don\'t develop e-antibody.
>
> While the patients are in the so-called e-window phase, the likelihood
> that they flip back and become e-antigen-positive is higher than in
> people who have developed detectable e-antibody. But the detection of
> e-antibody is not a proof that the patient will not flip back. It is
> just a matter of probability being lower.
>
> DR. HOOFNAGLE: Actually, in patients who develop AIDS, too, you see
> spontaneous reactivation. Indeed, with interferon treatment, we had
> very nice response rates and many gay men who then developed HIV, they
> all will reactivate eventually under the immune suppression of HIV
> disease.
>
> DR. GULICK: With those clarifications, I am going to suggest we take a
> ten-minute break and then we will come back and answer the last two
> questions. So we will reconvene at 3:30.
>
> \[Break.\]
>
> DR. GULICK: Welcome back. Dr. Murray wanted to clarify something
> before we get started on the next question.
>
> DR. MURRAY: Yes. Regarding noninferiority or superiority. A new drug
> product does not have to show superiority to gain marketing approval.
> That is not a regulatory standard, or have that sort of relative
> efficacy standard. So they could be comparable or actually, in some
> cases, products inferior but known to have activity and they could
> still actually get on the market. They just have to show that they do
> have efficacy, so it doesn\'t have to be superior. It is usually
> comparable in a noninferiority study.
>
> Then the second point was using a non-approved drug as a control. We
> think it would be very difficult to design a study at this point with
> tenofovir as a control for hepatitis B because its longer-term us for
> hepatitis B has not been adequately established in control trials. So
> we would think that the use of tenofovir would require a whole lot of
> background work before using it as a control in a trial for
> registration.
>
> DR. GULICK: Great. Thank you.
>
> So we are on to Question No. 4; considering the patient population,
> and the necessity that endpoints for registration be clinically
> meaningful, please answer the following; which endpoint or combination
> of endpoints should be primary in clinical trials? We are going to
> want to touch on histologic, serologic, biochemical and virologic
> endpoints; so the primary endpoint in future hepatitis B studies.
>
> Dr. Goodman?
>
> DR. GOODMAN: It is my turn to comment on some of the things that have
> been said about histology today. I want to clarify things that have
> been said over the last two days. One of the most important ones is
> about the criterion of a two-point change in histology as an endpoint,
> is that clinically meaningful.
>
> I have never been entirely sure where that came from but, as I
> understand it, it was in negotiations between the agency and the
> sponsors of previously approved drugs. I think using the histology
> activity index, it was originally conceived of as being a continuous
> variable even though there are missing numbers.
>
> I think that was the way it was intended to be used, but the agency
> statisticians were unhappy with that, as I understand it, and they
> asked the sponsors to pick out something that they considered a
> clinically meaningful degree of change.
>
> Two points was decided on. I am sure whose idea that was. How can you
> get a two-point change? You can get a two-point change in several
> ways. The natural history of the disease; this is a disease that
> flares and subsides. So some patients are going to improve by two
> points spontaneously. Some will worsen by two points spontaneously.
>
> You can get it by sampling error. I have seen liver biopsies where one
> end has a score than is more than two points higher than the other
> end. If you only have half of that biopsy, you can get a change that
> way. That was referred to in Dr. Soon\'s presentation. Then the
> interpretation by the pathologist. This is a continuous variable, but
> the pathologist has to put it into discrete categories. If it is on
> the borderline, you can get a two-point change just that way, even if
> nothing absolutely happened to that patient.
>
> There are lots of ways you can get a two-point change irrespective of
> the virologic response.
>
> Now, a two-point mean change, I think that is extraordinarily
> meaningful. The agency statistician yesterday showed the box plots
> from the adefovir study showing a whole shift of the entire population
> who was being treated with the active drug.
>
> That is a big change. The entire population shifted by more than two
> points. I think that is the way all of this histologic data ought to
> be used is in terms of a cohort rather than an individual. I tell that
> to pathologists when they ask me how to go about scoring it because
> Dr. So-and-So wants the Knodell score on this patient. So I say,
> \"Just refuse to do it. Tell them that is not the way to do it.\"
>
> The way you should do it is, if you want to know if an individual
> patient improves, you look at the two biopsies together. If you want
> to know whether a cohort improves, then you need something to do with
> statistics that you can do a test on that can show a meaningful
> improvement.
>
> What would be a better way? You could use the mean change. But, in
> fact, that two-point proportion still worked. As I said yesterday,
> that is the absolutely most conservative way you could interpret the
> data, but it still works. It showed a highly statistically significant
> change between the placebo and the active drug. So that is possible,
> but it is not necessary and that is really not the right question to
> ask, though.
>
> The real question is whether the entire cohort improved. I think, with
> the drugs that have been approved, they have. Anyway that you look at
> the data, it shows improvement.
>
> That\'s the main thing. I am not going to say whether I think the
> liver biopsies are the best way. I was confused by some of the data
> that was presented. I think Dr. Lok\'s data that she presented showing
> a total lack of correlation between histologic improvement and the
> other parameters was because histologic improvement was defined as a
> two-point change.
>
> Dr. Soon showed that actually, and I think Dr. Wulfsohn mentioned,
> that the best predictor of improvement was the baseline score, that
> people who have a lot of inflammation are going to be spontaneously
> improving but more of them will improve if you treat them with an
> active drug and they will improve to a greater degree. So it is
> another thing to take into consideration.
>
> Dr. Soon showed what looked like a lot of lack of improvement but it
> was based on the change in the score rather than the absolute score,
> so I am not sure whether it wouldn\'t have been better if you looked
> at the absolute amount of inflammation, as to whether that correlated.
> And I was totally befuddled when Dr. Murray showed that graph showing
> an absolutely perfect correlation of histology with DNA. How can that
> be? I don\'t understand that at all.
>
> Since I enjoy looking at liver biopsies, I am not going to tell you
> that you have to liver biopsies. I do have a conflict of interest
> there, but I think that there is more to be gained from looking at
> liver biopsies than just doing these scores. There is all sorts of
> other information that you get about the patient including where he is
> in the natural history of his disease and what his prognosis is going
> to be.
>
> DR. GULICK: Dr. Birnkrant?
>
> DR. BIRNKRANT: Do you have a preference, though, for Knodell over the
> Ishak score?
>
> DR. GOODMAN: In the adefovir study, we analyzed it both ways using the
> two-point improvement, looking at the mean improvement, and it comes
> out the same, basically. I think it is a matter of personal
> preference. Probably since the Ishak score did away with that group,
> the missing number 2, why not do it that way in the future. But I
> don\'t think it will make any difference in the outcome of the
> studies, as long as we are talking about cohorts as opposed to
> individual patients.
>
> DR. BIRNKRANT: You would never anticipate, then, a discrepancy between
> the Knodell and the Ishak?
>
> DR. GOODMAN: Oh, anything could happen when you are dealing with
> numbers. That is the other that I meant to mention. How do you do away
> with these other reasons for variability? Besides having a placebo
> control, you have to have adequate sample size for statistical
> analysis, not just looking at individual patients.
>
> DR. GULICK: Dr. Wong and then Dr. Hoofnagle?
>
> DR. WONG: I guess I want to ask Dr. Goodman, yesterday we saw, from
> the FDA reviewer, that the adefovir treatment arm caused a measurable
> improvement in fibrosis score, not just an improvement in inflammation
> and necrosis score.
>
> Then Dr. Hoofnagle\'s presentation this morning, I think you showed
> that if you follow people out longer than one year, that is not so
> surprising, that that was seen in other cohorts as well. Which would
> be your preference? I guess, from my point of view, prevention of
> fibrosis is what we are really trying to achieve as opposed to
> prevention of inflammation. If one could expect that that would be
> demonstrable in a reasonable period of time such as one year with a
> highly effective agent, would that be a preferable endpoint of the two
> choices for histology?
>
> DR. GOODMAN: The absolute change in fibrosis is actually pretty small.
> It is statistically significant. It is definitely going in the right
> direction. But, in one year, it is really not very large. Most of the
> patients don\'t have that much fibrosis to start with and it becomes
> less.
>
> If you started with people with more fibrosis, you would have a harder
> time getting them into it. I suppose, then, there might be more room
> for improvement but I think you would probably need larger samples.
> There, again, we are not dealing with probably a clinically meaningful
> improvement in fibrosis in terms of individual patients, even though
> it is definitely happening and I presume that, over the course of many
> years, there would be statistical, even clinically meaningful
> improvement.
>
> DR. GULICK: Dr. Hoofnagle?
>
> DR. HOOFNAGLE: I think you have answered one question and that is when
> you give all these HAI scores, are you using the old system where you
> skip the number 2?
>
> DR. GOODMAN: We collected the data both ways for the study. The
> primary endpoint was defined as the original Knodell score and that is
> what we used. When you analyze it using the modern one, it comes out
> about the same.
>
> DR. HOOFNAGLE: The second issue is a mathematical statistical one that
> I have never been able to understand how to analyze changes in scores.
> As you showed very clearly, if you begin with a low score, 5, you
> can\'t improve very much. So these multivariate analyses that show
> that improvement in histological score correlates with the initial
> histological score is stating obvious, isn\'t it? It is not really
> very helpful.
>
> So the reason why the two-point change was used was basically you
> wanted to change this from a parametric to a nonparametric number.
> Basically, are they improved? Are they the same? Or are they worse?
> Improved would be one point better. But they said, \"Oh; one point
> isn\'t enough. Let\'s make it two.\" So that is how it was to
> categorize the patients as improved, the same or better.
>
> But when we talk about the amount of improvement, that is so dependent
> upon where you start that I am not sure how that can be interpreted.
>
> DR. SOON: That is why I have been showing the two lines, basically to
> say it has to be forced even if there is no correlation. If it varies
> wide enough, because you cannot see various above, below, the two
> lines, so you are going to see an artificial trend there. So it is
> really hard. You cannot tell if it is really because this is the upper
> and lower limit in the scoring system or is that because there was
> really a correlation. It cannot be separated.
>
> DR. BLOCK: I just had a quick question and also a point. One, first, I
> wasn\'t surprised\--I was, actually, encouraged\--by what Dr. Murray
> presented showing the tight correlation that was change in DNA from
> baseline rather than absolute levels as was shown previously at
> Year 1. I think that is very telling. It was the change in DNA and,
> actually, you or someone else may have mentioned that that might be
> best taken at a particular time under therapy.
>
> Again, I will emphasize that the endpoints used will have to be
> influenced, I believe, by the mechanism of action of the drugs. But,
> having said that, since the drugs that are being considered are,
> again, the nucleoside analogues, the change in DNA correlation was, I
> think, satisfying and actually consistent with what we saw before.
>
> I just have a question for the group because I really don\'t know the
> answer to this and it may be known. Given the fact that hepatitis B,
> obviously, causes liver cancer as much as cirrhosis or fibrosis, is it
> clear that the HAI scores and Knodell scores are the best predictor of
> length of life or quality of life or in other clinical terms? Is that
> clear, because that is what is we are all aiming for.
>
> DR. GULICK: So the question is does histology predict clinical
> outcome.
>
> DR. LOK: There is not a whole lot of data. Most people quote a paper
> that was published from the Stanford group many, many years ago where
> they biopsied a bunch of patients using the old terminology, chronic
> persistent hepatitis, chronic active hepatitis and cirrhosis. These
> were patients who were not on treatment. These were patients who just
> happened to be biopsied.
>
> You follow them ten years out and you found that the patients who had
> cirrhosis in initial biopsy obviously had higher mortality. The
> patients who had CPH initially had better survival compared to dose
> with chronic active hepatitis.
>
> So that is really the most widely quoted study and that was a study
> from fifteen years ago. I find that one of the problems with using
> histologic response as endpoint and trying to understand whether that
> predicts clinical outcome is it is so much dependent on whether you do
> the biopsy when the patients are still on treatment because, with all
> these nucleoside analogues, if you do the second biopsy while the
> patients are still on treatment, and if the viral load is still
> suppressed, the liver enzymes are down. You are not surprised that the
> second biopsy looks better.
>
> Does that actually predict better clinical outcome? It depends on
> whether you are able to maintain the patient in that state. If you
> stop the treatment and everything comes back, then I don\'t believe
> that the initial histological response would be of benefit to the
> patient or, if it is, it is probably only very minimal benefit to the
> patient.
>
> Likewise, if the patient subsequently developed resistance and there
> is beginning to be some data emerging that show that the patient\'s
> Year-1 biopsy improved, but the Year-4 biopsy, after the patients have
> now developed resistance, the HAI score has gone back up again. So you
> have the pretreatment one and then the Year 1 comes down. Then, if
> they have developed resistance later on, it will go back up again.
>
> So you really need to understand the timing at which the biopsy is
> done and whether the patient was still on treatment. I, personally,
> would like to see that we can get away from histologic response as an
> endpoint not because I think that Zach is too busy. We can certainly
> give him more work and he certainly enjoys looking at biopsies anyway,
> but I think that, from a practical standpoint, if there is a way by
> which you can use a noninvasive endpoint, you would prefer to use a
> noninvasive endpoint because it is certainly more acceptable to the
> patients.
>
> We also have a hard time, as we just discussed\--liver biopsy is not
> bad but if you want to use histology, how do you define what is
> clinically meaningful. We are not sure that a two-point decrease is
> clinically meaningful. It depends on what your starting point is. It
> depends on whether you repeat the liver biopsy when the patients are
> on treatment.
>
> So if we want to stay with histology, we should review whether we
> should stay with a two-point improvement or whether we should have a
> more creative way of looking at it. Dr. Hoofnagle had, in the past,
> proposed a 50 percent reduction. So, if you start off with sixteen
> points, you need to drop down to eight points.
>
> Or maybe we need to have a percentage drop and drop below a certain
> level, because if you start off with 18 and you drop down to 9, it is
> still fairly high. It is still not very good. So, do we want it to
> drop below 6 or 7 before we say that this is clinically meaningful
> because if we talk about clinically meaningful and not just to play
> around with statistics, then we really should decide what is
> clinically meaningful.
>
> I also want to suggest that we should carefully examine the
> possibility of using virologic endpoint or, better still, I think we
> should use composite endpoint. I don\'t believe that we should just
> look at ALT normalization. I don\'t believe that we should just look
> at HBV DNA level at one time point or even at multiple time points.
>
> I believe that, for the e-antigen-positive patients, we should
> certainly look at the composite of e-antigen loss plus or minus
> development of e-antibody, a DNA that drops below a certain level\--I
> propose maybe 10^5^\--and ALT being normalized as a composite
> endpoint.
>
> For the e-antigen-negative patients, obviously, we can\'t talk about
> e-antigen loss. If we use a composite endpoint, it would have to be a
> drop in the viral load and normalization in liver enzyme. How much
> should the viral load be dropped down to? I believe that it should be
> dropped down to a lower level because these patients start off with
> lower levels so they should drop to lower levels.
>
> These patients fluctuate. So are we satisfied with just looking at
> these endpoints at one time point or do we need to see that this is
> consistent, that you can actually reproduce it and that you can see
> that this is occurring over two months and three months.
>
> So I think we should look at using other endpoints. We should look at
> composite endpoints and, if we do decide on histology, we should
> definitely reexamine whether a drop in HAI by two points is the right
> criteria.
>
> DR. GULICK: Dr. DeGruttola?
>
> DR. DeGRUTTOLA: I just wanted to comment on a previous issue but I
> also believe it relates to Dr. Lok\'s comments about the histology. As
> Dr. Hoofnagle pointed out, it someone starts at a lower value, they
> can\'t decline as much as someone who starts at a higher value.
>
> But there are statistical methods for censored data that can handle
> that situation, so I don\'t think that need, necessarily, be a concern
> although you have to bear in mind that some of the data are actually
> censored because you can\'t drop below a certain level.
>
> The issue of where you start in terms of the Knodell score may affect
> how much of a drop you had can also be handled using methods like
> analysis of covariates. So I don\'t think that these issues prevent
> being able to do valid analyses although, as I think Dr. Lok pointed
> out, the crucial question here is what is most clinically relevant.
>
> In terms of the bDNA analyses, obviously the ones that are the most
> straightforward are the ones just discussed going below a particular
> threshold. I think that, as part of a composite score, obviously that
> would be an interesting endpoint that would reflect a lot of things
> that were going on. But one of the concerns that I would have about
> the DNA being used as an exclusive endpoint is that the association
> with the Knodell score appeared to vary, as Dr. Soon pointed out,
> earlier.
>
> Therefore, you couldn\'t assume that a certain level of DNA meant the
> same thing in terms of its predicting a Knodell score whether or not
> you were on therapy or it could also depend on what therapy a patient
> was taking. So I think that would be a concern about using DNA on its
> own.
>
> DR. GULICK: Dr. Sherman.
>
> DR. SHERMAN: I agree with Dr. Lok with the need for probably
> developing some composite markers and that those are going to have to
> be individualized based on each individual treatment. In other words,
> what is defined as the primary endpoint for a patient on interferon in
> e-antigen-positive group of compensated disease may be different than
> what you are seeking on nucleoside analogue in a patient with HIV
> infection.
>
> In other words, the population that you are treating will partially
> define what you select as your primary endpoint. I think that the
> agency is going to have to be somewhat flexible and cognizant of that
> fact.
>
> The issue about two points isn\'t enough and maybe we should use a
> greater drop or percent drop or a certain decrease is not validated by
> anything either. There is no prospective data that tells us that, gee,
> a 50 percent drop in HAI is going to be clinically more relevant then
> a two-point change. It sounds good. It feels right. But it is not
> based on anything.
>
> The other point that I wanted to make relative to what Dr. Lok said
> was that issue of looking at histology and making a decision about
> when you would like to biopsy is partially dependent upon your
> philosophy of treatment.
>
> If we had a treatment that cured disease, similar to that which we see
> in hepatitis C now, then a reasonable time point would be after the
> end of treatment and a time has passed. But that is not our goal of
> therapy here. Our goal is, itself, kind of vague. We would like to see
> e-antigen conversion and e-antigen-positives.
>
> But a large percentage of patients are not e-antigen-positive that
> have this disease. Particularly, with the newer agents that are out
> there, we, in fact, are dealing and must come to grips with the fact
> that we are dealing with suppressive therapy and here invoking the
> model of what we do with HIV, that it is going to require long periods
> of treatment, that some patients will have a conversion of a type that
> may take them to a less replicative state and maybe some of those
> patients won\'t need therapy, but that the majority of patients, in
> fact, will need, with the therapies that we have now and the data that
> we have seen on all the therapies, to need suppressive therapy.
>
> Therefore, a histologic model that shows you the effect of treatment
> of therapy is reasonable. Now, that is separate from the practical
> issues related to getting those biopsies that have been brought up,
> but it is still reasonable to consider that as a marker for therapy
> unless we feel confident that one of the other endpoints is highly
> correlated; for example, a drop of some level in HBV DNA.
>
> DR. GULICK: Dr. Mathews.
>
> DR. MATHEWS: I wanted to ask a question of Dr. Goodman and then make a
> comment. When you read the biopsies in clinical trials, you are
> blinded to the treatment assignment. But are you reading the paired
> biopsies? You know you are reading the same patient?
>
> DR. GOODMAN: It is different in different trials. Sometimes, I am
> totally blinded. I don\'t even know which ones go together. Sometimes,
> I do look at them both together. I don\'t think it has made any
> difference in the outcome of the studies.
>
> DR. MATHEWS: But, in terms of the correlation between the baseline
> biopsy and the reading, the score, the numerical score on the Knodell
> and the follow-up biopsy, I would think that that could explain part
> of the high correlation between the baseline and the subsequent
> biopsies if you knew that you were reading the same patient, because
> you are doing them at the same time, presumably.
>
> DR. GOODMAN: It is not that they come out the same. It is that those
> with a higher baseline HAI are more likely to have improvement. That
> is the only correlation there. It is not that the biopsies correlate
> with one another. Sometimes they do look the same and sometimes they
> look dramatically different. Do you see what I mean?
>
> The predictor was how high the HAI was predicts whether or not the
> patient is going to have a two-point improvement.
>
> DR. MATHEWS: The other point I wanted to make is that the histology is
> really\--I mean, it is being treated as the equivalent of a clinical
> endpoint but, in fact, it isn\'t and it is quite fallible because of
> all of these measurement variabilities that you talked about; sampling
> error, the reading error, and so on.
>
> As I think about it, I wonder if it isn\'t possible to actually do a
> true clinical endpoint study where hepatic decompensate or death is
> the endpoint to validate some of the virologic markers if you started
> with people with cirrhosis at baseline, where the event rates are not
> small, as I understand it. Maybe the hepatologists could comment on
> that?
>
> DR. HOOFNAGLE: You are talking about a very large study that goes on
> for a long time. In hepatitis C, we are engaged in such a study
> looking at long-term interferon therapy for patients with stage 3 and
> 4 disease. But it is an enormous study, very long.
>
> This goes to the question that Dr. Wong brought up that I didn\'t
> answer which is why not use fibrosis rather than the histology
> necroinflammation part of the HAI score. That actually is right on
> target as far as we think of the natural history of the disease is
> progressive fibrosis that leads to cirrhosis and end-stage liver
> disease.
>
> So the name of the game, really what we are trying to do, is prevent
> the progression of fibrosis on liver biopsy. So, as an endpoint, that
> would be certainly harder although it, also, has not been proven to be
> the clinical endpoint. The FDA has had a lot of input into our trial
> in hepatitis C in patients with advanced disease for this very reason.
>
> It hasn\'t been shown that preventing progression from, let\'s say, an
> ISHAK 4 to an ISHAK 5 is clinically meaningful. So these are difficult
> issues but the fibrosis progression is the endpoint that would be much
> harder if you are going to use liver biopsy. The trouble is it takes a
> long time so that a liver biopsy, after one year, is unlikely to show
> much improvement or worsening in fibrosis.
>
> When you go two years, you start to see something, though, I think
> and, in these trials, you will begin to see big differences in
> progression of fibrosis in patients who have maintained low levels of
> virus and so forth. So I think that can be achieved. It just requires
> a very large number of cases.
>
> I agree with Dr. Lok that we are using liver biopsy as the be-all and
> end-all, the gold standard, without it really being proven to be the
> gold standard, particularly the activity on the liver disease, the
> necroinflammation, really hasn\'t been proven to be the factor that
> needs to be calmed down. It hasn\'t been proven to be any more
> accurate than ALT levels, for instance.
>
> DR. GULICK: Dr. Stanley
>
> DR. STANLEY: On my way out. I tend to agree with Dr. Lok that
> composite endpoints are probably a way to go, a good way to go, but
> what Dr. Sherman said, I want to expand on. It is not just that you
> may have to change those based on the population you are studying but
> also the drug you are studying.
>
> When I looked at Dr. Soon\'s data on all of the interferon arms, DNA
> was just off the chart, up and down, up and down, as well as ALT. So
> you couldn\'t really necessarily use those as part of your composite
> for interferon treatment or any other potential immunomodulator
> possibly.
>
> So then that begs the question of how are you going to compare trials
> with different drugs, do you need a standard, and I don\'t know
> whether that is biopsy or not, where you can compare what the results
> were in a lamivudine trial with what the results were in an interferon
> trial or an adefovir trial. So that is just a concern that I express.
>
> DR. GULICK: Dr. Schapiro?
>
> DR. SCHAPIRO: If I had to answer Question 4, I would say that, based
> on what we saw today, we did not see the correlations with histology
> for the other endpoints. So I would say that the primary endpoint
> should remain histological although I think we have heard some
> suggestions that it would not have to be more than two points.
>
> I think, using it as a continuum and doing censoring, as Victor
> mentioned, might be a better way. I think the fact that the data from
> the other trials can probably be also compared in that way would be
> helpful. That would be the primary endpoint.
>
> I think using 48 weeks despite the fact the patient may be treated
> longer remains a reasonable time point to look at. There are many
> therapies which are continued beyond that but, if we see a good
> response at 48 weeks, it is not to say that it won\'t be continued. So
> I think that is reasonable.
>
> I think secondary endpoints might be appropriate. What was suggested
> earlier, a composite of the others would be a possible secondary
> endpoint although, again, I think I was, I won\'t say disappointed,
> but the data we saw from Dr. Soon didn\'t heavily support that those
> correlated with histology. I do think, still, histology has better
> correlation with clinical outcome than the others.
>
> DR. GULICK: Thanks for being provocative there. Dr. Schapiro is
> proposing that we recommend at this point that the primary endpoint
> for future studies continues to be histology, even given all the
> limitations that people have mentioned. Can we just focus on that one
> point for a minute?
>
> Dr. Wong?
>
> DR. WONG: That is attractive, but I am a little bit reluctant because
> the lack of correlation that we saw in Dr. Soon\'s presentation might
> have been because virologic and biochemical measures don\'t correlate
> well with clinical outcome. But I guess it is just as possible that
> the inflammatory score doesn\'t correlate with clinical outcomes and
> the virologic and biochemical correlate measures do.
>
> So I am not sure that we can decide. That is why I asked the question
> about fibrosis just because, on the basis of biological plausibility,
> it would seem to me that if we could demonstrate clearly in a
> clinical-setting that we prevented progression of fibrosis in one
> treatment group as opposed to another, just on the basis of general
> biological plausibility, I would say that is something that we really
> want to achieve.
>
> But, beyond that, I don\'t know that we choose a priori that any other
> is better than any\--Group A is better than Group B.
>
> DR. GULICK: Dr. Lok?
>
> DR. LOK: I agree with Brian. We sort of assume that a liver biopsy is
> really the gold standard and we take it at faith without really
> showing the data. In fact, when you try to review the literature and
> see whether there is, indeed, data to show correlation between
> histology and clinical outcome, like I said, other than that old
> standard paper from fifteen years ago, there is really no data.
>
> On the other hand, there are numerous studies that show that in
> e-antigen-positive patients who have sustained e-antigen clearance
> that is associated with improvement in clinical outcome, there is less
> liver-related death. There is less hepatic decompensation whether it
> is spontaneous e-antigen loss or whether it is interferon-related
> e-antigen loss.
>
> Lamivudine trials haven\'t gone on long enough for us to really show
> that. Even in the e-antigen-negative patients, I showed you data,
> although the graphs were not very convincing, but, nonetheless,
> Stephanos Hadziyannis and his group have shown that, in the
> e-antigen-negative patients who had sustained response to interferon
> therapy define as normalization of liver enzyme and hepatitis-B DNA
> dropping to undetectable using hybridization assay.
>
> They also had better transplant three survival compared to the
> patients who were treated and didn\'t respond and compared to the
> patients that were not treated. Granted, that is not parallel
> controls. Some of those were nonconcurrent controls.
>
> So we do have some data, not perfect data, to show that these
> serological and virologic and biochemical endpoints, if it is
> sustained, can correlate with good clinical outcome.
>
> Instead, we actually don\'t have data to show good histology and
> improvement in clinical outcome in part not because there is no
> correlation but, because we don\'t repeatedly do biopsies on patients
> on the time, it is much harder to generate those data.
>
> DR. GULICK: Let me push you again on this. I don\'t know why it is
> always me pushing you, Dr. Lok. So let\'s answer the question, then,
> again. The new drug is coming along. What should the primary endpoint
> of the study be? Should it be histological or should it be a composite
> based on the other measures we have been talking about?
>
> DR. LOK: I would like to see that we move to a composite endpoint. I
> would like the panel and FDA to seriously consider using a composite
> endpoint and I do think that, perhaps, with Dr. Soon\'s help and with
> the industry\'s help, that we can define specific questions, go back
> to the database and try to understand some of these questions a little
> bit better and define how low we want the viral level to drop down to.
>
> What I really is serious consideration of moving to a composite
> endpoint.
>
> DR. GULICK: Could others ring in on this issue, too? Dr. Wong?
>
> DR. WONG: I think that the agency should remain flexible on that
> point. I think it really depends on the population and the drug that
> they are studying. I personally would be convinced that a drug was
> effective if a sponsor could show that there was a reduction of
> progression of fibrosis or if the sponsor could show that there was a
> sustained virologic response including, for example, conversion to
> e-negative, e-antibody-positive and all the enzymes disappear and all
> the DNA appears.
>
> Either of those, to me, would constitute convincing evidence of
> antiviral effect and I don\'t think one has to choose one as the
> primary endpoint for all future trials. I think that the sponsor
> should be able to choose any convincing data showing antiviral\--or
> actually any convincing data showing clinically relevant effect. It
> may well be different for different sorts of drugs or different sorts
> of populations.
>
> DR. GULICK: Dr. Hoofnagle. Dr. Sherman, do you want to ring in on
> this?
>
> DR. HOOFNAGLE: I think one of the major issues is are we looking at
> suppressive therapy or somewhat curative. Are you going to give
> therapy long-term continuously as we often do now with lamivudine and
> probably adefovir will be the same, or do you give a short defined
> course like we do with interferon for only six months?
>
> If you are going to talk about continuous long-term therapy, I think
> using a composite viral definition is good, a sustained suppression of
> HBV DNA below 10^5^ with normal ALT. I\'ll bet if you maintain that
> for four years, you are going to show marked improvement on biopsies.
>
> So this goes to the issue of how long should studies go on that are
> looking at maintained continuous therapy? Should it be a year? Should
> it be two years?
>
> DR. GULICK: That is our next question, actually. We will get to that
> shortly.
>
> Dr. Sherman?
>
> DR. SHERMAN: I agree with Dr. Wong that it is very reasonable to have
> each drug brought in by a sponsor, be evaluated by one or more
> parameters that they suggest in discussion with the agency. We know
> what the relevant markers are. We know that some drugs will probably
> do better in some areas than others. The way that you structure your
> application, the way that you decide to position yourself, whether it
> is for suppressive therapy in the short-term, recovery of
> decompensated patients or seroconversion of patients that are
> e-antigen-positive are all good goals and all will create market
> niches that can be utilized appropriately by clinicians.
>
> This committee will be the one that will, then, ultimately, review
> those data and try and decide if it is viable and that there is going
> to have to be some flexibility because we have so much uncertainty in
> picking a single outcome that we can say is the outcome that should be
> used in all studies.
>
> DR. GULICK: Dr. Englund, and then we will try to come to some
> conclusions.
>
> DR. ENGLUND: I would agree with that. I think that it is very
> reasonable that one has to be flexible depending on the drug, the
> mechanism of action, the patient population studied. I do like the
> idea of composite scores especially as we are moving to larger, more
> multinational, studies. It makes sense to have something that is going
> to be less open to different types of interpretation across different
> medical centers or investigators.
>
> What I would like to say, though, is if we move to the composite
> scoring system, we have to be very careful not to give weights to
> different parts of the composite score and add it together and make it
> a total scoring system, which we have seen and seen misadventures in
> the past with, for example, other antiviral studies.
>
> You can\'t add together and make a relative judgment that an ALT is
> worth so much weight and a bDNA is worth so much weight in a clinical
> score. You cannot do that. I would still like to have the composite
> score, the individual measures, and not attach different values. So
> you don\'t want to end up with a single scoring system to assess
> whether the antiviral therapy was actually good or not because I think
> that will attach value judgment to what is potentially unknown.
>
> DR. GULICK: Last comment. Dr. Wong.
>
> DR. WONG: Just a brief comment. If we are going to accept composite
> scores, I would just like to make a point I have made before. Make
> sure that the toxicity measures are kept out of the efficacy measures.
> We have just had terrible problems with that with other classes of
> drugs and just confusing the issue.
>
> So efficacy and toxicity have to be clearly demarcated.
>
> DR. GULICK: So, regarding endpoints, clearly we want the most
> clinically meaningful. Yet it is just not clear to this committee
> which that is. Mechanistically, from a biological plausibility point
> of view, perhaps it is preventing the progression of fibrosis but
> that, too, is unproven. In general, the endpoints may need to be
> individualized according to the patient population.
>
> Also, the endpoints depend on the goal of therapy. As Dr. Hoofnagle
> pointed out, is it suppression or is it curative disease and then, as
> many said, flexibility of endpoints may be the key in choosing the
> right one for the right drug and the right population.
>
> With regard to the question of which should be the primary endpoint,
> we are uncertain as a group. Some advocate histology, others leaning
> more towards a composite endpoint and the realization that neither is
> perfect and, actually, that neither is prove to correlate with
> clinical outcome.
>
> Histology, certainly a direct measure of inflammation and fibrosis and
> the current gold standard. But, lots of variability realized. It has
> been treated as a continuous variable in the past which may be not
> appropriate. It is really a parametric variable. It depends on where
> you start.
>
> It can vary according to the natural history or sampling errors and
> the choice of two points is somewhat arbitrary. Different ways of
> looking, of course, at scoring the histology. Mean change for a
> population cohort was advocated. Change versus absolute number,
> percentage change were other things that people mentioned.
>
> Does it predict clinical outcome? Lots of weight to a fifteen-year-old
> Stanford study. The timing of the biopsy and the presence of
> resistance were also pointed out as things that need to be considered.
>
> Regarding the other measures, people really did not pick one out
> although we were intrigued with Dr. Murray\'s data
> correlating\--Triangle\'s data, I should say, that Dr. Murray got to
> present\--showing a nice correlation, at least in e-antigen-positive
> of the change in DNA. Most others gravitated towards a composite
> endpoint including a sustained e-antigen loss, decrease in HBV DNA and
> ALT.
>
> Several people made the point that, perhaps, multiple time points is
> better than one time point for assessing that. Also, once again, the
> question, does that correlate with clinical outcome and then very
> practical suggestions toward the end of the conversation. This should
> not be a weighted score, that the individual measures are important
> and that it should not include toxicity.
>
> Let\'s open it up to comments from\--oops.
>
> DR. MURRAY: Can I just ask one question? On the composite for
> e-antigen-positive patients, must the composite include e-antigen
> seroconversion. It is a lower-frequency event and, if you add that to
> the composite, then, in an active controlled study, you are going to
> need a very small delta or perhaps go out to two years. Or would you
> look at ALT and DNA as a composite and they must have the trend in
> e-antigen seroconversion?
>
> Do people understand what I am asking? When you add e-antigen to a
> composite endpoint, the seroconversion, it really drives up your
> sample size because it is a lower-frequency event at one year.
>
> DR. HOOFNAGLE: Of course, there are people who have been maintained on
> lamivudine or adefovir for several years who remain e-positive who
> have no detectable HBV DNA, normal ALT and an improved biopsy. So, I
> think you need to move\--if you are talking about suppressive therapy,
> long-term suppressive therapy, to just suppression of HBV DNA below a
> certain level and ALT.
>
> Your friends in the hepatitis-C area of the FDA have come up with
> somewhat of a nice approach. They have virologic, biochemical and
> histological responses. When people come in with a drug, they
> basically say you have got to do two out of the three; we are not
> going to accept a drug that just affects virus or just affects ALT or
> just affects histology. It has got to affect two of the three.
>
> That actually turned out to be a very smart approach, I think.
>
> DR. GULICK: Dr. Lok?
>
> DR. LOK: Just a comment on Dr. Murray\'s point. I think it all depends
> on whether you are thinking of suppressive therapy and, as long as you
> can maintain this, you can just continue to stay on the treatment or
> whether this is an endpoint which would provide guidance for stopping
> therapy.
>
> If this is an endpoint which would provide guidance to stopping
> therapy, then I think some sort of change in e-antigen is important.
> This comes back to the point, is the e-antigen loss good enough
> because, in every single study, we see that the e-antigen-loss rate
> occurs higher and the difference between the treated patients and the
> patients on placebo is more dramatic whereas, if you look straight at
> the e-antigen conversion, then, yes, the difference is tighter and it
> drives the sample size.
>
> So I think it is really worthwhile going back and looking at is the
> e-antigen loss good enough and, if the e-antigen loss is good enough
> and you don\'t need the antibody, that might be important.
>
> But the ultimate thing is what is the purpose of the endpoint? Is the
> endpoint going to provide guidance to practicing physicians that, when
> you see this, this is an indication that you might consider stopping
> treatment. On the other hand, if we all sort of throw up our hands and
> say that, from now onwards, we are going to treat all our patients
> forever and ever, then we don\'t need to look e-antigen as long as the
> DNA stays down and ALT stays down, we are happy.
>
> DR. GULICK: Dr. Block.
>
> DR. BLOCK: Very quickly. A reason against favoring both or either of
> those three endpoints, as Dr. Hoofnagle was talking about, because I
> think it is going to depend on the claims that are made by the
> applicant, what it is they are representing their drug to do.
>
> If you had, hypothetically, a drug that was wonderful at improving
> histology but very poor in antiviral or lab values, that might have a
> great value. And you have the luxury, now, with drugs that are
> antiviral, of saying, \"All right; I can imagine a combination.\" It
> just depends on what the claims are that are made by the applicant.
>
> DR. GULICK: Let\'s go ahead and open this up to the observers. A
> couple of people already tossed me some notes or caught my eye. So we
> are open for public comments for about five minutes.
>
> DR. BROSGART: I just wanted to share with you some data. We call this
> the \"Hoofnagle analysis.\" Our primary analysis in our study was to
> look at the greater-or-equal-to-two-point decline in the Knodell
> necroinflammatory score with no accompanying worsening in fibrosis.
>
> We met that endpoint. If you looked at an endpoint by mean change in
> total or median change in total, we met that. If you looked at the
> rank assessment, it was a statistically different result.
>
> If you looked at whether or not you had at least a five-point decline
> or a four-point decline or a two-point or a three or a one, no matter
> how you cut it, it is always statistically different from the treated
> group to the placebo group. But we did the Hoofnagle analysis because
> Jay threw down the gauntlet at the NIH meeting a couple of years ago
> because he thought the two-point wasn\'t good enough and you should
> look at at least a 50 percent decline.
>
> So, in our e-antigen-positive study, looking at at least a 50 percent
> decline in Knodell score, for 30 milligrams, it was 35 percent. For 10
> milligrams, it was 32 percent. For placebo, it is 6 percent.
>
> Then, in the e-antigen-negative study, again, a greater or equal to 50
> percent decline in Knodell. For 10 milligrams, it is 43 percent. For
> placebo, it is 5 percent. In each of those studies, the active arms,
> as compared to placebo using at least the 50 percent decline, are
> highly significant statistically.
>
> So I think this goes back to I think Zack\'s adage that no matter
> whether you are looking at the individual components or the total
> component and whether you use a greater or equal to two-point or you
> take the 50 percent, if you have an adequately powered study that has
> been appropriately randomized so that there are enough people and you
> have a full range of demographic characteristics and they are balanced
> for baseline disease characteristics, if the agent is active, no
> matter what the threshold is, you are going to see a statistical
> difference because you are looking at moving the entire cohort away
> from the natural history of disease.
>
> That has been shown. Nat spoke to it, and others have, similar kinds
> of results were seen when you looked at histology from a number of
> different ways. So I am not sure whether using the two-point plus no
> fibrosis or looking at the greater or equal to 50 percent, I think
> each of them are highly discriminatory.
>
> DR. GULICK: Thank you.
>
> DR. BROWN: I was going to make a scientific comment. I was hoping Anna
> would still be here, but I think we can still discuss it briefly. I
> had the impression from this morning\'s analyses that I think were the
> most thorough done to date that there may be a little more correlation
> between the serologic parameters than there is between any serologic
> parameter in histology improvement.
>
> I don\'t know if that is worth digging up at this point or whether we
> have moved on, Mr. Chair, but that might speak to the kind of
> precision that we need in large active-control designs. If there is
> more correlation between the serologic endpoints, it does speak to the
> composite serologic approach that Anna talked about and it may be
> related to the issue that Brian Wong mentioned that I also mentioned
> which is the variance in histology measures is part of the scientific
> issue here.
>
> DR. GULICK: Thanks.
>
> DR. BROWN: So the question is, is there more correlation between
> serologic parameters. I don\'t know if Greg Soon can comment on that
> or whether he looked at that. I had the impression from Anna\'s data
> that she got from both Glaxo and Gilead that that might be true. But I
> don\'t know if Dr. Soon can comment.
>
> DR. GULICK: Dr. Soon?
>
> DR. SOON: The only thing I looked at is the e-antigen loss versus the
> Knodell score. That has a correlation of approximately about 0.3, the
> same strength as in HBV DNA.
>
> DR. GULICK: Anybody else?
>
> We have a number of sort of rapid-fire endpoint questions. So let\'s
> try to rapidly fire them. What is the timing of the primary endpoint.
> Dr. Schapiro, before he left, suggested that 48 weeks is a reasonable
> time point. Dr. Wood?
>
> DR. WOOD: I think one of the issues is that the appropriate timing of
> endpoints is also going to depend on the patient population because we
> have clearly seen with e-antigen-negative individuals, given the
> fluctuation in their clinical course, that they may actually require a
> longer duration for evaluation in terms of efficacy. So it might not
> only be 48 weeks but then, again, at 72 and 96 for that particular
> cohort since they are e-antigen-negative.
>
> DR. GULICK: So, long-term follow up critical.
>
> Dr. DeGruttola?
>
> DR. DeGRUTTOLA: I just had a question for the clinicians whether you
> might have an endpoint like time to reaching certain kinds of
> improvement; for example, in the composite endpoint, if you need to go
> below a certain level in the Knodell score and ALT or something else,
> could that be an endpoint where you wouldn\'t require that it would be
> a specific length of time but follow until certain benefit occurred.
>
> DR. GULICK: Dr. Kumar was getting at that yesterday.
>
> DR. KUMAR: And I really got to that which, again, in my mind is not
> resolved, is at what point do you say that a patient is not responding
> to the treatment?
>
> DR. GULICK: Dr. Wong?
>
> DR. WONG: I think, Victor, that is a nice idea. If someone could come
> in and show that a new drug is superior to a standard drug in that
> respect, that would be very convincing, that that was an effective
> drug. But the other point I wanted to make about the timing, I think
> that there are also situations in which substantially shorter periods
> of time than 48 weeks might be relevant such as the patients with
> decompensated liver disease.
>
> If someone could come in and show that, in twelve weeks, for example,
> there was a substantial increase in albumin, prothrombin time, et
> cetera, as compared to either historical controls or, let\'s say 3TC,
> that would also be, to me, a convincing demonstration of efficacy and
> it wouldn\'t be necessary to show long-term results in a different
> sort of population.
>
> So, any of these. If a sponsor can show that a drug has clinically
> relevant beneficial effects as compared to an appropriate control
> group, that should do it. I don\'t think that there is any specific
> length of time specific endpoint, that should be put up as a necessary
> condition.
>
> DR. GULICK: Dr. Englund?
>
> DR. ENGLUND: I just want to say that Dr. DeGruttola\'s approach is
> going to be particularly useful when we talk about moving these drugs
> into the pediatric patient population because we really don\'t want to
> put five-year-old children on 40 years of drugs. We are going to want
> to try and limit the amount of drug exposure.
>
> So you can see for certain patient populations, that approach is
> really going to help give an answer.
>
> DR. GULICK: Other comments about timing? Dr. Birnkrant?
>
> DR. BIRNKRANT: What about moving to the hepatitis C model\--that is,
> looking at sustained viral response off therapy. Are there any
> comments related to that? You end your treatment at 48 weeks and then,
> six months to twelve months later, off therapy is when you assess.
>
> DR. SHERMAN: Can I try that one?
>
> DR. GULICK: Sure.
>
> DR. SHERMAN: We are not getting anything comparable to sustained
> response. The comparable outcome would be clearance of HbSAg. Since
> that has not been discussed at all and is a very, very rare event, I
> don\'t think that that is what we can use as an outcome at this point.
>
> DR. BIRNKRANT: So then are we seeing that we are comfortable with
> 48-week data predicting chronic use? In other words, 48-week data
> supports five years of the drug?
>
> DR. SHERMAN: No.
>
> DR. BIRNKRANT: Which is a way of asking when do we stop treatment.
>
> DR. SHERMAN: No. I mean, this is obviously the issue that came up
> yesterday. On the part of a pharmaceutical company, they have to have
> a line and say, here is what I am going to come forward with my
> information for you all to make a decision. But they also have a
> responsibility for these drugs that don\'t lead you to, in essence, a
> cure of the condition, to continue to provide data and come back to
> the agency with that data supports continued use as time goes on. In
> clinical practice, that it what will happen in most of these patients.
>
> DR. GULICK: Other comments about duration? Dr. Kumar?
>
> DR. KUMAR: But shouldn\'t there be something that says, in patients
> who finally we made the decision to stop because they converted from
> e-antigen to e-antibody, that, in these patients, the durability of
> response I think may be important as one of our endpoints.
>
> DR. GULICK: So, in general, we reaffirm that 48 weeks for compensated
> disease, although all of us were interested in longer-term follow up
> as come out yesterday, Dr. Sherman\'s point that shorter endpoints
> might be appropriate\--or, sorry; Dr. Wong\'s\--for decompensated
> disease to show a difference. Patient population is important. And
> then Dr. DeGruttola\'s suggestion, maybe time to response would be a
> novel way of looking at this, particularly in the pediatric
> population. We dismissed the Hepatitis C model because this is not a
> curative therapy, at least at this point.
>
> Secondary endpoints, rank order. Do you want us to consider that or
> have we spent some time talking about\--
>
> DR. MURRAY: I don\'t think you need to order them. I think we have got
> the idea on their relative value.
>
> DR. GULICK: The next question was about histology. I think we have
> spent some time talking about this already, too.
>
> DR. MURRAY: Yes; I think we have devoted sufficient time to that.
>
> DR. GULICK: How about the virologic assay?
>
> DR. MURRAY: If anybody has any comments. I know we didn\'t spend much
> preparation time in talking about what the different assays were, but
> if anybody has an opinion on if an assay should be used. Sometimes, we
> get a question whether PCR versus just an assay which has a higher
> sensitivity limit, so if there is a strong feeling that a PCR assay
> should be included in all development plans, then we would like to
> hear that voiced, I guess.
>
> DR. GULICK: Dr. Wong?
>
> DR. WONG: I think the viral load should be treated as continuous
> variables. Having specific cutoffs is probably misleading. I,
> personally, believe it has been misleading in HIV Since it is a
> continuously variable function, it should be treated that way.
>
> DR. GULICK: Dr. Stanley, before she left, really had a question about
> the viral cutoffs and what the clinical significance of those cutoffs
> is. I guess both Drs. Lok and Hoofnagle suggested some cutoffs for
> different populations. Where do those numbers come from? What do they
> mean clinically?
>
> DR. HOOFNAGLE: I think the Glaxo and Gilead trials will help to answer
> these, is there a level below which you see histology improvement and
> above which you don\'t. But in a couple of studies that have been done
> in so-called inactive carriers of hepatitis B, virtually 95 percent
> have levels of HBV DNA below 10^5^. So that has been kind of used as
> the upper limit of defining someone as an inactive carrier.
>
> The trouble with that is that there are people with e-negative chronic
> hepatitis B who fluctuate down and may actually fall even to
> undetectable by PCR spontaneously and yet come back up, and so forth.
> So it is a bit of a moving target.
>
> But if we are looking at suppressive therapy, I think it would be good
> to know at what level of suppression do you see biochemical and
> histological improvement.
>
> DR. GULICK: Has that correlation really been done up until now?
>
> DR. HOOFNAGLE: It hasn\'t been done until we had these more sensitive
> assays that are reliable. We had assays in our lab, but they weren\'t
> as reliable as the ones that are commercially available now. The
> hybridization tests of old are just above what you need. We say 10^5^,
> but that is very optimistic. It is really like two times 10^5^ or
> 10^6^ that they become negative.
>
> Furthermore, at the low levels, those assays have problems with false
> positivity.
>
> DR. WONG: Right. But one of the problems with\--even if 10^5^ turns
> out to correlate, if we say that 10^5^ is what we are going to shoot
> for, that might result in our deciding that a drug that, let\'s say,
> moves people from 10^10^ to 10^6^ will not be considered an active
> drug. I think that would not be right.
>
> So if we look at change in viral titer, at least in addition\--I am
> not necessarily suggesting instead\--but at least that that is an
> additional criterion for antiviral effect, I think we will be better
> off.
>
> DR. HOOFNAGLE: We would be better off if everybody were PCR-negative
> on therapy. So all these things can be looked at as secondary
> endpoints but, if you wanted a composite endpoint and you need a viral
> definition, I am not sure we can give it to you yet.
>
> DR. BLOCK: But if I can just add, of course we would all rather see
> PCR negativity. Actually, it would be very nice to have some kind of
> standardization\--that is another plea\--some kind of standardization
> for these tests which can vary wildly from laboratory to laboratory.
>
> But what I saw from the briefing documents and from what Dr. Murray
> gave was surprising to me and that was that the best correlations with
> other endpoints was a change in DNA, a relative change in DNA, of at
> least 10^2^. Actually, it didn\'t have to be 10^2^. I mean, if you
> followed that chart that you put up, it actually kind of plateaued.
> Once you dropped about a thousand-fold, 10^2^, 10^3^, it didn\'t buy
> you much more correlation or improvement.
>
> That, obviously, has to be looked at more, but it looked to me, and
> that was consistent with what I inferred from the briefing document,
> that it was actually the relative change. That may reflect the poor
> standardization from one test to the other, so one person\'s 10^5^
> might be another person\'s so many genome equivalents.
>
> So that\'s why I would suggest that you don\'t get hung up on absolute
> values yet. Some day, that probably would make sense. But it seemed to
> me like it was relative change. If you had to aim towards something,
> you probably could get there with the data you have now deciding what
> the relative change should be.
>
> DR. HOOFNAGLE: As far as the FDA is concerned, as far as new drugs
> coming in, I think you have to ask them to use these more sensitive
> assays. I think you miss a lot with the just hybridization assays.
>
> DR. BLOCK: I agree with Dr. Hoofnagle. But then, of course, bear in
> mind that will create a whole new world, a new family, of data in
> terms of values. It shouldn\'t, but it will. You are talking about the
> real-time PCR.
>
> DR. HOOFNAGLE: This is just a standard PCR. It is not real-time is it?
> It is the Roche assay.
>
> DR. BLOCK: Even that would be different than the branch change, than
> the dot blot.
>
> DR. GULICK: Dr. Englund?
>
> DR. ENGLUND: I just want to say that I think that we, the committee,
> should endorse standardization. If we are going to use a company\'s
> assay, then that has to be standardized, which other people are doing.
> But we also need to be saying that, in terms of resistance assays and
> looking toward the future, that those should be standardized so that
> the values from one study can somehow be comparable to values from
> another study. I am talking more of the phenotype as opposed to
> genotype.
>
> DR. GULICK: Dr. Wood? Same point, huh?
>
> DR. WOOD: Exact same point. I think that, by using an assay that we
> know is now commercially available that is standardized, that is
> sensitive, that is better than earlier generations, then, when
> applicants come, that will add to the database and allow
> cross-comparison studies so that we can better able get at, maybe,
> surrogate markers that might correlate with clinical outcomes because
> we have the identical surrogate marker across multiple larger studies
> in larger patient populations.
>
> DR. GULICK: So, in brief, we suggest using the more sensitive test. We
> would like to require standardization of the assays for comparison and
> that goes for resistance testing, too. Regarding cutoffs, some
> uncertainty whether the change in DNA versus the absolute value is
> important and we are looking forward to the correlation of this with
> other markers and histology.
>
> Shall we open it up for other comments about virologic assays?
>
> DR. BROWN: There are a number of companies engaged that I think have
> already pretty well gone with the quantitative PCR precedent although
> all the points that have been made today, I think we all realize are
> perfectly valid. But I think we are doing so, and maybe Carol and
> others could comment, precisely with the idea, hopefully, you have in
> mind which is we can learn more scientifically about what is important
> in terms of viral suppression.
>
> I agree with Dr. Wong\'s comment as well.
>
> DR. BROSGART: I would agree with Nat. I think that it was a limitation
> within the lamivudine database with using the Abbott Genostics assay
> is that you couldn\'t probe deep enough to look, then, at
> correlations. One opportunity now that we have, along with the agency
> where we have used a very sensitive assay, is to begin doing these
> more exploratory analyses that take a number of different endpoints
> and ask questions, what proportion of patients normalize ALT and get
> below a certain level of HBV DNA or have a certain delta in their HBV
> DNA and who, if it is an e-antigen-positive patient, lose e-antigen.
>
> We are beginning to do a lot of that work now. I think it is very
> interesting. I think, again, certainly in the e-antigen-positive
> patient, a lot of correlation with the delta in HBV DNA. It is a
> little different in the e-antigen-negative patient. There is a
> difference in the natural history of disease, and I think it is
> reflective, than in some of the outcomes.
>
> But I imagine, over the next number of months, that we will be able to
> work with the agency and they will get a clearer idea of what might be
> reasonable composites by looking at an existing database.
>
> DR. GULICK: Thanks.
>
> Let\'s go on to the last part of this endpoints question which I think
> is looking at appropriate endpoints for decompensated liver disease.
> That is the next one, I think. What is the feasibility and validity,
> and the particular suggested endpoints to consider are mortality,
> change in Child-Pugh or MELD score, need for transplant or
> liver-disease-associated complications.
>
> DR. SHERMAN: Can I try that one?
>
> DR. GULICK: Absolutely.
>
> DR. SHERMAN: Mortality is an endpoint that can be considered. Change
> in Child-Pugh or MELD is reasonable although, again, we don\'t know
> the validity of what degree of change is meaningful. There is
> tremendous variability in what MELD scores mean in different places,
> even today.
>
> In our region, a patient with a MELD less than 20 virtually never gets
> a liver so you could arbitrarily say that, if you took a patient less
> than 20, then maybe that is a good thing because it suggests that
> either they don\'t need a liver right away or, more likely, they are
> not going to get one right away.
>
> But those are arbitrary. Although the model has somewhat validated the
> decision about how much of a change would you need and from where you
> would need to go or some cutoff to get below to be meaningful is
> really not established. We would have to say something to the effect
> of predicted survival of one year is acceptable or unacceptable. Then
> you need to get above or below that point.
>
> Dr. Lok addressed, before, the issue of getting a transplant is highly
> variable. There are places in this country where you can get a liver
> within 30 days of listing, still, and other places where you wait two
> to three years. That is reflected, then, in the differences in
> mortality on the waiting list.
>
> So, if you do a multicenter trial and you use that as an endpoint, you
> will have considerable variability. The occurrence of
> liver-disease-associated illnesses, again, highly variable. Not every
> patient develops variceal bleeding. Not every patient develops SBP.
> Those are all added complications of late-stage decompensated disease
> but, if you can prevent those things as a cumulative group relative to
> two treatment arms, it would be important but what difference, again,
> would be important would be ultimately a clinical judgment and it
> would be very difficult to put a number on that.
>
> DR. HOOFNAGLE: Actually, Glaxo went through a long exercise of looking
> at endpoints here. The Child-Turcotte-Pugh score has been repeatedly
> shown to correlate with outcomes in patients with cirrhosis. We have
> to have cirrhosis to correlate with outcomes; for instance, survival
> after a portacable shunt, or survival to transplantation.
>
> So, I think a two-point improvement in the CPT score is a very good
> endpoint to use. The MELD score is supposedly an improvement on the
> CPT score and actually uses some of the same values. It has been
> refined nicely so that you can give a estimate of survival and you can
> use the MELD score, or the average MELD score, to give you your
> natural-history study.
>
> The trouble with the MELD score, then, though is, once you put a
> person on therapy and their MELD score begins to change, you don\'t
> know whether that correlates with improvement in survival. That is the
> problem, particularly because the MELD score includes the serum
> creatinine which may be a problem for adefovir, in particular. So it
> gets involved in the effects of the drugs independent of their effects
> on the disease.
>
> So I think it needs to be included in all the studies to test it out.
> But, for the time being, you are going to have to stick with the CPT
> score.
>
> DR. GULICK: Could you comment on mortality and liver-disease
> complications, just as suitable endpoints?
>
> DR. HOOFNAGLE: Oh, yes; those are solid endpoints. The trouble with
> mortality in liver disease is liver transplantation. Some people get
> it. Some people don\'t. So it becomes a variable.
>
> If you have decompensation, if you qualify for this, you already
> qualify to be on transplant lists. So time to entry into a transplant
> list, you also can\'t use. Time to transplantation is affected by so
> many other things that you don\'t have control over.
>
> DR. GULICK: It is getting kind of lonely at this end of the table. Was
> it something I said? Can we do something else today, or are we kind
> of\--
>
> DR. MURRAY: I think we can finish. The only thing is if anybody has
> any strong feelings on the questions under 1 and 2 about essential
> patient populations. So if anybody would like to just voice any
> comments on the populations that are essential that you would not like
> to see a marketing application not have.
>
> DR. GULICK: So which populations are essential for the marketing of a
> new drug.
>
> DR. MURRAY: For the initial marketing. If a sponsor came in without
> population X, you would tell them to resubmit at a later date.
>
> DR. GULICK: Dr. Hoofnagle?
>
> DR. HOOFNAGLE: I guess you are referring to something like
> HIV-positive patients. There, the problem is they are on lamivudine
> already, on Epivir, and you shouldn\'t give them interferon, I don\'t
> think. So it is a very different group. They get tenofovir instead of
> adefovir. So they are not really a group that is real important here
> in this analysis.
>
> Children are very important group. It is a different disease in
> childhood. You have different outcomes there. Long-term suppression
> doesn\'t sound too good to us. We would like to see it cured. So,
> there, the focus should really be on a defined period of treatment and
> trying to induce the seroconversion or loss of e or s.
>
> Other populations, both men and women, are included in trials. I am
> not sure what else would be excluded.
>
> DR. MURRAY: If it was restricted to just e-antigen-positive disease.
> Let\'s say, if there was no e-antigen-negative disease, could a drug
> get on the market without investigating that, they just looked at
> positive or compensated liver disease, no data in decompensated liver
> disease?
>
> DR. HOOFNAGLE: I would think any company really should try the
> e-negative group. They are really the group that responds best to
> these nucleosides so they are the nicest group to treat, in a way. I
> think they should be included. Decompensated liver disease is not that
> common a problem and I think there are a lot of things being thrown at
> them, so I am not sure that it is important that it be included in an
> initial evaluation.
>
> Racial and ethnic should be taken in mind. This is a disease that is
> very common in the Asian population. It is more common in blacks than
> whites, but the Asian population is the one with the largest\--
>
> DR. MURRAY: And your drug has activity to previous drugs such as
> lamivudine resistance and any drug coming along should know if it is
> active or not against that? It seems obvious, but\--
>
> DR. HOOFNAGLE: They would have to define whether it is effective at
> all against lamivudine-resistant virus, both in vitro and in humans,
> because, otherwise, you are looking at a lamivudine \"me too\" drug to
> compare. So the design there would be a little bit different than if
> you feel that it was a drug that was effective against
> lamivudine-resistant.
>
> DR. GULICK: Okay. How did we do?
>
> DR. BIRNKRANT: Very good.
>
> DR. GULICK: Good. I would like to thank the agency and those stalwart
> members of the committee who stayed right until the end, and the
> observers. Thanks very much. We will close the session.
>
> \[Whereupon, at 4:45 p.m., the meeting was adjourned.\]
>
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