## **To:** Members and Guests of the Antiviral Drugs Advisory Committee

**From:** The Division of Antiviral Drug Products

# 

# Re: August 7^th^ Advisory Committee Meeting to discuss clinical trial design issues in the development of drugs to treat chronic hepatitis B

### Date: July 10, 2002

# The purpose of this document is to provide background information for the Aug. 7^th^ advisory committee meeting, which is being convened to discuss issues in clinical trial design for the development of drugs to treat chronic hepatitis B disease. As you are aware there are two therapeutic agents approved for the treatment of chronic hepatitis B (CHB), interferon alpha and the antiviral drug, lamivudine. In addition, on Aug. 6th, the committee will be asked to provide comments on the safety and efficacy of a second antiviral drug, adefovir, to treat CHB (please refer to the separate adefovir background document). Also, several other anti-HBV drugs are currently in phase 2 and 3 development. Given recent advances in the field, the Division believes this is an opportune time to discuss clinical trial design issues in hepatitis B drug development. Although therapeutics for CHB includes both antiviral drugs and immune modulators, we would like the discussion on Aug.7 to focus primarily on antiviral drugs, and on the design of the principal phase 3 studies intended to support registration. 

The attached references and information/analyses included in this
document are intended to aid the committee as they address these issues.
In the initial planning for this advisory committee meeting, the
Division asked pharmaceutical sponsors to submit written opinions on
clinical trial design issues. They were asked to support any conclusions
with references or data from their own drug development. This background
document was written taking into consideration information from these
submissions.

Please see attachment A for the discussion points/questions that the
advisory committee will be asked to address. In brief, the discussion
points focus on the following issues: the appropriate and essential
patient groups that should be studied in CHB drug development, selection
of control arms for phase 3 studies, the most appropriate endpoint or
combination of endpoints to evaluate efficacy, and the type of
information that should be collected during longer-term follow-up in
phase 3 studies. Background information pertinent to each of these
issues is presented in the following sections along with the
corresponding questions/discussion points (in boxes at the beginning of
each section below) that the committee will be asked to address.

**1.0 Patient Populations**

> *Advisory Committee Discussion Points*
>
> *1. Identify patient populations that are appropriate targets for
> treatment studies (consider attributes such as stage of disease, viral
> genotype, co-morbidities, lamivudine resistance, IFN-experience,
> pediatrics, HBeAg-/HBV DNA+). Please include demographics in your
> discussion, i.e. race and ethnicity.*
>
> *2. Which of the aforementioned patient subgroups are essential in a
> marketing application? In particular, comment on race and ethnicity,
> disease stage and co-morbidities.*

Hepatitis B drugs are developed globally. While an estimated 1.25
million individuals in the United States are chronically infected with
HBV (surface antigen positive for at least 6 months), approximately 350
million persons are chronically infected worldwide \[1\]. Therefore it
is reasonable that a development program would study patients with CHB
throughout the world. However, from a regulatory standpoint, a marketing
application should also contain safety and efficacy data that includes a
fair representation of CHB patients from the U.S. In the U.S. CHB is
more common among African Americans than Caucasians but rates are
highest among Asian Americans, especially immigrants. \[2\]

We would like the committee to focus on both demographics
(race/ethnicity) and disease characteristics when considering patient
groups that are most appropriate for establishing safety and efficacy in
principal phase 3 studies. We would also like the committee's opinion
regarding the essential patient groups to support a marketing
application considering that certain demographic and disease
characteristics may be correlated, such as race/ethnicity and frequency
of CHB with precore mutant.

After discussing the important subgroups that should be studied and
included in a marketing application, the Division would like the
committee to comment on the types of studies that should be conducted to
obtain data in various subgroups. The committee should comment on
whether it is advisable or necessary to conduct [separate]{.underline}
studies for certain disease characteristics or whether larger studies
should be conducted that stratify randomization based on baseline
characteristics. Information on the response rates in various patient
subgroups will help to address this question. For example, response
rates appear to be fairly similar for HBeAg negative or positive CHB
among patients treated with antivirals such as lamivudine; however
response rates differed for these two groups in studies of interferon
(patients with HBeAg negative disease showed a lower response than those
with HBeAg positive disease)\[3\].

A high level of morbidity or other factors may make it difficult to
conduct a randomized controlled study in certain patient groups.
Patients at imminent risk of complications may be better suited to
enroll in open-label expanded access safety studies. For subgroups with
certain demographics or disease characteristics, such as co-infection
with HCV or HIV, we would like the committee to comment on whether it is
essential that adequately-powered, randomized controlled studies be
completed for all subgroups, or whether it would be more appropriate to
include these patients in larger pivotal studies or in studies with
alternative designs. Another issue to consider is whether all current
drug candidates should be studied for activity against lamivudine
resistant populations.

**2.0. Selection of Controls**

> *Advisory Committee Discussion Points*
>
> *3a. Discuss the role of the following controls in the compensated
> liver disease group:*

-   *Placebo controls/delay of initiation of treatment; and of what
    duration?*

-   *Active controls: Lamivudine (or other antiviral drug) monotherapy
    or Interferon*

> *3b. Please also discuss controls for patients with decompensated
> liver disease or those who have failed previous regimens*

We would like the committee to comment on selection of control groups
for studies evaluating drugs in both compensated and decompensated liver
disease due to CHB. Most experts appear to agree that placebo controlled
trials in patients with decompensated liver disease would not be
acceptable. In addition, many investigators contend that
placebo-controlled phase 3 studies in patients with compensated liver
disease are also no longer acceptable because several approved therapies
for CHB are available. However, factors other than drug availability may
be important when considering the feasibility of placebo controlled
studies. These factors may include the rate of disease progression
without treatment (risk to the study participant) and the certainty in
which the optimal choice and timing of an initial regimen is known
(clinical equipoise). Although rapid progression to cirrhosis has been
documented among some individuals, CHB is generally considered to be
slowly progressive for most individuals. Among patients with CHB
referred to clinical centers, the incidence of cirrhosis is estimated to
be up to 2-3% per year \[1\]. For patients with compensated cirrhosis
the 5 year survival rate is 84% \[1\]. Thus, most patients would not be
expected to have substantial morbidity if left untreated for a period of
time (perhaps up to one year). In addition, in one of the pivotal
studies for lamivudine, 2 point worsening in the HAI occurred in 24% of
patients on placebo compared to 11% on lamivudine \[4,5\] (an absolute
difference of 13%).

The optimal timing and choice of initial therapy for hepatitis B does
not appear to be definitively established. As stated in a summary of a
workshop sponsored by the National Institute of Diabetes and Digestive
Kidney Diseases (NIDDK) and the American Gastroenterological Association
\[2\] regarding recommendations for starting therapy,

> "Currently, therapy of hepatitis B is difficult and limited in
> long-term efficacy. Therefore the decision to initiate therapy should
> not be taken lightly and should be based on a combination of serum
> liver tests (ALT elevations), virologic assays (presence of HbeAg
> and/or HBV DNA at levels \> 10^5^ copies /mL), liver histology
> (presence of moderate disease activity and fibrosis), and virologic
> testing to exclude concurrent hepatitis C or D and HIV infection. **In
> patients with mild disease, it is appropriate to monitor ALT levels
> and defer therapy until advances have been made that allow for
> sustained benefit in most patients. At issue is what criteria should
> be used to define moderate-to-severe disease and to recommend
> therapy** \[emphasis added\]."

Therefore, it appears that there may be equipoise, at least for some
patient groups, to consider deferred therapy, pending future clinical
studies. If placebo controlled studies (or "treatment-deferred studies")
are not acceptable for 48-week phase 3 studies, we will ask you to
comment on whether they are still feasible for shorter-term (\< 6
months) dose-ranging studies or other phase 2 studies.

The alternative to placebo-controlled studies is active-controlled
studies comparing a new drug with interferon, lamivudine, or
subsequently approved agents. It must be recognized that active
controlled studies will require larger sample sizes to assess
non-inferiority. Sample size will also depend on the endpoint chosen. If
lower frequency events are chosen for an endpoint (such as
seroconversion), then a smaller delta will be needed, this will in turn
require a much larger sample size.

Another issue regarding active controlled studies with lamivudine is the
known risk of emergence of resistance to lamivudine. In addition because
of interferon's route of administration and tolerability profile,
blinding active controlled studies with interferon will not be feasible.

For decompensated disease active controlled studies with lamivudine
could be used, whereas interferon is not recommended for decompensated
patients. However, one must consider that many patients with
decompensated liver disease may have already developed resistance to
lamivudine and may not be willing to participate in a controlled study
with lamivudine. The other issue is whether the treatment effect of an
active control in decompensated hepatitis is adequately known relative
to placebo in order to choose an appropriate delta for a noninferiority
study.

**3.0 Evaluation of Efficacy: Endpoints**

**3.1 Compensated Liver Disease**

*Advisory Committee Discussion Points*

4.  *Considering the patient populations identified in question #1, the
    information presented, and the necessity that endpoints for
    registration be clinically meaningful, please answer the following:*

-   *Which endpoint (or combination of endpoints) should be the primary
    in clinical trials? Please discuss histologic, serologic,
    biochemical, and virologic endpoints.*

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-   *When should the assessment of the primary endpoint be made?*

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-   *List the most appropriate secondary endpoints and rank them in
    order of importance.*

> *5. For histologic endpoints, what is the preferred method of
> histologic scoring? What degree of change in histologic score is
> clinically meaningful?*
>
> *6. For virologic endpoints, which assay is best suited for clinical
> trials? What is the appropriate cutoff point for HBV DNA (eg. \<10^5^,
> \<10^4^, etc)? Should viral genotyping be done and why?*

Probably the most pressing issue confronting clinical studies evaluating
drugs to treat CHB is the choice of primary endpoint. Choice of endpoint
may depend on the population studied such as, compensated vs.
decompensated liver disease, and presence or absence of e antigen. From
a regulatory standpoint, primary endpoints that assess differences in
clinically meaningful outcomes are generally required. For CHB, the
ultimate goal of treatment is to prevent clinical sequelae such as
cirrhosis complications, hepatocellular carcinoma, or death. However,
given the amount of time required to detect treatment arm differences
for such outcomes in patients with compensated liver disease, studies
employing these endpoints would not be logistically feasible. Thus to
support the approval of lamivudine a histologic endpoint was considered
to be a stringent primary endpoint in that the disease in the end organ
could be directly visualized. Changes in histology have been the
recommended primary endpoint for subsequent phase 3 drug studies.
However, it must be recognized that even liver histology is a surrogate
for the desired clinical endpoints. In CHB drug development, multiple
secondary endpoints have been evaluated to support efficacy including
biochemical, serologic and virologic parameters.

When selecting an endpoint, one must consider the choice of measurement
(e.g., histologic, HBV DNA), the timing of the measurement (e.g., I year
on treatment), and the magnitude of change in measurement deemed to be
clinically meaningful (e.g., suppression of HBV DNA below a threshold,
loss of e antigen, or changes or improvement in histologic scores). One
may also consider using a composite endpoint consisting of two or more
measurements (ALT + HBV DNA).

The following sections review some of the advantages and disadvantages
of several possible endpoints for evaluating CHB drugs. In addition,
data showing correlations between the endpoint and clinical outcome or
with histologic outcome are presented when available.

[3.1.1 Histologic Endpoint]{.underline}

To date, histologic improvement has been the recommended primary
endpoint for regulatory purposes in studies of antiviral drugs to treat
CHB. For lamivudine and adefovir, histologic changes served as the
primary endpoint in pivotal registrational studies. For lamivudine
studies the proportion of participants with a 2 point improvement in the
total Histologic Activity Index (Knodell score)\[4\] was used. For
adefovir the definition of improvement was slightly modified to include
a 2 point reduction in the Knodell score with no worsening of the
fibrosis score.

Some contend that there will be a lot of missing data for histologic
endpoints because of patient refusal to undergo a second biopsy or
because of specimen mishandling. But the lamivudine and adefovir phase 3
trials do not support this opinion. There was lack of paired biopsy
specimens in approximately 15-21% of patients participating in
lamivudine studies and in only 5-9% in adefovir phase 3 studies.

*Advantages:*

-   direct visualization of inflammation and changes in structure of the
    liver;

-   histologic treatment difference between active drug and placebo is
    sufficiently large (approx. 30% difference in 2-point improvement)
    to allow for "reasonably sized" studies

*Disadvantages*:

-   invasive procedure

-   multiple assessments (more than two) not feasible on a large scale

-   variability in measurement owing to small sample or subjectivity of
    reading

-   because of limited sampling cannot provide information regarding the
    time course of the response; unlikely to provide guidance on the
    duration of therapy

*Correlation with clinical outcomes*:

-   no analyses correlating treatment induced changes in the Knodell
    score and ultimate clinical outcome, such as the development of
    cirrhosis related complications, hepatocellular carcinoma, or death

[3.1.2 Serologic Endpoints]{.underline}

Serologic endpoints include clearance of e antigen, e antigen
seroconversion (defined as e-antigen loss, e-antibody gain and
suppression of HBV DNA \< 10^5^ copies), or clearance of surface antigen
with acquisition of surface antibody. These were important secondary
endpoints in previous drug development programs. In clinical practice e
antigen seroconversion is often the "endpoint" used for deciding when to
stop therapy \[1\].

*Advantages*:

-   noninvasive

-   can obtain measurements at multiple time points, can measure onset
    and duration of efficacy.

-   HBeAg seroconversion often used in the decision to stop treatment in
    clinical practice

-   loss of surface antigen considered as resolution of CHB

*Disadvantages*:

-   Can't use e antigen seroconversion in studies of e-antigen negative
    CHB (precore mutant).

-   Loss of e-antigen may not be stable

-   May have histologic improvement even in the continued presence of
    e-antigen

-   Surface antigen loss is a low frequency event

-   Treatment differences in e-antigen seroconversion between active
    drugs and placebo is approximately 10% at I year. For noninferiority
    studies this would require a delta of \< 10 %. This would
    necessitate large sample sizes or longer studies. Larger treatment
    differences between active drugs and placebo would be expected for
    clearance of e antigen (without acquisition of Ab).

*Correlation with clinical outcomes*:

Loss of e-antigen and seroconversion have been shown to be associated
with a reduction in the risk of clinical complications of CHB. In
follow-up studies, interferon responders (loss of e-antigen and
sustained suppression of HBV DNA) had lower rates of liver related
complications and mortality \[6\].

[3.1.3 Virologic Endpoint]{.underline}

Reduction in HBV DNA is the preferred endpoint in phase 1 and 2
dose-ranging studies.

*Advantages*:

-   dynamic endpoint with rapid reduction/rebound with start or
    cessation of antivirals

-   quantitative, can measure at multiple time points

-   well suited to evaluate inhibition of viral replication by antiviral
    agents

*Disadvantages*:

-   different assays with different range of sensitivity

-   does not measure liver inflammation

*Correlation with clinical outcomes*

No analyses showing direct correlations with clinical outcomes. However
as discussed below, there is some information correlating changes in HBV
DNA with other outcomes (histologic, serologic) and there is indirect
evidence that lowering HBV DNA leads to clinical improvement in patients
with decompensated liver disease.

-   One small study suggested that patients maintaining HBV DNA levels
    \< 10^4^ genomes/mL are more likely to have HBeAg seroconversion
    (4/12 patients) than patients with HBV DNA levels \> 10^4^
    genomes/mL (0/11 patients) \[7\].

-   In studies of decompensated liver disease, patients receiving
    lamivudine demonstrated concomitant suppression of HBV DNA and
    improvement in Child-Pugh-Turcotte scores \[8,9\]. The authors state
    that previous studies have shown that spontaneous improvement in
    liver function is unusual in CHB patients with established cirrhosis
    and hepatic decompensation. Consequently, the improved liver
    function in these studies was unlikely to be due to factors other
    than the antiviral effect (i.e., HBV-DNA suppression) of lamivudine.
    This indirectly supports the notion that HBV DNA suppression is the
    mechanism through which the treatment effect is mediated for
    antivirals.

-   FDA conducted several analyses using data sets from the lamivudine
    and adefovir development programs evaluating correlations between
    changes in HBV DNA and improvements in histologic outcome (the
    currently recommended primary endpoint for registrational trials).
    These are shown in detail in section 5.0 below. In brief, for both
    drugs there was a weak correlation between year 1 HBV DNA levels and
    changes in histology scores when evaluating associations at the
    individual or trial level. However, such analyses may have been
    limited by substantial variability in histologic measurements, in
    which the intrasubject variability (standard deviation) for
    sequential biopsies is substantial. When evaluating the proportion
    of the histologic treatment effect explained by HBV DNA some
    lamivudine and adefovir studies, it appears that HBV DNA
    measurements were predictive of histologic outcome. The disparity in
    these results may be explained by the fact that analyses evaluating
    "proportion of treatment effect explained" are less influenced by
    the variability of the histologic measurements.

[3.1.4 Biochemical Endpoints]{.underline}

Biochemical endpoints typically include transaminases, AST and ALT.
Although a single measurement is not a good indicator of hepatic damage,
measurements over time particularly when combined with other parameters
may be an indicator of changes in histology.

*Advantages:*

-   easy, inexpensive, can measure at multiple time points

-   with repeated measurements, elevated transaminases may correlate
    with liver inflammation

*Disadvantages*

-   an elevated ALT does not necessarily signal worsening disease but
    may herald clinical improvement

*Correlation with clinical outcomes*:

-   FDA analyses using data sets from the lamivudine and adefovir
    development program show a modest correlation between reductions in
    transaminases and changes in HAI. The correlation between changes in
    transaminases and histology was greater than that found for HBV DNA
    and histology. These are shown in section 5.0 below.

**3.2 Endpoints: Decompensated Liver Disease**

###### Advisory Committee Discussion Points

7.  *For patients with decompensated liver disease, please discuss the
    feasibility/validity of the following alternative endpoints:*

-   *mortality*

-   *change in Child-Pugh score (or its components)*

-   *transplant/no transplant*

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-   *occurrence of liver disease associated illness (variceal bleed,
    SBP, etc)*

Several uncontrolled studies have been conducted using antivirals to
treat patients with decompensated liver disease secondary to CHB. In
studies, decompensated liver disease generally includes patients with
Child-Pugh (CP) scores of B and C (appendix C). In studies of both
lamivudine \[8,9\] and adefovir (see Aug. 6 background documents),
patients experienced improvements in CP score concomitant with
reductions in HBV-DNA. Some patients were removed from wait lists for
transplantation. In addition comparisons of mortality rates with
historical controls (realizing the caveats of historical controls)
appeared to show improvement. From what is known regarding the natural
history of decompensated liver disease, spontaneous improvements without
intervention would be highly unlikely.

**4.0 Long Term Follow-up**

*Advisory Committee Discussion Points*

*8. Beyond the assessment of the primary endpoint for registration, what
is the appropriate duration of studies for treatment of CHB infection,
and what kind of information should be gathered?*

Since many patients with CHB require prolonged treatment with antivirals
to maintain a treatment response, there will be value in collecting
long-term data. Although studies of I year duration (or less) have been
used to approve previous therapeutic agents for hepatitis B, a longer
duration of follow-up may show further improvements in markers of CHB.
Based on the adefovir data, mean changes in HBV DNA appear to slowly
decrease over time (even after one year) and additional people show loss
of e antigen or seroconversion.

In addition, longer-term studies should be conducted to assess the
occurrence of any late-occurring toxicities or maintenance of treatment
response of patients who have discontinued therapy

**5.0 FDA Exploratory Analyses of Clinical Trial Data**

## This section describes the outcomes of exploratory analyses correlating measurements such as ALT and HBV DNA with histologic outcomes at 48 weeks. Additional data may be presented to the committee on August. 7th.

## **5.1 Description of Data Sources**

The following analyses were conducted using data from NDA reviews of
lamivudine and adefovir. The tables below list the studies included in
the exploratory analyses. Treatment groups, respective sample sizes, and
the frequency of missing biopsies are shown. Only subjects who had a
baseline and follow-up biopsy were included in these exploratory
analyses. The total number of patients from the two NDAs is 1573, of
whom 1372 had biopsies at one year. Among 1372 subjects evaluable for
biopsy, 17 subjects had missing ALT or HBV DNA at the end of one year.

### Table 5a: Lamivudine Studies Included in Exploratory Analyses

+---------------+------------+-----+-----+-----+-----+----+---------+
| **Lamivudine  |            |     |     |     |     |    |         |
| (N=901)**     |            |     |     |     |     |    |         |
+---------------+------------+-----+-----+-----+-----+----+---------+
| ####          | ####### ** | ### | *   | **L | **  | *  | **      |
| ### **Study** | Protocol** | ### | *LA | AM2 | LAM | *I | Missing |
|               |            | # * | M10 | 5** | +IF | FN | B       |
|               |            | *PB | 0** |     | N** | ** | iopsy** |
|               |            | O** |     |     |     |    |         |
+---------------+------------+-----+-----+-----+-----+----+---------+
| **US**        | **         | 63  | 62  |     |     |    | 17%     |
|               | NUCA3010** |     |     |     |     |    |         |
+---------------+------------+-----+-----+-----+-----+----+---------+
| **IFN         | **N        | 54  | 110 |     | 59  |    | 21%     |
| N             | UCAB3011** |     |     |     |     |    |         |
| onresponder** |            |     |     |     |     |    |         |
+---------------+------------+-----+-----+-----+-----+----+---------+
| **Asian**     | **         | 68  | 131 | 134 |     |    | 10%     |
|               | NUCB3009** |     |     |     |     |    |         |
+---------------+------------+-----+-----+-----+-----+----+---------+
| **Act         | **         |     | 81  |     | 72  | 67 | 21%     |
| ive-control** | NUCB3010** |     |     |     |     |    |         |
+---------------+------------+-----+-----+-----+-----+----+---------+
| **Total**     |            | 185 | 384 | 134 | 131 | 67 | 16%     |
+---------------+------------+-----+-----+-----+-----+----+---------+

Table 5b: Adefovir Studies Included in Exploratory Analyses

+------------------+-------------+-------+---------+--------+---------+
| **Adefovir       |             |       |         |        |         |
| (N=672)**        |             |       |         |        |         |
+------------------+-------------+-------+---------+--------+---------+
| #                | ####### *   | ##### | **      | **A    | **      |
| ###### **Study** | *Protocol** | ## ** | ADV10** | DV30** | Missing |
|                  |             | PBO** |         |        | B       |
|                  |             |       |         |        | iopsy** |
+------------------+-------------+-------+---------+--------+---------+
| **HbeAg+**       | **          | 161   | 168     | 165    | 9%      |
|                  | GS-98-437** |       |         |        |         |
+------------------+-------------+-------+---------+--------+---------+
| **HbeAg-**       | **          | 57    | 121     |        | 5%      |
|                  | GS-98-438** |       |         |        |         |
+------------------+-------------+-------+---------+--------+---------+
| **Total**        |             | 218   | 289     | 165    | 8%      |
+------------------+-------------+-------+---------+--------+---------+

Patients randomized to interferon-containing regimens were treated for
24 weeks followed by an off-treatment period, all other patients were
treated for one year. Biopsies were done after one year.

HBV DNA and ALT levels were typically measured every 4 weeks. For
lamivudine studies, the HBV DNA was measured by Abbott hybridization
assay, which has a very high lower limit (around 500,000 copies/mL by
some conversion method). Adefovir trials used PCR assay, which has a
lower limit of 400 copies/mL. The high lower limit for the assay used to
measure HBV DNA in lamivudine studies may impose limitations on the
interpretability of the correlation analyses of HBV DNA and histology.

## **5.2 Procedures**

Analyses exploring the relationship between average year 1 HBV DNA
(log~10~) levels or changes in ALT and histologic outcomes were
conducted using four methods.

-   The first method examined individual patient level correlations

-   The second method simply involved plotting average Year 1 absolute
    HBV DNA level vs. change in histology for each treatment arm in
    several studies. Studies were subdivided into smaller "trials"
    determined by region and race to increase the number of data points.

-   The third method examined trial level correlations, i.e., the
    correlation of treatment effects (treatment differences between drug
    and placebo) for change in ALT or year 1 absolute HBV DNA vs.
    treatment effects on biopsy score. As in method 2, studies were
    divided into smaller "trials" determined by region and race to
    increase the number of data points for trial level correlation.

-   The fourth method evaluated the proportion of treatment effect
    (change in Knodell score) explained by changes in ALT or year 1 HBV
    DNA.

Both ALT and HBV DNA was converted to a log~10~ scale. In all analyses,
patients with missing values were excluded.

For analyses examining individual correlations, coefficients were
computed for each study and each treatment arm. Within studies,
consistency in how certain parameters (i.e., ALT or HBV DNA) predict
histologic outcome were explored by fitting a linear model and examining
the treatment by surrogate endpoint interaction. An overall correlation
for each study was computed after adjustment for treatment effect.
Similarly, consistency in the relationship between change in ALT or year
1 HBV DNA vs. histologic outcome was examined.

Trial level correlation examines how treatment responses in potential
surrogate endpoints relate to treatment effects on biopsy across many
different trials in order to evaluate how well the potential surrogate
markers could predict the biopsy outcome in a future trial. It should be
noted that some of the trials used in these analyses had more than two
treatment arms. To generate independent data for studies with more than
two treatment arms, the control was re-randomized into several subgroups
to be combined with the treatment groups. This was done for Asian
lamivudine study and adefovir study 437. For example, for study 437 the
placebo arm was re-randomized equally into two arms to form two new
two-arm studies. This was not done for IFN-containing regimens.

### 

3.  **Results of Exploratory Analyses**

##### **5.3.1 HBV DNA vs Histology**

[Individual-Level Correlation (method 1)]{.underline}

Table 5c shows correlation coefficients for year 1 log~10~ HBV DNA level
vs. changes in Knodell score at one year in lamivudine studies. Table 5
d shows the same for adefovir studies. Note that the assay used in the
lamivudine studies had an insensitive lower limit. Many patients
achieved suppression below this assay limit, therefore the assay could
not differentiate among these subjects. The correlation between year 1
HBV DNA and changes in Knodell score is relatively weak. For adefovir
studies, the correlation for the HBeAg negative group (study 437) was
weaker than that of the HBeAg positive group (study 438)

Although the correlations would be considered to be weak, they were
statistically significant when combining studies (overall) for each
drug. Note that all correlations were adjusted for study and randomized
treatment (\* = significantly different from 0 at level 0.05, \*\* =
significance level at 0.0001).

**Table 5c: Individual Correlation Analyses for Lamivudine Studies**

######## Year 1 HBV DNA vs. Change in Knodell Score

+-----------------+-------+-------+-------+-------+-------+---------+
| **Lamivudine**  |       |       |       |       |       |         |
+-----------------+-------+-------+-------+-------+-------+---------+
| ##              | ##### | **    | **LA  | **L   | **    | **Ov    |
| ##### **Study** | ## ** | LAM** | M25** | AM+** | IFN** | erall** |
|                 | PBO** |       |       |       |       |         |
|                 |       | **    |       | **    |       |         |
|                 |       | 100** |       | IFN** |       |         |
+-----------------+-------+-------+-------+-------+-------+---------+
| #### US         | 0.19  | 0     |       |       |       | 0.30\*  |
|                 |       | .41\* |       |       |       |         |
+-----------------+-------+-------+-------+-------+-------+---------+
| **IFN           | 0.27  | 0     |       | 0.6   |       | 0       |
| Nonresponder**  |       | .34\* |       | 2\*\* |       | .40\*\* |
+-----------------+-------+-------+-------+-------+-------+---------+
| **Asian**       | 0.23  | 0.16  | 0     |       |       | 0       |
|                 |       |       | .29\* |       |       | .22\*\* |
+-----------------+-------+-------+-------+-------+-------+---------+
| **A             |       | 0     |       | 0.31  | 0     | 0       |
| ctive-control** |       | .28\* |       |       | .34\* | .31\*\* |
+-----------------+-------+-------+-------+-------+-------+---------+
| **Overall**     | 0     | 0.2   | 0     | 0.4   | 0     | 0       |
|                 | .23\* | 8\*\* | .29\* | 6\*\* | .34\* | .30\*\* |
+-----------------+-------+-------+-------+-------+-------+---------+

LAM: lamivudine. PBO=Placebo. IFN=interferon

**Table 5d: Individual Correlation Analyses for Adefovir Studies**

######### Year 1 HBV DNA vs. Change in Knodell Score

+--------------------+----------+----------+----------+-------------+
| **Adefovir**       |          |          |          |             |
+--------------------+----------+----------+----------+-------------+
| ####### **Study**  | #######  | *        | *        | **Overall** |
|                    |  **PBO** | *ADV10** | *ADV30** |             |
+--------------------+----------+----------+----------+-------------+
| **Study 437        | 0.33\*\* | 0.35\*\* | 0.36\*\* | 0.34\*\*    |
| HbeAg+**           |          |          |          |             |
+--------------------+----------+----------+----------+-------------+
| **Study 438        | 0.13     | 0.05     |          | 0.09        |
| HbeAg-**           |          |          |          |             |
+--------------------+----------+----------+----------+-------------+
| **Overall**        | 0.28\*\* | 0.26\*\* | 0.36\*\* | 0.29\*\*    |
+--------------------+----------+----------+----------+-------------+

### [Plot of HBV vs. Histology (method 2)]{.underline}:

Figure 5a is a plot of year 1 log~10~ HBV DNA vs. change in Knodell
score at 1 year for treatment groups in adefovir and lamivudine studies.
The plot shows a clear separation of data points for the lamivudine vs.
adefovir studies that is probably a reflection of the different assay
limits for the assays used for the two NDAs. For this reason, analyses
of trial level associations were conducted for each drug separately.

**Figure 5a: HBV DNA (log~10~) level at year 1 vs Change in Knodell
Score at 1 year for lamivudine and adefovir.**

![](media/image1.wmf){width="5.990277777777778in"
height="4.415277777777778in"}

L=Lamivudine 100mg, l=lamivudine 25mg, 0=Placebo, M=LAM+IFN, F=IFN
alone, A=adefovir 10 mg, a=adefovir 30 mg. Size of characters is
proportional to sample size.

[Trial Level Correlations: HBV vs. Histology (method 3)]{.underline}

The trial level correlations examine treatment differences in log~10~

HBV DNA (at 1 year) between treatment arms vs. treatment differences in
Knodell score change across studies.

Figure 5b shows the associations for adefovir trials. At trial level,
treatment differences for log~10~ HBV DNA at year 1 of therapy correlate
with treatment differences in the change in Knodell score with a
correlation coefficient of 0.41 (R^2^ = 17%, confidence limits, 0% to
49%).

**Figure 5b: Year 1 HBV DNA (log~10~) vs Change in Knodell Score at 1
year. Trial level correlations for adefovir studies.**

![](media/image2.wmf){width="5.995138888888889in"
height="4.610416666666667in"}

\*7's represent data points from adefovir study 437 and 8's represent
data points from 438.

Size of characters is proportional to sample size.

Figure 5 C shows the correlation for lamivudine studies, excluding
IFN-containing arms. The R^2^ value was only 5%, worse than that
observed for the adefovir trial level correlations.

**Figure 5c:** **Year 1 HBV DNA (log~10~) vs Change in Knodell Score.**

***Trial level correlations for lamivudine studies***

![](media/image3.wmf){width="5.995138888888889in"
height="4.610416666666667in"}

1=US Study, 2=IFN-non-responder Study, 3=Asian Study

Size of characters is proportional to sample size.

**5.3.2 Results: ALT vs Histology**

[Individual Level Correlation (method 1)]{.underline}

Tables 5 e and f show the correlation between the change from baseline
in log~10~ ALT with the total change in necro-inflammatory scores from
baseline at one year, for lamivudine and adefovir studies, respectively.
Note that all correlations were adjusted for study and randomized
treatment (\* = significantly different from 0 at level 0.05, \*\* =
significance level at 0.0001).

Overall the correlation between change in ALT and histology was greater
than that observed for HBV DNA and histology.

### Table 5e: Individual Correlation Analyses for Lamivudine Studies

## Change in ALT vs. Change in Knodell Score

+---------------+------+------+------+--------+-----+-------+-------+
| *             |      |      |      |        |     |       |       |
| *Lamivudine** |      |      |      |        |     |       |       |
+---------------+------+------+------+--------+-----+-------+-------+
| ####          | ###  | **L  | *    | **     | *   | *     | **Hom |
| ### **Study** | #### | AM** | *LAM | LAM+** | *IF | *Over | ogene |
|               |  **P |      | 25** |        | N** | all** | ity** |
|               | BO** | **1  |      | *      |     |       |       |
|               |      | 00** |      | *IFN** |     |       |       |
+---------------+------+------+------+--------+-----+-------+-------+
| #### US       | 0.56 | 0.59 |      |        |     | 0.5   | 0.38  |
|               | \*\* | \*\* |      |        |     | 7\*\* |       |
+---------------+------+------+------+--------+-----+-------+-------+
| **IFN         | 0.   | 0.   |      | 0.     |     | 0.3   | 0.001 |
| N             | 31\* | 25\* |      | 74\*\* |     | 9\*\* |       |
| onresponder** |      |      |      |        |     |       |       |
+---------------+------+------+------+--------+-----+-------+-------+
| **Asian**     | 0.   | 0.53 | 0.64 |        |     | 0.5   | 0.21  |
|               | 37\* | \*\* | \*\* |        |     | 4\*\* |       |
+---------------+------+------+------+--------+-----+-------+-------+
| **Act         |      | 0.   |      | 0.26\* | 0   | 0.2   | 0.98  |
| ive-control** |      | 26\* |      |        | .26 | 6\*\* |       |
+---------------+------+------+------+--------+-----+-------+-------+
| **Overall**   | 0.40 | 0.37 | 0.64 | 0.     | 0   | 0.4   | 0.02  |
|               | \*\* | \*\* | \*\* | 50\*\* | .26 | 3\*\* |       |
+---------------+------+------+------+--------+-----+-------+-------+
| **            | 0.54 | 0.55 |      | \<     |     | \<0   | 0.013 |
| Homogeneity** |      |      |      | 0.0001 |     | .0001 |       |
+---------------+------+------+------+--------+-----+-------+-------+

LAM: lamivudine. PBO=Placebo. IFN=interferon

### Table 5f: Individual Correlation Analyses for Adefovir Studies

## Change in ALT vs. Change in Knodell Score

+-----------------+---------+---------+---------+----------+----------+
| #### Adefovir   |         |         |         |          |          |
+-----------------+---------+---------+---------+----------+----------+
| ##              | #       | **      | **      | **O      | **Homog  |
| ##### **Study** | ######  | ADV10** | ADV30** | verall** | eneity** |
|                 | **PBO** |         |         |          |          |
+-----------------+---------+---------+---------+----------+----------+
| **HbeAg+**      | **0.4   | **0.5   | **0.5   | **0.     | **0.30** |
|                 | 7\*\*** | 0\*\*** | 7\*\*** | 52\*\*** |          |
+-----------------+---------+---------+---------+----------+----------+
| **HbeAg-**      | *       | **0     |         | **0.     | **0.59** |
|                 | *0.23** | .32\*** |         | 29\*\*** |          |
+-----------------+---------+---------+---------+----------+----------+
| **Overall**     | **0.4   | **0.4   | **0.5   | **0.     | **0.37** |
|                 | 1\*\*** | 4\*\*** | 7\*\*** | 46\*\*** |          |
+-----------------+---------+---------+---------+----------+----------+
| **Homogeneity** | *       | *       |         | **0.03** | **0.85** |
|                 | *0.12** | *0.12** |         |          |          |
+-----------------+---------+---------+---------+----------+----------+

ADV10 = adefovir 10 mg; ADV30 = ADV 30

Homogeneity: p-value for testing if unit change in log10 ALT has the
same impact on the Knodell score across the row or column.

There is considerable variation in the correlation coefficients across
studies. For adefovir, within study variation between treatment groups
are small. For lamivudine, the within study variation arises from the
larger correlation in the LAM+IFN arm of the IFN-Nonresponders study,
and the smaller correlation in the placebo arm of the Asian study.

[Plot of ALT vs Histology:]{.underline}

Fig. 5d shows the correlation between change in log~10~ ALT and change
in Knodell score at 1 year for all the treatment arms.

**Figure 5d**. **Change from Baseline in ALT (log~10~) vs Change in
Knodell Score at 1 year for lamivudine and adefovir studies.**

![](media/image4.wmf){width="5.999305555555556in"
height="4.429861111111111in"}

L=Lamivudine 100mg, l=lamivudine 25mg, 0=Placebo, M=LAM+IFN, F=IFN
alone, A=adefovir 10 mg, a=adefovir 30 mg.

Size of characters is proportional to sample size.

Note that the responses were separated into several groups according to
treatment. In the lower left corner of Figure 5d the data points are
mostly from lamivudine or adefovir arms, in the upper right corner the
data points are mostly from placebo arms, and in between the data points
are mostly from IFN-containing regimens or placebo arms.

##### Trial Level Correlations: ALT vs Histology

The trial level correlations examine treatment differences in log~10~
ALT change between treatment arms vs. treatment differences in Knodell
score change across studies.

The trial-level correlation shown in Fig. 5e included placebo,
lamivudine and adefovir arms, but excluded IFN-containing arms. Each
study was divided into smaller "substudies" according to region and
race. A scatter plot of the relationship for treatment effects on log10
ALT change vs. biopsy change is given below.

Fig. 5e. Trial Level Correlations for Change in ALT vs. Change in
Histology, for adefovir and lamivudine studies.

![](media/image5.wmf){width="5.995138888888889in"
height="4.610416666666667in"}

1=US Study, 2=IFN-non-responder Study, 3=Asian Study, 4=Active Control
Study, 7=HbeAg+ Study, 8=HbeAg- Study, size of symbol is proportional to
the sample size of each substudy.

From the graph we see there is a trend that the larger the treatment
difference between either lamivudine or adefovir arm compared to the
placebo arm, the larger the treatment effects on Knodell score change.
However, there is also considerable noise in this prediction. In fact,
the estimated R^2^ value is 17% (95% C.I. 0% to 40%), indicating a
limited predictive value of treatment effect on log~10~ ALT change.

Note in the graph above there is one sub-study in the US study at the
lower left corner, that deviates significantly from other points.
Removing this sub-study decreased the trial level association
considerably, R^2^= 4%.

When restricted to adefovir alone, trial level R^2^ =25% (95% C.I., 0%
to 61%). When restricted to lamivudine vs. placebo comparisons the R^2^=
17% (95% C.I. 0% to 50%) when the influential point at the lower left
corner is not removed, or 4% (95% CI 0% to 18%) when the influential
point is removed.

##### **5.3.3 Proportion of Treatment Effect Explained (method 4)**

The approaches discussed in the sections above, based on individual and
trial level-correlations, attempt to address the surrogacy issue
directly with empirical evidence. Using these methods, the underlying
association of the potential surrogate endpoint with the biopsy (i.e.,
HBV DNA or ALT with histology) is potentially affected by the following
factors:

-   Sampling variation and reading error for biopsy will weaken both the
    individual and trial-level correlation. If biopsy assessment has
    considerable variation, this will reduce the strength of the
    correlation.

-   Variation in trial results is desirable. Two studies with different
    effect sizes will be more useful than two studies with similar
    results.

```{=html}
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```
-   The correlations may be influenced by how the sub-studies are
    constructed. There may be many plausible ways of forming sub-studies
    for meta-analysis, different constructions could yield somewhat
    different results.

Another concept for validation is the proportion of "treatment effect
explained" by a surrogate endpoint (PTE). In this case PTE modeling
attempts to determine how much of the overall effect on histologic
outcome is mediated through HBV DNA or ALT. Measurement errors in biopsy
and surrogate endpoints affect the estimation of PTE less than that of
the methods described previously. However, its use has been widely
debated. The results on the proportion of treatment effect (histologic
outcome) explained are summarized below in Tables 5g and 5h for year 1
log~10~ HBV DNA and change in log~10~ ALT, respectively. More detailed
results will be presented in the meeting.

##### **Table 5g: PTE by HBV DNA as measured using Year 1 log~10~ HBV DNA**

+------------+--------------+-----------------+--------+--------------+
| **Study    | **Study**    | ### Treatments  | *      | **95% CI**   |
| Drug**     |              |                 | *PTE** |              |
+------------+--------------+-----------------+--------+--------------+
| **         | HBeAg+       | ADV10 vs PLA    | 65%    | 41%, 104%    |
| Adefovir** |              |                 |        |              |
|            | \(437\)      |                 |        |              |
+------------+--------------+-----------------+--------+--------------+
|            |              | ADV30 vs PLA    | 78%    | 49%, 110%    |
+------------+--------------+-----------------+--------+--------------+
|            | HBeAg-       | ADV10 vs PLA    | 15%    | -8%, 39%     |
|            |              |                 |        |              |
|            | \(438\)      |                 |        |              |
+------------+--------------+-----------------+--------+--------------+
|            |              |                 |        |              |
+------------+--------------+-----------------+--------+--------------+
| **La       | US Study     | LAM100 vs PLA   | 33%    | 10%, 87%     |
| mivudine** |              |                 |        |              |
+------------+--------------+-----------------+--------+--------------+
|            | IFN-Non-resp | LAM100 vs PLA   | 37%    | 22%, 63%     |
+------------+--------------+-----------------+--------+--------------+
|            |              | LAM+IFN vs PLA  | 23%    | -241%, 312%  |
+------------+--------------+-----------------+--------+--------------+
|            | Asian        | LAM100 vs PLA   | 40%    | 6%, 79%      |
+------------+--------------+-----------------+--------+--------------+
|            |              | LAM25 vs PLA    | 48%    | 18%, 104%    |
+------------+--------------+-----------------+--------+--------------+
|            | Ac           | LAM100 vs IFN   | 75%    | -525%, 950%  |
|            | tive-Control |                 |        |              |
+------------+--------------+-----------------+--------+--------------+
|            |              | LAM+IFN vs IFN  | 19%    | -205%, 276%  |
+------------+--------------+-----------------+--------+--------------+

##### 

##### **Table 5h:** **PTE by ALT as measured using change in log~10~ALT at I year**

+------------+---------------+----------------+--------+--------------+
| **Study    | **Study**     | ### Treatments | *      | **95% CI**   |
| Drug**     |               |                | *PTE** |              |
+------------+---------------+----------------+--------+--------------+
| **         | ADV HbeAg+    | ADV10 vs PLA   | 46%    | 31%, 68%     |
| Adefovir** |               |                |        |              |
+------------+---------------+----------------+--------+--------------+
|            |               | ADV30 vs PLA   | 40%    | 28%, 55%     |
+------------+---------------+----------------+--------+--------------+
|            | ADV HbeAg-    | ADV10 vs PLA   | 17%    | 7%, 31%      |
+------------+---------------+----------------+--------+--------------+
|            |               |                |        |              |
+------------+---------------+----------------+--------+--------------+
| **La       | US Study      | LAM100 vs PLA  | 65%    | 30%, 129%    |
| mivudine** |               |                |        |              |
+------------+---------------+----------------+--------+--------------+
|            | IFN-Non-resp  | LAM100 vs PLA  | 27%    | 13%, 47%     |
+------------+---------------+----------------+--------+--------------+
|            |               | LAM+IFN vs PLA | -24%   | -469%, 466%  |
+------------+---------------+----------------+--------+--------------+
|            | Asian         | LAM100 vs PLA  | 42%    | 21%, 72%     |
+------------+---------------+----------------+--------+--------------+
|            |               | LAM25 vs PLA   | 49%    | 26%, 91%     |
+------------+---------------+----------------+--------+--------------+
|            | A             | LAM100 vs IFN  | 63%    | -352%, 479%  |
|            | ctive-Control |                |        |              |
+------------+---------------+----------------+--------+--------------+
|            |               | LAM+IFN vs IFN | -37%   | -344%, 321%  |
+------------+---------------+----------------+--------+--------------+

**6.0 Conclusions**

Given recent advances in the treatment of CHB and the increased interest
in drug development for the treatment of CHB, this is an opportune time
to discuss clinical trial design issues facing future drug development
in this field. We have provided you with a list of what we believe are
the most crucial issues in the design of phase 3 studies evaluating
drugs to treat CHB. We have also presented advantages and disadvantages
of some of the options one might consider when selecting controls, study
designs, endpoints, and patient populations.

As stated previously, choice of endpoint may be one of the most pressing
issues facing current drug development. Presently, the recommended
primary endpoint for registrational studies is changes in histologic
scores. The Division utilized clinical trial data sets to explore
associations between treatment effects on other less invasive
measurements (HBV DNA, ALT) and histologic outcome. Associations between
HBV DNA and histologic outcome were weak on the individual level;
associations were better for ALT and histology but still modest.
However, the weakness of the associations may have been a result of a
large degree of variability in histologic measurements. Analyses
exploring the proportion of treatment effect explained by the surrogate
showed that some associations between HBV DNA or ALT and histologic
outcome were fairly strong, specifically for adefovir study 437 in
HBeAg-positive patients. The correlations were weaker for adefovir study
438. Similar analyses using lamivudine studies were generally supportive
of a correlation and were consistent with the adefovir studies; however,
lamivudine studies containing interferon treatment arms were not
supportive of a positive correlation between HBV or ALT and histologic
outcome.

We realize that there is a large amount of information to consider, but
hope that this document and the attached references will help the
committee to have a productive discussion on August 7th. We look forward
to your feedback.

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### Attachment A: Discussion Points/Questions for Antiviral Advisory Committee

# Patient Populations

1.  Please identify patient populations that are appropriate targets for
    treatment studies (consider attributes such as stage of disease,
    viral genotype, co-morbidities, lamivudine resistance,
    IFN-experience, pediatrics, HBeAg-/HBV DNA+)? Please include
    demographics in your discussion, i.e. race and ethnicity.

2\. Which of the aforementioned patient subgroups is essential in a
marketing application? In particular, comment on race and ethnicity,
disease stage and comorbidities.

**[Control Arms]{.underline}**

3a. Discuss the role of the following controls in the compensated liver
disease group:

-   Placebo controls/delay of initiation of treatment; and of what
    duration?

-   Lamivudine (or other antiviral drug) monotherapy

-   Interferon

3b. Please also discuss controls for patients with decompensated liver
disease or who have failed previous regimens

**[Study Endpoints and Timing of Evaluations]{.underline}**

4.  Considering the patient populations identified in question #1, the
    information presented today, and the necessity that endpoints for
    registration be clinically meaningful, please answer the following:

-   Which endpoint (or combination of endpoints) should be the primary
    in clinical trials? Please discuss histologic, serologic,
    biochemical, and virologic endpoints.

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-   When should the assessment of the primary endpoint be made?

-   List the most appropriate secondary endpoints and rank them in order
    of importance.

5.  For histologic endpoints, what is the preferred method of histologic
    scoring? What degree of change in histologic score is clinically
    meaningful?

6.  For virologic endpoints, which assay is best suited for clinical
    trials? What is the appropriate cutoff point for HBV DNA (eg.
    \<10^5^, \<10^4^, etc)? Should viral genotyping be done and why?

7.  For patients with decompensated liver disease, please discuss the
    feasibility/validity of the following alternative endpoints:

-   mortality

-   change in Child- Pugh-Turcotte score (or its components)

-   transplant/no transplant

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```
-   occurrence of liver disease associated illness (variceal bleed, SBP,
    etc)

**[Long Term Follow-Up]{.underline}**

8\. Beyond the assessment of the primary endpoint for registration, what
is the appropriate duration of studies for treatment of CHB infection,
and what kind of information should be gathered?

### Attachment B: Bibliography

1.  Lok AS, McMahon BJ. Chronic Hepatitis B, AASLD Practice Guidelines.
    Hepatology 2001; 34:1225-41.

2.  Lok AS, Heathcote J, Hoofnagle JH. Management of Hepatitis B:
    2000-Summary of a Workshop. Gastroenterology 2001; 120: 1828-1853.

3.  Rizetto M. Efficacy of lamivudine in HBeAg-negative chronic
    hepatitis B. J Med Vir 2002; 66:435-451.

4.  Knodell RG, Ishak KG, Black WC, et al. Formulation and Application
    of a Numerical Scoring System for Assessing Hisotologic Activity in
    Asymptomatic Chronic Active Hepatitis. Hepatology 1981; 5: 431-435.

5.  Dienstag JL, Schiff ER, Wright TL et al. Lamivudine as initial
    treatment for chronic hepatitis B in the United States. NEJM 1999;
    341:1256-1263.

6.  Lau DT, Everhart J, Kleiner DE, et al. Long-term follow-up of
    patients with chronic hepatitis B treated with interferon alfa.
    Gastroenterology 1997; 113; 1660-1667.

7.  Gauthier J, Bourne EJ, Lutz MW et al. Quantitation of Hepatitis B
    viremia and emergence of YMDD variants in patients with chronic
    hepatitis B treated with lamivudine. J Infect Dis 1999;
    180:1757-1762.

8.  Yao FY, Bass NM. Lamivudine treatment in patients with severely
    decompensated cirrhosis due to replicating hepatitis B infection. J
    Hepatol 2000; 33:301-307.

9.  Kapoor D, Guptan RC, Wakil AM. Beneficial effects of lamivudine
    inhepatitis B virus-related decompensated cirrhosis. J Hepatol 2000;
    33: 308-312.

10. Jonas MM, Kelley DA, Mizerski J et al. Clinical trial of lamivudine
    in children with chronic hepatitis B. NEJM 2002; 346: 1706-1710.

11. Zavaglia C, Mondazzi L, Maggi G et al. Are alanine aminotransferase,
    hepatitis B virus DNA or IgM antibody to hepatitis B core antigen
    serum levels predictors of histological grading in chronic
    hepatitis B. Liver 1997; 17: 83-87.

12. Pawlotsky JM, Bastie A, Hezode C et al. Routine detection and
    quantification of hepatitis B virus DNA in clinical laboratories:
    performance of three commercial assays. J Virol Meth 2000; 85:11-21.

### Attachment C: Child-Pugh Score

### Scoring System

1.  Total Serum Bilirubin

    1.  Bilirubin \<2 mg/dl: 1 point

    2.  Bilirubin 2-3 mg/dl: 2 points

    3.  Bilirubin \>3 mg/dl: 3 points

2.  Serum Albumin

    1.  Albumin \>3.5 g/dl: 1 point

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    ```
    1.  Albumin 2.8 to 3.5 g/dl: 2 point

    2.  Albumin \<2.8 g/dl: 3 point

3.  INR

    1.  INR \<1.70: 1 point

    2.  INR 1.71 to 2.20: 2 point

    3.  INR \>2.20: 3 point

4.  Ascites

    1.  No ascites: 1 point

    2.  Ascites controlled medically: 2 point

    3.  Ascites poorly controlled: 3 point

5.  Encephalopathy

    1.  No Encephalopathy: 1 point

    ```{=html}
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    ```
    1.  Encephalopathy controlled medically: 2 point

    2.  Encephalopathy poorly controlled: 3 point

**Classification/Interpretation**

Child Class A: 5 to 6 points

## Child Class B: 7 to 9 points 

## Child Class C: 10 to 15 points