101 But most cold-pack cheeses won’t support

101
contamination.
2
the growth of Listeria to high levels.
3
there may have been recalls of those products, it really
4
speaks to whether, indeed, those products represent a
5
present, imminent danger to public health.
And even though
so, I think it is very critical that we have
6
7
some kind of measure on whether these products can
8
support growth.
9
I think there are industry folks that can help out in
10
And I think Bruce’s point is well-taken.
that assessment.
And Bob 1Buchanan talked about the role of
11
-
But most cold-pack cheeses won’t support
1
And there’s
12
challenge studies, inoculated pack studies.
13
plenty of those as well that can be factored in on that
14
particular point.
So, to me, it goes just beyond probability of
15
16
contamination, you know, whether it’s contaminated there
17
or not.
18
of consumption, I think.
19
to model.
20
But it’s also level of contamination at the time
I know that’s a difficult thing
The other thing, the other piece I guess I
I know the UK
21
would ask about is the quantitative data.
22
data that Dr. Hitchins presented had as a upper limit
23
greater than a thousand per gram, I believe.
24
the scientific nature of the risk assessment that we’re
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And given
102
n
1
trying to do, given the work at the University of Georgia
2
and the Emory Primate Center on the L.M. Monkey Study, as
3
I call it, trying to get at infective dose, my question
4
is that we try and measure up the levels of Listeria in
5
these products that we’re consuming versus anything that
6
would come out at infective dose study, is greater than a
7
thousand per gram or a thousand per gram sufficient
8
enough?
9
quantitating
10
Or should we be trying to go higher in terms of
levels?
And then, I guess my other question is the
11
issue of, really, how do we harmonize ready-to-eat
12
definitions of ready-to-eat foods in this whole process
13
versus, say, frozen foods, for example?
14
factor that in as well?
15
16
17
And how do we
Thank you.
MR. MORRIS POTTER:
comments from -- Okay.
foods,
Thanks, Paul.
Other
Tony?
DR. TONY HITCHINS:
Tony Hitchins, FDA.
Just a
There are data in the
18
comment on Paul’s comments.
19
collection already that have, you know, numbers greater
20
than a thousand per gram.
21
particular study or that piece of that study, it wasn’t
22
apparent; it wasn’t done.
23
24
It’s just that in that
MR. MORRIS POTTER:
You got a little far from
the mike there, Tony.
.-.,
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1
c
w
w
<
DR. TONY HITCHINS:
Sorry.
There is data in
2
the data base, at least from some other studies, that
3
gives numbers for rare cases where the counts are greater
4
than a thousand per gram.
5
but some do.
And not all studies have that,
Yeah.
6
MR. MORRIS POTTER:
Wally?
7
MR. WALLY SCHLECH:
Wally Schlech again.
I
8
just wanted to comment about the quantitation.
I think
9
that you also, particularly if you’re looking at levels
There
10
of quantitation, need to look again at the host.
11
is clear data in the Boston outbreak in the late 70’s
12
that antacids were a risk factor.
13
say, allow ten to the two Listeria per gram to get out
14
into the market.
15
protect one of these immunocompromised individuals.
16
if you look at all the Pepcid AC ads on TV, it seems like
17
the entire American population is swallowing them.
18
maybe that would argue against -- and presumably the
19
monkey studies might give some additional information.
20
But we certainly have studies in a gastric model in rats
21
that is a real phenomenon.
22
So, you may decide to,
But that may not be sufficient to
MR. MORRIS POTTER:
Thanks, Wally.
And
Then
The BRFSS
1
23
surveys have looked at antacid and H2 blocker
24
consumption, at least in some of them, so there are some
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1
data there.
But that may be a bit difficult to model.
MS. CARY FRYE:
2
Cary Frye, International Dairy
Also , the National Cheese Institute.
3
Foods Association.
4
And we really appreciate the comments here today, and
5
we’re very supportive of the risk assessment.
6
speak to Mary Bender about some of the data she presented
7
with the food consumption, specifically in the cheese
8
category.
9
pasteurization
10
I did
And the slide that you showed about mandatory
of 33 percent is certainly accurate.
I
don’t disagree with that.
However, I think commercial practices of cheese
11
12
manufacturing,
specifically cheese manufacturing
that
13
could have a higher probability of contamination,
14
showing that pasteurized milk is used.
15
commercially, Mexican-style cheese by one of our members,
16
all of their milk is pasteurized.
17
could be a data gap here that might need additional
18
information that we could assist with, rather than just
19
looking at the regulations, but maybe providing actual
20
practices for cheese manufacture.
21
and we hope that we can provide that because many soft
22
cheeses are made with pasteurized milk for that very
23
reason.
are
I know
SO, it appears there
o
cl
c’
L
z
u
w
L
<
II
24
So, I realize that,
Secondly, I had a question related to the risk
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.-—..
If YOU
1
assessment similar to this same line of thinking.
2
look at the literature, you’re looking at it worldwide,
3
cheeses that may show levels of Listeria that were made
4
from raw milk because there’s different regulations
5
different countries.
6
in the risk assessment?
7
the different practices of how cheeses are produced?
8
Because it’s my understanding the risk assessment will be
9
looking at the risk of the U.S. population.
in
And how will you account for that
Will there be any accounting for
Will you
10
look at the imported cheeses such as the data we have at
11
NCI and weight that, or will you look at all cheeses?
12
Thank you.
DR. MARY BENDER:
13
Mary Bender, FDA.
There’s
14
somebody back there right now who’s trying to get data,
15
as you’re discussing.
16
FDA does collect some data on imports.
17
really excited that they have a data base going, but
18
they’ve warned us not to take everything as is because
19
this is a developing data base.
20
look at some of the imports of the lots of cheeses.
21
a certain proportion that’s been tested or held back for
22
Listeria, and then some where there have been positive
23
results.
24
all together to come out with something that makes sense
Our Regulatory Affairs Office at
And they’re
But we have been able to
And
But it’s been a challenge to try to put this
n
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There was one slide that I had that --
1
and is accurate.
2
we do want to look at this further to try to figure out.
3
And I really do appreciate any help.
Now, Cary and two others did come to me at the
4
5
break and said that there really has not been an outbreak
6
related to ice cream.
7
there was an epidemiological link -- I don’t know -- it
8
was from a CDC article.
9
This is something I’ve read.
10
input.
And I looked back at my file, and
And you all are the experts.
So, I really appreciate the
Thanks.
11
MR. MORRIS POTTER:
12
MR. LARRY BORCHERT:
Other comments?
Yes.
Larry Borchert with the
My comments also deal with data
13
American Meat Institute.
14
acquisition and consideration.
15
following up on points that have already been made.
16
1’11 use that as an example.
17
is not a hot dog as a cheese is.
18
international data, for example, the hot dogs that are
19
made in Germany, for example, have probably twice the
20
brine concentration, traces of salt and water
21
concentration, that they do in this country.
22
warrants us to be very careful of the use of
23
international data.
24
And it really is
And
A hot dog is not a hot dog
If we are considering
So, it
Likewise, acquisition of data, I think we do
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.-.
For example, two
1
need to be cognizant of sales data.
2
major companies in the United States produce 40 percent
3
of the hot dogs in the United States.
4
broad-based consumption data might distort the overall
5
picture, particularly if one or both of these companies
6
are using some intervention technique that might decrease
7
the prevalence of Listeria in their products.
so, I think the point I’m trying to make is
8
9
So, looking at
that we must be very, very careful in acquiring the data
10
and using the data that we are applying that to the
11
specific products that we’re talking about, not just a
12
generic family of those particular products.
MR. MORRIS POTTER:
13
Thanks, Larry.
Thank you.
Other
Seeing none, the schedule calls for us to be
14
comments?
15
back in session at 1:00.
16
schedule, I hope folks will be prompt.
17
again at 1:00.
Since we’re a little ahead of
We will start
Be here.
o
0
c1
L
18
(Whereupon, a lunch recess was had in
19
this matter.)
>
=5
MR. MICHAEL JAHNCKE:
20
Welcome back, everybody.
21
I hope everyone had a nice lunch.
22
started.
23
three more, with the summary.
24
slide.
We’re going to get
We have two more presentations this afternoon-I/m just waiting for a
Here we go.
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As I mentioned, we’re going to have two more
1
Then Dr. Whiting later will do a summary
2
presentations.
3
of what has been presented to this day.
4
session of Hazard Assessment.
5
will be Dr. Pat McCarthy looking at some epidemiologic
6
records.
7
Raybourne on dose-response experimentation.
10
11
12
13
And the two presenters
And the second speaker will be Dr. Richard
Let me introduce our first speaker, Dr. Pat
8
9
We’re in the
McCarthy.
And he will be speaking on epidemiology
of
Listeria monocytogenes outbreaks.
DR. PATRICK McCARTHY:
Good afternoon.
I’m
going to talk about the epidemiology of Listeriosis.
Next slide, please.
Listeria was first
And a few years later, the organism
14
described in 1926.
15
was recognized as a human pathogen.
16
Listeria, Listeriosis could be transmitted to humans in
17
food dates back to the 1930’s.
18
1980’s that evidence was obtained that Listeriosis
19
foodborne disease.
20
The suggestion that
But it was not until the
is a
Since the 1980’s, foodborne outbreaks in
21
sporadic cases have been reported in many countries
22
throughout the world.
23
and Territorial Epidemiologists recommended that
24
Listeriosis be a reportable disease.
And in 1986, the Council of State
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Next slide.
1
Listeria is the name of a group of
Listeriosis is the name of
2
disorders caused by Listeria.
3
a group of disorders caused by the organism, Listeria
4
monocytogenes.
5
Listeria is isolated from blood cultures, spinal fluid or
6
an otherwise normally-sterile site like a placenta or a
7
fetus.
Cases of Listeriosis are usually divided into
8
9
Listeriosis is clinically defined when
perinatal and nonperinatal groups.
The perinatal group
10
includes pregnant women and their fetus or newborn.
11
Women may get Listeriosis at any time during pregnancy,
12
but most cases are reported in the third trimester.
Often, pregnant women will present with an
13
14
influenza-like illness which includes fever, chills and
15
headache.
16
thirds of women with pregnancy-associated
17
About three to seven days after the onset of prodromal
18
symptoms, women will abort the fetus or will have
19
premature labor.
20
This prodromal illness occurs in about twoListeriosis.
In the first trimester, Listeriosis results in
In later stages of pregnancy, the
21
spontaneous abortions.
22
result can be a stillbirth or a critically-ill newborn.
23
Sepsis occurs in about 30 percent of pregnant women with
24
Listeriosis, and there are a few reports of meningitis
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in
110
pregnant women.
2
stillbirth.
3
meningitis or can die.
4
And the newborn can present with sepsis,
The nonperinatal group includes all nonNonperinatal
5
pregnant persons over the age of 28 days.
6
cases primarily include persons that are taking
7
immunosuppressive medications, persons with chronic
8
debilitating diseases like cancer, diabetes or
9
alcoholism, and persons over the age of 60.
Healthy
10
children and adults have a relatively low risk of
11
infection from Listeria.
12
When infection does occur in children and
13
adults, Listeriosis is usually superimposed upon some
14
other illness.
15
meningitis or sepsis.
16
o
v
The fetus can suffer abortion,
1
Nonperinatal cases often present with
In the next few minutes, 1’11 discuss the early
17
foodborne outbreaks and surveillance for Listeriosis;
18
1/11 provide some examples of recent outbreaks and
19
sporadic reports.
and
4
20
5
m
<
.
Listeriosis is known to cause severe illness,
21
but there have been events in which the majority of cases
22
developed mild symptoms.
23
where mild symptoms were primarily reported.
24
1’11 identify a few events
I have a slide on the incubation period for
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1
Listeriosis and another slide on fecal carriage studies.
2
I’ll show you the incident trend for Listeriosis
3
United States between 1989 and 1993.
4
recent data from FoodNet, the ongoing active surveillance
5
program for foodborne diseases.
6
Next slide.
cc
w
m
<
.
And I have some
The earliest evidence that
7
Listeriosis is a foodborne illness was obtained from
8
outbreaks that occurred in Nova Scotia, Massachusetts,
9
Los Angeles, and Switzerland between 1981 and 1987.
10
Other outbreaks occurred before 1981, but the vehicle of
11
infection was not identified.
12
80’s lasted for several months each but involved
13
relatively few cases.
14
several deaths associated with these outbreaks.
Next slide.
15
o
v
in the
These outbreaks during the
On the other hand, there were
Both nonperinatal and perinatal
The age range
16
cases were identified in each outbreak.
17
for the nonperinatal cases was between age 21 and 100.
18
The median age in the nonperinatal cases was about 60
19
years.
20
nonperinatal cases were taking immunosuppressive
21
medications, had a debilitating disease or were over age
22
60.
23
24
In these outbreaks, the majority of the
About one-third of the nonperinatal cases died.
In the perinatal group, the mother and fetus or
newborn was considered as a single case.
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The fatality
112
1
rate in the perinatal group was about one-third.
Matched case-control studies implicated a
2
In Nova Scotia,
3
particular food in each outbreak.
4
coleslaw was implicated.
5
implicated in the other outbreaks.
6
implicated the food were all significant at the 0.05
7
level or below the 0.05 level.
8
was isolated from cases in each of the outbreaks and from
9
the implicated food in all outbreaks except from
10
And dairy products were
The odds ratios that
Listeria monocytogenes
4b
Massachusetts.
The incident rates that I show here are for the
11
in which the outbreaks occurred.
I don’t
12
populations
13
have the background incident rates for all these
14
outbreaks.
15
outbreak, the background rate was approximately
16
hundred thousand cases.
17
incident rate was about 5 cases per 100,000.
18
incident rates make the outbreaks very difficult to
19
detect.
20
the cases occurred in a single hospital or were reported
21
to a single laboratory.
22
hospital infectious control nurse noticed the increase in
23
cases; and her observation led to the investigation which
24
implicated the Mexican-style cheese.
But in Switzerland in the years preceding the
.5 per
At the end of the outbreak, the
Low-
These outbreaks were only detected because all
For example, in Los Angeles, a
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The likely source of Listeria in the Nova
1
2
Scotia outbreak was the raw manure used to fertilize the
3
cabbage which was made into coleslaw.
4
all these outbreaks suggest that Listeriosis was linked
5
to the farm or to food production facilities.
These early outbreaks showed that Listeriosis,
6
7
the foodborne Listeriosis can cause abortion, stillbirth,
8
sepsis, meningitis and death.
9
investigations showed that significantly more cases than
Matched case-control
The L. monocytogenes
10
controls ate the implicated food.
11
4b was identified in most of the infections occurring
12
during the epidemic period.
13
Listeria monocytogenes was isolated from opened and
14
unopened samples of food implicated in 3 of the 4
15
outbreaks.
16
o
v
The sources for
And the epidemic strain of
Following the Los Angeles outbreak in 1985, CDC
I show here data from two
17
started Listeria surveillance.
18
surveillance populations, but there were other reports in
19
the literature of surveillance that took place between
20
1985 and 1993.
21
surveillance.
22
surveillance, there was 19 million people.
23
surveillance periods included people from Oklahoma,
24
Tennessee and Los Angeles County.
There were 34 million people in the 1986
And between 1989 and 1993, in that
Both
The 1986 surveillance
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1
population was larger because health departments
2
Missouri, New Jersey and Washington were included.
3
Before the surveillance was started, hospitals,
4
laboratories and physicians in the surveillance area were
5
contacted and asked to report cases of Listeriosis.
6
the end of the surveillance period, facilities that
7
reported cases were audited to determine the sensitivity
8
of the surveillance.
9
surveillance was 93 percent, and case ascertainment
10
At
The case ascertainment for the 1986
in
1993 was shown to be 97 percent.
246 cases were reported in 1986.
11
o
in
And between
Now, I’m
12
1989 and 1993, about 400 cases were reported.
13
going to show additional data from the 1986 surveillance.
14
And in a few minutes, I’m going to show the incident
15
trend that was developed for Listeriosis between 1989 and
16
1993.
17
Overall, in 1986 there were .7 culture positive
0
The rate
18
cases of Listeriosis per 100,000 population.
19
was slightly less in the nonperinatal group but was much
20
higher, 7.8, in the perinatal group.
21
If Los Angeles County was included, the cases
But Los Angeles
22
per 100,000 would be approximately 24.
23
County experienced an outbreak during 1985, and this
24
heightened awareness could have been the reason for the
AIM REPORTING SERVICE
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1
increase in cases.
2
reporting to you.
Listeria monocytogenes has 13 serobars.
3
serotypes accounted for approximately 96 percent of the
5
cases.
6
percent; and 4b accounted for 33 percent of the isolates
7
during the 1986 surveillance.
8
data, it was projected that about 1700 cases and 450
9
deaths due to Listeriosis occurred in the United States
CL
<
CL
l/2a accounted for 30 percent; l/2b for 33
Based on surveillance
in 1986.
Next slide.
11
u
w
But 3
4
10
o
v
so, I have excluded it in what I’m
Listeria monocytogenes
can cause
12
illness if it penetrates the lining of the GI tract.
13
Once the organism penetrates the tissue, it can protect
14
itself from phagocytosis, grow and then migrate
15
throughout the host.
16
thought to depend upon the number of organisms consumed,
17
host susceptibility and virulence of the organism.
18
In the 1986 surveillance, there were 179
The chance of tissue invasion is
There was a 2-month-old and a 3-
19
nonperinatal cases.
20
year-old, but the other 177 cases were all age 16 or
21
over.
22
percent of the cases had sepsis; 19 had sepsis and
23
meningitis; and 12 percent had meningitis only.
24
percent of the cases had a focal infection caused by
56 percent of the cases occurred in males; 66
.-.
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About 3
116
The incidence of Listeriosis increased with
1
Listeria.
2
age.
3
percent of the cases were over age 70.
4
fatalities also increased with age.
5
35 percent fatality rate.
6
fatality rate was 41 percent.
84 percent of the cases were over age 50, and 40
In adults,
Overall, there was a
In cases over age 60, the
There were 67 affected pregnancies.
7
80 percent
8
of the pregnancies resulted in live birth, and one of the
9
neonates died.
Of the live births, 75 percent were
10
culture positive, so transmission of Listeria to the
11
fetus does not always occur.
12
positive babies had an early onset Listeriosis.
80 percent of the culture
Early onset is defined as a case of Listeriosis
13
14
in a neonate between birth and seven days of age.
15
onset is often characterized by a premature birth,
16
respiratory distress and circulatory failure.
17
80 percent of the early onset neonates had sepsis, and 20
18
percent had meningitis.
Early
In 1986,
20 percent of the culture positive babies had
19
Late onset is defined as
20
late onset Listeriosis.
21
Listeriosis in a neonate between 8 days and 28 days of
22
life.
23
at fullterm.
24
babies.
Usually late onset neonates are born healthy and
Meningitis is more common in the late onset
The mothers of late onset babies usually had an
~-.
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Listeria
1
unaffected pregnancy and no prodromal illness.
2
is rarely isolated from the mother, and the source of
3
Listeriosis is often not identified in late onset cases.
4
Data was available for 31 maternal cases in the
58 percent of the mothers experienced
5
1986 surveillance.
6
premature labor or premature membrane rupture; 32 percent
7
of the mothers had sepsis or fever; and 10 percent
8
aborted their fetus.
9
deaths reported in the maternal cases.
Listeriosis
10
rarely life-threatening to the mother.
Other studies in
11
the literature suggest that Listeria does not cause
12
repeated abortions in the same women.
13
Next slide.
There was no meningitis and no
is
This slide shows a few examples of
14
outbreaks and sporadic reports of Listeriosis that have
15
occurred since 1988.
16
several countries, and a variety of foods have been
17
implicated as the vehicle of infection, including turkey
18
franks, cheese, mushrooms, pate, fish and hot dogs.
19
Listeriosis has been reported in
This slide shows some of the milder symptoms
It’s
20
that have been associated with Listeria infection.
21
been estimated that 33 percent of all cases give mild
22
symptoms and that most cases occur sporadically.
23
symptoms include chills, diarrhea, nausea, vomiting,
24
fatigue, abdominal cramps.
Mild
Reports of mild symptoms
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1
suggest the possibility that many illnesses caused by
2
Listeria may go unreported.
This slide shows events where most of the cases
3
4
reported mild symptoms -- not all the cases, but most of
5
the cases.
6
infection have been reported in several countries, and a
7
variety of foods have been implicated as the vehicle of
8
infection.
Again, mild symptoms associated with Listeria
I’d just like to speak a little bit about the
9
These cases involved babies at a
10
cases in Denmark.
11
daycare center.
12
and was hospitalized.
13
diarrhea.
14
child was treated for his symptoms and released after two
15
days in good clinical condition.
16
cultures grew Listeria monocytogenes.
17
readmitted but no longer had symptoms.
18
that attended the same daycare were also admitted to the
19
hospital, released in good condition and then readmitted
20
when the blood culture came back positive.
21
second admission, blood cultures from all three babies
22
were negative, but stool cultures grew Listeria
23
monocytogenes
4b.
24
established.
But this example shows that mild symptoms
There was a 2-year-old that got fever
After the fever subsided, he got
Blood and stool cultures were obtained.
The
After discharge, blood
The baby was
Two other babies
After the
The source of the outbreak was not
.-.
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1
can occur even if a blood culture is positive.
The peer reviewed literature shows that the
2
3
incubation period associated with Listeria infection can
4
range from less than 24 hours to approximately
5
Incubation associated with severe illness, like sepsis
6
and meningitis, can range between several days to a few
7
months.
8
gastrointestinal
9
and a few days.
10
3 months.
The incubation period associated with
symptoms can range between several hours
The large bowel is the principal reservoir for
Several studies have looked at fecal
11
Listeria in humans.
12
carriage to gain insight into how the disease is
13
transmitted, especially in sporadic cases.
14
two examples of fecal carriage studies.
15
I show here
In Germany, less than 1 percent of persons with
16
diarrhea and healthy food workers were fecal carriers.
17
In Scotland, approximately 2 percent of pregnant women
18
and 3 percent of nonpregnant women were fecal carriers.
19
In the literature, estimates of fecal carriage ranges
20
between less than 1 percent to 21 percent.
21
It’s not known how fecal carriage relates to
22
the length of incubation or to the occurrence of
23
Listeriosis, although it’s been suggested that in fecal
24
carriers, stress can undermine resistance; and then
--—.
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1
carriers can get the disease.
This is the Listeriosis incident trend from the
2
The bar chart shows cases per
3
1989 to 1993 surveillance.
4
million on the y-axis and year on the x-axis.
5
1990, as more information became available, the
6
regulatory agencies and private industry developed plans
7
to reduce the incidence of Listeriosis.
Industry initiated HACCP programs and increased
8
9
About
sanitation to eliminate contamination.
The regulatory
10
agencies expanded programs to remove contaminated
11
before retail sale.
12
campaign that focused on food safety.
foods
There was also a consumer education
Shortly after these efforts were initiated,
13
14
Listeriosis declined from about 7.9 cases per million in
15
1989 to about 4.4 cases per million in 1993.
16
occurred in diverse geographic areas of the United
17
States.
18
declined in the United Kingdom after the government
19
issued a health warning.
And also, about the same time, Listeriosis
This data is from FoodNet.
20
The decline
FoodNet is an
The purpose of FoodNet is
21
active surveillance program.
22
to determine the frequency and severity of foodborne
23
illness.
24
FoodNet personnel contact each clinical laboratory in
To identify all cases of confirmed disease,
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1
each surveillance area in each catchment area, either
2
weekly or monthly.
This slide shows Listeriosis compared to other
3
There were
4
pathogens that are tracked by FoodNet.
5
approximately
6
Data for 1996 and 1997 also showed that there was
7
approximately
8
years.
.5 cases per 100,000 population
.5 cases per 100,000 population
in 1998.
in those
This chart shows FoodNet data from 1997.
9
The
10
y-axis shows cases per 100,000, and the x-axis shows ages
11
in years.
12
occur in the very young and in the very old.
13
same data was broken down by sex, the ratio of males to
14
females was approximately equal.
15
the same picture that you would see from the 1986
16
surveillance.
17
From this graph, you can see that most cases
When this
This is approximately
A seasonal trend of Listeriosis has been
This slide
18
referred to in literature for many years.
19
shows combined FoodNet data from 1986 and 1997.
20
axis shows cases per month per million population.
21
the x-axis shows month of the year.
22
increase in cases between late spring to autumn, but the
23
reason for this apparent increase is not known.
24
The yAnd
There’s an apparent
This graphic shows some of the pathogens that
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On the x-
1
are being tracked by FoodNet on the y-axis.
2
axis, it shows the percent of isolates from hospitalized
3
individuals.
4
rate in 1998.
5
Salmonella and Shigella, which occurred more often,
6
Listeria put more people into the hospital on a percent
7
basis.
8
Listeria had the highest hospitalization
Listeriosis also had the highest
9
hospitalization
10
in 1997, 1998.
11
Compared with other pathogens like
rate and the highest case fatality rate
In conclusion, I found by reviewing the
12
literature that Listeriosis is a deadly foodborne illness
13
that can be transmitted in many foods, but it is not
14
product specific.
15
the highest hospitalization rate and the highest case
16
fatality rate.
17
in the future due to our aging population and to the use
18
of immunosuppressive medications in surgery and due to
19
the AIDS epidemic.
20
of Listeriosis in the future.
21
presentation.
22
23
24
Of the FoodNet pathogens, Listeria has
Listeriosis cases could possibly increase
And intervention may decrease cases
MR. MICHAEL JAHNCKE:
That’s the end of my
Thank you, Dr. McCarthy.
Are there questions from the subcommittee?
MR. BRUCE TOMPKIN:
Bruce?
This is Bruce Tompkin.
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_—_
1
the conclusion, it states that Listeriosis is not product
2
specific.
3
however, it is product-specific
4
in which multiplication can occur.
DR. PATRICK McCARTHY:
5
in terms of those foods
What I tried to point
6
out there is that it’s in hot dogs; it’s in vegetables;
7
it’s in a variety of foods.
8
product-specific.
10
13
So, within each of those
commodities, it is product-specific
questions?
is what I was saying.
Thank you.
MR. MICHAEL JAHNCKE:
11
12
And in that sense, it’s not
MR. BRUCE TOMPKIN:
9
_—
And in a general sense that may be true;
Other
Yes, Mike.
MR. MICHAEL DOYLE:
This is Mike Doyle.
14
you elaborate on this outbreak in Finland that was
15
associated with butter?
16
DR. PATRICK McCARTHY:
17
prepared to at this time.
18
I could talk about that.
Could
I don’t think I’m
I’d need some more time before
19
MR. MICHAEL JAHNCKE:
20
MR. MORRIS POTTER:
Other questions?
Morris Potter.
Yes.
I/d just
21
like to point out for the committee that three of the
22
areas covered by surveillance in the last case-control
23
study fall into the FoodNet catchment area, so while all
24
of the studies on Listeriosis aren’t the same, there is
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1
some overlap that allows one to look for general trends.
3
4
5
Thank you.
MR. MICHAEL JAHNCKE:
2
questions?
Thank you very much for an excellent
presentation.
Thank you.
6
DR. PATRICK McCARTHY:
7
MR. MICHAEL JAHNCKE:
Thank you.
Our next speaker is Dr.
He will be addressing characteristics
8
Richard Raybourne.
9
of Listeria monocytogenes, dose-response.
10
Any other
DR. RICHARD RAYBOURNE:
I’d like to thank the
11
committee for the opportunity to make this presentation
12
and also to thank the collaborators in the dose-response
13
effort whose names are listed there and two of whom are
14
in attendance today.
15
Next slide, please.
There are probably many
16
ways to define -- or at least several ways to define
17
dose-response and the concept of the dose-response model.
18
I’ve chosen one that was in one of the other Listeria
19
risk assessments by Farber, et al. , and that is the dose-
20
response model provides a functional relationship between
21
the probability that an individual will contract
22
Listeriosis and a specific dose or level of exposure to a
23
virulent strain of Listeria monocytogenes.
24
that was a reasonable definition, and I didn’t think I
.-——=
.
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1
could improve on it very much.
2
the paper.
3
In looking at the possible sources for
4
information on dose-response, there are four listed here.
5
The first we’ve heard something about in Dr. McCarthy’s
6
previous talk -- that is, the epidemiology and case
7
report information.
8
sources include animal studies and in-vitro studies of
9
various sorts which have addressed questions which are
10
11
o
SO, I just lifted it from
In addition to that, other possible
also related to dose-response.
Go on to the next slide, please.
Some of the
12
parameters that might go into calculating or developing a
13
dose-response model are, obviously, the number of
14
organisms; the food matrix or the food in which the
15
organisms are existing at the time that they are
16
consumed; the virulence of the particular Listeria
17
strain; and the host susceptibility -- that is, the
18
resistance or susceptibility of the host to infection.
0
Ci
u.
z
Ca
19
By combining these various factors, you would
20
develop several types of outcomes ranging all the way
21
from asymptomatic carriage of Listeria through more mild
22
diarrheal-type
23
ultimate end point of death in some individuals and also
24
the fetal abortions, as well.
illness to invasive disease to the
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1
n
The first issue I’m going to touch on is the
And this goes to the point
2
issue of the food matrix.
3
that was made earlier in regard to the data initially on
4
survival of Listeria in various foods, except the way
5
that I’m presenting or thinking of it here is in the more
6
qualitative sense of the effects of the types of
7
treatment as opposed to the quantitative or number of
8
things -- that is, to raise the question of whether
9
adaptation of Listeria to a acidic or a high-salt
10
environment can actually alter or result in the selection
11
or adaptation of a functionally more virulent population
12
of Listeria such as improving its ability to survive the
13
stomach acid barrier or within some host phagocytic
14
cells, as well as a result of adaptation to a harsh
15
environment.
16
specific stress in the food environment is actually the
17
same stress may not actually be relevant due to the sort
18
of global stress responses in some of these organisms
19
resulting in the phenomenon that’s sometimes referred to
20
as cross tolerance among these pathogens.
21
Whether the specific environment, the
In addition, another area that might well be
22
considered is the issue of the fat content in foods,
23
specifically again the question of whether a high-fat
24
content and the sort of relationship between Listeria and
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.——%
1
the structure of the food and the fat mice cells, for
2
example, could actually protect Listeria from gastric
3
acid or even modulate its interaction with some host
4
cells, perhaps.
I have not directly found a tremendous amount
5
.
But I did find one reference
6
of evidence on this area.
7
in -- 1 think it was in the Massachusetts outbreak where
8
there was actually a protective effect of skim milk
9
versus whole or 2 percent milk on one outbreak.
I think
10
this is an area where additional data would also be
11
needed.
12
Moving on from the food matrix issue to the
13
area of numbers of organisms associated with illness,
14
this is a collection of basically case report and
15
epidemiological data which contains some dose information
16
in it in which an effort was made to quantify the level
17
of Listeria.
18
to determine what the consumption was to actually get to
19
a dose.
20
was a given CFU, “ that means that it was normalized for
21
food intake.
22
it means that the intake of the food was uncertain.
23
we don’t actually know how much was consumed.
24
And in some cases, an effort was also made
So, in these cases where it just says, ‘tThedose
And in those where it says, “CFU per gram,”
Sor
Again, there may be other cases that I don’t
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And we
1
know about or that our group doesn’t know about.
2
would definitely appreciate information related to dose
3
from any other sources that the audience may know of.
What you can say about this
4
is that there’s
5
certainly a wide range of doses, and they’re basically
6
all over the place in terms of the level of Listeria
7
implicated in illness.
8
other subsets of data like this have been used in three
9
other Listeria risk assessments to produce dose-response
10
11
This type of data and various
models.
The next slide, please.
In the dose-response
12
of studies in the Farber, et al. risk assessment, they
13
developed the dose-response curves for both high --
14
normal populations and high-risk populations based on a
15
Weibull-Gamma model.
16
the total number of Listeria monocytogenes
17
the probability of illness.
18
approximate ID-10 and ID-90 doses which were extrapolated
19
from case report information.
20
In this particular graph, it plots
cells versus
This was based on
In another risk assessment, Buchanan, et al.
21
developed a conservative model using consumption data for
22
a single food source and Listeria incidence data.
23
this dose curve, the plot is again the log of Listeria
24
monocytogenes
In
cells versus the probability of illness.
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Finally, more recently, another risk assessment
1
2
was done for Listeriosis derived from soft cheese
3
consumption.
4
model.
5
what the cystograms represent.
6
the plot here, the risk of illness from one serving of
7
cheese versus the probability of illness.
8
curve represents the curve for the high-risk population,
9
and the lower curve represents the low-risk population.
10
o
u
Again, this used the same mathematical
This is a little bit harder to sort of access
But I will explain that
The upper
The point here is not to particularly dwell on
11
these models but to make the point that there are some
12
limitations to the approach used in these studies.
13
clearly, these are all based on epidemiologic data
14
which -- in addition to this, in these studies, the
15
virulence is basically assumed in the sense that
16
virulence would be considered a more or less absolute
17
characteristic, either virulent or avirulent, and that
18
the host susceptibility in both of these studies -- in
19
all three of these risk assessments -- was identified as
20
an important variable.
21
ways to address the issue of relative susceptibility,
22
this was essentially based on, to use the term quoted
23
from one of the studies, a IIroughapproximation of the
24
relative susceptibility.”
And,
However, in terms of developing
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.-.
so, for the rest of the time, I’m going to try
1
2
to present some approaches by which we could use some
3
other data sources other than the epi-data and case
4
report data to try to improve the level of -- or decrease
5
the level of uncertainty in these dose-response models,
6
particularly dwelling on the issues of pathogen virulence
7
and host susceptibility.
8
And so, I’m going to present some animal and
9
various other kinds of -- and other kinds of data, in-
10
vitro data, which have been developed extensively
11
Listeria since Listeria is a favored organism for both
12
microbiologists
14
studies that have been done and is not intended to be an
15
exhaustive review of Listeria virulence or immunological
16
mechanisms associated with Listeria.
17
what kind of data in these studies can be used to help us
18
in development of models.
But the focus is on
First, dealing with the issue of pathogen
19
UJ
1U
and immunologists alike.
This is a brief overview of the types of
13
m
m
in
We might pose the question:
Can experimental
20
virulence.
21
virulence studies be used to identify a range of relative
22
Listeria virulence?
23
to our data sources, in looking at human studies, as
24
we~ve heard, the outbreaks are focused on a small number
g
w
cc
If you’ll look at our -- going back
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1
of predominant serotypes: the l/2a, l/2b and 4b.
2
Although, if you noticed in the slide on the outbreaks,
3
the butter outbreak was mentioned in there.
4
believe it was actually a serotype 3a.
5
to every rule, I guess.
And I
So, an exception
And it’s important here, I think, to remember
6
7
when talking about these serotypes -- and also, the
8
phagetypes and ribotypes -- that these data are
9
essentially valuable epidemiologic tools but are not
10
necessarily mechanistically related to the virulence of
11
the organism as well, which I’m sure you’re all aware of.
Next, please.
12
One virulence factor that’s been
13
studied extensively in in-vitro studies is
14
Listeriolysin O, which we’ve already heard discussed
15
today.
16
isolates of Listeria.
17
that it’s required for survival within microphage cell
18
lines, which are an important line of defense against
19
Listeria.
20
survival of even Listeriolysin O positive Listeria is
21
actually limited in in-vitro studies to a small
22
percentage of the bacteria, indicating that there is some
23
selection or adaptation that goes on in this system, as
24
well.
Essentially, it’s produced by all clinical
And in-vitro studies have revealed
But this is also not an absolute in that the
Listeriolysin O negative strains, however, do not
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1
survive at all in these in-vitro microphage survival
2
models.
3
.-
Functionally, the Listeriolysin O enables the
4
organism to escape from the phagolysosome of the
5
microphage and mediate the next phase of its virulence
6
cascade or mechanisms which would be the cell-to-cell
7
spread.
8
cells -- such as liver cells, for example, and move
9
within epithelial cells -- and move within the cytoplasm
That is, Listeria can also invade nonphagocytic
10
and spread from cell to cell by means of actin
11
polymerization.
12
determinate responsible for this is a surface protein
13
Act A which mediates actin polymerization.
The molecule or the virulence
In addition to this, there are also a series of
14
15
proteins involved in getting the organism into the cell
16
in the first place.
17
protein InLA which facilitates adherence to and invasion
18
of phagocytic cells.
One of these is the Internalin
Next, please.
19
Looking at how these studies
20
based on essentially salt culture models pan out in
21
animal studies, it’s observable that Listeriolysin
22
strains are all -- Listeriolysin O negative strains are
23
avirulent in mice in parenteral and oral inoculation
24
studies.
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In addition to this, Act A negative strains
1
2
also show reduced infectivity in mice.
3
another group of virulence determinates, the
4
phospholipases, play an important role in the ability of
5
Listeria to evade the early host neutrophil-mediated
6
defense mechanism in the mouse liver, which has been
7
shown in in-vitro studies.
So, we can look at what some of this data tells
8
9
n
And, finally,
us in terms of dose-response in the next slide.
In this
10
study, this is a study based on oral inoculation and
11
shows a reduction in the number of colony-forming
12
in the mouse spleen and liver comparing hemolysin
13
positive and hemolysin negative Listeria strains.
14
this gives us a kind of quantitative data based on the
15
presence or absence of hemolysin in an oral inoculation
16
model.
units
So,
The next example shows the fact -- basically,
17
18
the take-home message from this is that the Listeriolycin
19
is not the whole story in terms of in-vivo virulence in
20
the animal models in that strains which have the
21
Listeriolycin but lack the phospholipase C are reduced in
22
virulence.
23
Putting all the sort of animal virulence factor
24
studies together into a model of what happens in the oral
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.-.
1
infection in the mouse model in Listeria, you could
2
summarize it by saying that Listeria can attach via the
3
attachment virulence factors to either M-cells in the gut
4
or gut epithelial cells, become internalized, then move
5
through the cell via means of actin polymerization
6
emerge on the other side of the gut barrier to be taken
7
up by macrophages, which they are capable of survival in,
8
and from there they’re capable of then disseminating
9
various tissues and causing various pathologies
10
u
UJ
CL
<
CL
w
m
L(J
FCC
0
II
u
u
and
to
in the
animal.
11
Next, please.
12
the dose-response parameters, host
13
question that werre posing here is:
14
immunocompromised states provide us with any useful
15
quantitative data on relative susceptibility
16
This is a fairly ambitious question.
17
that as we progress through there, you can see that there
18
may be some relationships that are possible to exploit in
19
this question.
20
Looking at the last component of
susceptibility,
the
Can animal models of
in humans?
However, I think
We know from looking at human studies that
21
healthy adults are usually asymptomatic carriers.
22
Nonperinatal disease usually occurs in individuals as
23
various predisposing conditions.
24
very young, infants, individuals with AIDS -- although,
For example, pregnancy,
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1
this is actually kind of an interesting case because
2
parenthetically,
3
it was initially thought that Listeria would be a common
4
opportunistic
5
be actually a sort of unusual opportunistic
6
AIDS, relatively speaking.
7
which will emerge later on in the discussion.
8
immunosuppressive therapies of various kinds and,
9
finally, old age are other predisposing conditions.
when the AIDS epidemic first developed,
infection.
And, in fact, it turned out to
infection in
And there’s a reason for that
Cancer,
What you can say about this is that all of
10
11
these predisposing conditions are likely to involve
12
different types of immunosuppression mechanisms.
13
to say, the factors that predispose in pregnancy are
14
probably different than the factors that may predispose
15
in cancer or in infancy or in old age on a mechanistic
16
level.
17
model of Listeria infection tells us.
18
That is
And this is more or less what the mouse animal
In fact, one of the most useful of these models
=6
k
u)
<
-1
19
and instructive has been the use of the severe combined
20
immunodeficiency mouse model.
21
led to the realization that there was an extremely
22
important interaction of innate and adaptive immune
23
systems in the mouse.
24
immune-deficient mice which lack either both T-cells and
And it was this model that
That is that the SCIDS mice, the
n
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1
B-cells, do not clear an infection but also, at the same
2
time, do not succumb readily to the infection.
3
they remain chronically infected, which was kind of a
4
surprise at the time of the initial observation,
5
think.
6
In fact,
I would
The neutralization, however, of the Cytokine
7
Interleukin 12 or tumor necrosis factor L for either one
8
of those results in an increase in the lethality of the
9
infection in SCIDS mice and an increase in CFUS to
10
quantify it again, thinking always of what quantitative
11
data we can get from this, by between I and 3
logs.
The take-home message from the SCIDS mouse
12
13
model is that in the absence of T-cells, the infection is
14
controlled but not eliminated.
15
demonstrated that this effect is mediated by the
16
polymorphic nuclear leukocytes, neutrophils -- primarily,
17
monocytes, which are producing Interleukin 12 -- and NK-
18
cells,
19
NK or natural killer cells, which produce gamma
20
interferon, which is one of the most important host-
21
resistance mediators in the mouse model of Listeria.
Various studies have
which are present in these animals which produce
22
On the next slide, this model, the SCIDS model
23
is summarized by showing on the top, lJSCIDSMice,tr which
24
remain heavily infected, chronically infected with
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1
Listeria.
2
innate immune system mechanisms -- that is, the NK cells
3
and the neutrophil populations.
4
But the Listeria is held in check by the
In the normal mice, these things are operating
5
early on in the infection until such time as the T-cell
6
mediated mechanisms kick in ~ resulting eventually
7
sterile immunity in this model.
8
9
in
Looking at the next slide, you can see that
this has a direct impact on the dose-response to Listeria
10
in a system where neutrophils are depleted by a
11
monoclinal antibody against the neutrophil determinant.
12
The dose-response effect is really quite remarkable.
13
That is, the infective -- the lethal dose in this system
14
essentially drops from four times ten to the eighth to
15
four times ten to the fourth or a four-log increase in
16
susceptibility, you might put it, in this particular
17
mouse model in that zero of five of these -- it may even
18
go lower than this -- zero of five of the controls are
19
killed, whereas three of five of the neutrophil-depleted
20
animals are killed.
21
Next, please.
The purpose of this slide is not
22
to have you figure out one single thing that’s on this.
23
This is the pathway of the -- and I put it up here for
24
the point of showing that extensive studies have been
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1
done to show, to elucidate the various pathways involved
2
in resistance.
3
4
mechanistic studies are embedded information on dose-
5
response to Listeria that is linked specifically to
6
certain kinds of immune mechanisms.
7
to summarize on the next slide.
8
of ways to manipulate this system, you can see that
9
recombinant Interleukin-1 administered to the mouse
n
:
Looking at various types
results in a 250-fold decrease in the level of infection
11
in the spleen.
Looking at the Interleukin 6 knockout, there’s
13
a 300-fold effect.
14
animal lacks Interleukin-6; therefore, in the absence of
15
that component of the immune system, there’s a 300-fold
16
increase in CFUS.
17
UJ
These I have tried
10
12
cc
The point is that within these various
That is a knockout animal.
Using, again, a monoclinal antibody to deplete
18
Interleukin-12, there’s a 500-fold effect.
19
interferon is a thousand-fold effect.
20
thousand-fold effect in the mouse model.
21
But this
Gamma
TNF alpha, also a
I wanted to also mention at this point, while
22
we’re on the topic of Cytokines, what is happening and
23
some of the events that go on in the pregnancy model as
24
well because they fit in nicely to what we know from the
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1
mouse studies.
And that is that there’s studies in both
2
human and animal systems that show there’s actually an
3
inhibition of NK cell function during pregnancy.
4
know from the animal studies that NK cells are extremely
5
important in the resistance to Listeria infection.
And we
In addition to this, there’s a shifting of the
6
7
T-cell responses during pregnancy towards what’s called a
8
Th2 or T-helper-2 type Cytokine secretion pattern.
9
is, Interleukin-1, Interleukin-5 and Interleukin-10 are
That
10
produced.
11
the mouse model that the inhibition of Interleukin-4
12
actually has a beneficial effect on survival of mice
13
infected with Listeria monocytogenes so that those things
14
which tend to favor production of IL-2 are actually
15
detrimental in -- of Interleukin-4 are actually
16
detrimental in terms of the infection.
17
of the events that’s going on during pregnancy,
It’s also been shown in other -- in studies in
And this is one
In addition to this, it’s also been reported
18
19
that spontaneous abortions in humans are associated with
20
an increase in the sort of yin-to-the-yang
21
Cytokine.
22
it essentially begins to recognize the fetus as a foreign
23
body and reject it.
24
is one of the prime ways to attempt to drive this kind of
here, the Thl
When this type of response gains predominance,
And it’s worth noting that Listeria
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1
response.
2
system that’s doing what we can see in the animals.
3
Finally, of course, in terms of these animal
4
studies, there are some serious questions that need to be
5
asked about the use of these various animal models.
6
First of all, would be:
7
monoclinal antibody-based deletion have any relevance in
8
humans?
9
Does the use of gene knockout or
Secondly, do the mechanisms defined in the
10
mouse model operate in human infections?
11
very little information on what is happening
12
mechanistically
13
found.
14
more information that I’m not aware of.
15
u
w
m
<
-1
So, there may be a link there in the human
There’s very,
in human Listeriosis, at least that Irve
Maybe, again, some of the committee members know
And finally, a kind of subset to this:
Can the
16
host-resistance mechanisms identified in the animal
17
studies be connected with human biomarkers of exposure
18
and susceptibility?
19
important biomarkers in animals -- gamma interferon, TNF
20
alpha, for example -- and use them to answer questions
21
about human exposure and susceptibility to Listeria?
22
That is, can we use what we know are
In the next slide, this is kind of a bit of a
23
tongue-in-cheek
24
Washington Post just this past May 13th.
slide in a sense, coming from the
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1
anyone the impression that the Centers and FDA might be
2
working at cross-purposes in some instances.
3
recently-approved
4
spectacular results in treatment of rheumatoid arthritis,
5
may have caused serious infections in some patients, six
6
of who have died.
7
drug, Enbrel, which has produced
Enbrel is a biological response modifier,
8
chemically engineered to attract and neutralize tumor
9
necrosis factor alpha.
Therefore, there is some
10
relationship
11
Listeria infection in mice and these kinds of drugs.
12
-
But the
in terms of what we know, at least about
In addition to that, one could only anticipate
13
that as more of these mechanisms are investigated and the
14
drug design becomes more sophisticated, there will be
15
more and more therapies like this that are not just
16
general immunosuppressive therapies, but very
17
specifically targeted to certain immune mechanisms.
18
that there may be more and more instances where sort of
19
designer drugs can knock out specific components of the
20
immune system to a good effect in the treatment of
21
inflammatory disease, but to a possible detrimental
22
effect in terms of susceptibility to illness.
23
24
So
Secondly, as has been mentioned previously,
we’re in the process of developing in conjunction with
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.s—-.
1
the University of Georgia the Rhesus-pregnancy
model.
2
And in addition to the dose-response data -- which will
3
undoubtedly not be available for the July 6th deadline,
4
but hopefully sometime in the future, the absolute
5
numbers in dose-response -- we’re also trying to develop
6
some biomarker data in conjunction with that study so
7
that we can then if not look at -- if we can then verify
8
what’s happening in the mouse model and this sort of
9
closely-related non-human primate model, it may go a long
.
10
way to validating the use of the animal data in terms of
11
modelling the relative susceptibility.
12
Next, please.
Going back to the first slide
13
and sort of summing it up and restating or stating maybe
14
clearly for the first time, how we’re going to use these
15
various pieces of data or how we’re proposing to use
16
these pieces of data, in terms of the issue of numbers of
17
organisms and food matrix, we’re proposing to develop
18
distributions
19
human data.
20
for probability of illness based on the
Ultimately, we hope in the future to be able to
21
incorporate information from the dose-response
22
ongoing now when they become available.
23
hopefully, as more information from epi-studies comes
24
available, that will also be incorporated.
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We also will,
But at the
143
__—__
1
present, we’re essentially operating from the same data
2
set that other risk assessment efforts have operated from
3
in terms of human data.
4
Next, please.
In terms of organism virulence,
5
we’re proposing the concept of using the in-vitro and
6
animal data to model a range of virulence for Listeria
7
monocytogenes
8
plus-minus virulence situation, to see if that could be--
9
help refine the model.
to determine -- rather than a sort of a
10
And, finally, in terms of host susceptibility,
11
we/re hoping to explore the use of the animal, primarily
12
mouse data, to model relative susceptibility
13
immune-compromised
14
correlate the mouse biornarkers with the primate model as
15
surrogates for human infection.
16
17
states.
Ultimately, we would like to
And that~s pretty much the status of the doseresponse effort and data forces.
18
MR. MICHAEL JAHNCKE:
19
for an excellent presentation.
20
in various
Thank you.
Thank you, Dr. Raybourne,
We’re going to just break from regular
It/s warm in this room, and our
21
procedure a little bit.
22
audience is probably wilting.
23
minute break.
24
break down this wall and open up the two rooms to air
We’re going to take a 20-
What that will allow people to do is to
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.F—.
And then the next one will be our
1
this out a little bit.
2
committee discussion with all the speakers and our
3
National Advisory people.
so, 2:25, come on back.
4
5
(Whereupon, a recess was had in this
6
matter.
MR. MICHAEL JAHNCKE:
7
8
afternoon session.
9
housekeeping point.
Let us get started on the
Before we do, there’s one little
Committee members need to turn in
10
their -- they’ve got a calendar for August through
11
December as far as availability for meetings.
12
out and leave it with the staff in the hallway.
Fill that
13
We’re going to have our committee discussion
14
with all the committee members plus the presenters for
15
today.
16
of you have about the document itself, now is the time to
17
bring those up.
18
questions that were first presented this morning.
Keep in mind, if there are any questions that any
co
—
o
And also, keep in mind the three
0
a
Question one:
19
20
sound?
21
right data?
22
anything?
23
24
Is the scientific approach
The second question was:
Do they have all the
And the third one is:
Have they overlooked
With that, we’ll -- Yes?
DR. ALISON O’BRIEN:
of this committee.
I’m not a regular member
May I ask a question?
--.—
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MR. MICHAEL JAHNCKE:
1
2
3
4
5
Absolutely.
Identify
yourself.
DR. ALISON O’BRIEN:
Safety Committee.
I’m a member of the Food
It’s Dr. Alison O’Brien.
I wanted to ask a question of the last speaker,
6
Dr. Raybourner who is right next to me.
7
you were talking about using animal model data, pili
8
mouse model data as part of your dose-response
9
assessment, guesstimates, estimates.
10
Dr. Raybourne,
Are you aware of the older data from Christina
11
Cheers (phonetic) looking at innate susceptibility
12
different mouse strains to Listeria?
13
nothing about the basic genetic host background in your
14
discussions today.
15
being modulated.
16
I’m gonna say what I think she found.
17
there was a gene in mice that controlled early response
18
to infection which allowed certain strains of mice to be
19
several logs more susceptible to Listeria than others.
20
think it was a complement, actually, complement-medicated
21
factor on mouse chromosome 5.
22
be wrong about that, and I don’t want to mislead.
23
there’s a whole set of data on that.
24
of
Because there was
You talked about Cytokine response
And I can~t remember, unfortunately
--
And she found
And you never -- I could
DR. RICHARD RAYBOURNE:
But
Rich Raybourne, FDA.
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1
Yes, I’m aware of that data.
2
recall, almost a mirror image of the salmonella ITY data;
3
is it not?
I think it’s kind of, as I
4
DR. ALISON O’BRIEN:
5
DR. RICHARD RAYBOURNE:
6
It is not.
The strains are
different, though.
DR. ALISON O’BRIEN:
7
It is not the same gene;
8
and it doesn’t have exactly the same mouse profile in the
9
product, no.
But the product of the gene is not ITY, IEN
10
RAM now.
It’s a different gene, and I think it affected
11
complement, C-5 component of complement.
12
AJ strain of mice, which is low in that complement
13
component, was particularly susceptible to Listeria.
I believe the
so, since you’re using mouse models, I thought
14
15
you might go back and check that.
16
but I know it isn’t the same profile as salmonella
17
exactly.
18
19
DR. RICHARD RAYBOURNE:
agreeing with you.
My data may be wrong,
Yeah, that’s -- I’m
I’m saying it’s not the same.
20
DR. ALISON O’BRIEN:
21
DR. RICHARD RAYBOURNE:
Oh, it’s not the same.
I think it’s -- in the
22
C-57 is relatively more resistant in Listeria and it’s
23
more susceptible in salmonella.
24
MR. MICHAEL JAHNCKE:
Other questions?
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1
2
DR. RICHARD RAYBOURNE:
point.
But that~s a good
Thank you.
3
MR. MICHAEL JAHNCKE:
4
MR. BRUCE TOMPKIN:
Bruce?
Bruce Tompkin.
I just had
5
one question.
6
asymptomatic carriage.
7
healthy adults are usually asymptomatic carriers.
8
this a reality?
9
healthy individuals may have an indigenous population of
Both of you mentioned carriage,
Another one was the phrase where
Is
Are there carriers whereby normal,
10
Listeria monocytogenes in the GI tract?
11
transient, just as a result of consuming food; and when
12
stool surveys are conducted, they merely show up as a
13
positive because of whatever exposure?
14
DR. PATRICK McCARTHY:
In the studies that I
15
referred to, they were point prevalence.
16
simply were there at the time.
17
several thousand people were involved.
18
in those individuals.
19
Or is it a
And so, they
In the German studies,
And they found it
They found higher rates when they tested the
20
same person over a period of time.
21
that there are people that are carrying the organism but
22
do not show symptoms.
23
I donft know.
24
It’s my understanding
How long they carry the organism,
MR. MICHAEL JAHNCKE:
Yes, David?
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MR. DAVID ACHESON:
1
David Acheson.
That, to
2
me, raises of the question of any data out there on
3
person-to-person
transmission.
DR. PATRICK McCARTHY:
4
This is Pat McCarthy:
5
did see one study -- and, of course, I can’t remember
6
exactly the name of the study at this time -- but there
7
was a suggestion that individuals living in the same
8
household may have -- there may have been transmission
9
person-to-person.
But, for the most part, in all the
10
studies I looked at, that was not an issue.
11
person transmission was not an issue.
12
13
MR. MICHAEL JAHNCKE:
committee?
Other questions from the
Yes, Michael?
MR. MICHAEL DOYLE:
14
Person-to-
This is Mike Doyle.
15
Richard, I think I noticed on your slide, you had a
16
estimated dose of ten to the ninth for the butter-
17
associated outbreak.
Did I read that right?
DR. RICHARD RAYBOURNE:
18
Rich Raybourne.
It
19
should not -- if that’s what it said, it shouldn~t have
20
said that.
21
between a hundred and about ten to the fourth.
22
I think the dose was, as I recall, ranging
MR. MICHAEL DOYLE :
23
from the butter.
24
the ninth.
Yeah.
That was the count
But above that, I think I saw ten to
And I was curious to know how you arrived at
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that number.
DR. RICHARD RAYBOURNE:
2
3
No.
I think the number
is much lower than that.
4
MR. MICHAEL JAHNCKE:
5
MR. BRUCE TOMPKIN:
Other questions?
Bruce?
We haven’t really discussed
6
the document.
7
simplest is figure one.
8
I don~t.
9
But I couldn’t figure it out -- the top portion, in
10
And I only have two questions.
The
Ifve tried to understand
it, and
And there’s no sense spending time on it now.
particular.
But my other comment really was relating to
11
12
Page 6.
13
this is just all background and introduction, Pages 4, 5
14
and 6, and it’s not in here -- and I’d just like to
15
suggest perhaps you may wish to do this -- but it is to
16
actually compare the policies.
17
risk assessment is not to address policy at this point in
18
time.
19
be helpful to compare the policies in other comparable
20
countries, industrialized countries, in terms of their
21
Listeria policies, the numbers of cases per hundred
22
thousand -- and I know CDC will wince at that thought
23
because no one has as good a system as the United States
24
what the data are saying.
And as part of the background information where
I know the intent of this
But as a matter of comparison, I thought it would
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Anyway, the number of cases per hundred
1
2
thousand and also any information on percent of positive
3
food samples with the intent to see whether or not
4
there’s any relationship between the policy, the actual
5
exposure in terms of percent positive foods that are
6
reported in those countries, and then the public health
7
impact.
8
information at this point.
9
would not be anything actionable, as I understand,
10
.-.
u
w
co
<
.
And that would just be a matter of background
That’s all it would be.
It
from
this risk assessment.
11
MR. MICHAEL JAHNCKE:
12
MS. CATHY DONNELLY:
Cathy?
Cathy Donnelly.
I~d just
13
like to follow up on Bruce’s point and put in a plug for
14
a comment that was made earlier today in the public
15
comments section.
16
practices that leads to production of a food.
17
case that was being discussed was cheeses, and the focus
18
of the risk assessment was on food type or cheese type.
19
And I/d like to put in an appeal for production
20
practices, i.e. farmstead cheese versus cheeses made in
21
the manufacturing plant.
22
difference in incidents.
23
24
And that being a focus on production
And I think you’ll see a big
MR. MICHAEL JAHNCKE:
questions?
And the
Other comments,
Yes, Dane?
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MR. DANE BERNARD:
Thank you.
Dane Bernard,
2
not an immunologist.
3
it’s worth.
4
immune response, how do you plan to take what you’ve got
5
and translate that into what I think most of us would
6
accept as a population who distributes a wide range of
7
immunological conditions which vary.
8
curious because we’ve got models that show different
9
parts of how the immune response can be activated or not
10
11
So, take your question for what
The fine report on how we’re gonna model
I guess I’m just
activated against this particular challenge.
But how do you go from where we’re at now to
12
what you, what I think will need to do, which is look at
13
the human condition and the whole host of immunological
14
conditions from whatever you call normal or whatever we
15
rank as normal down to those who are very, very severely
16
immunocompromised?
17
DR. RICHARD RAYBOURNE:
Rich Raybourne, FDA.
18
think that the issue that you’re raising is one that
19
we’re at the moment struggling with as well.
20
that clearly there’s a spectrum of -- going to be a
21
spectrum of immunocompromised individuals.
22
at the moment we have a good handle on ways that we can
23
realistically measure that in the population as a whole
24
to even get it, to get at what proportion of the
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I don’t think
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1
population is, quote, unquote, IIimmunocompromised” and to
2
what degree they’re immunocompromised.
3
technically daunting task.
I think that the positive side of using the
4
0
v
It~s kind of a
5
data that I -- of sort -- of the type that I presented is
6
that it’s at least a quantifiable measure as opposed to
7
kind of a rough approximation.
8
also in as many ways as we can make sure that what we
9
learn from the animal models, particularly the mouse
I think we need to try to
10
models, is translatable into the human situation.
11
is particularly difficult in Listeria because there’s
12
essentially no prospect for doing any kind of human
13
clinical trials in Listeriosis.
14
approach that we have right now is to try to develop a
15
surrogate model, which werre trying to do in a primate,
16
in a primate system.
This
And so, the best
It might also be possible, for example, to
17
18
develop some of this kind of correlative human data in
19
outbreaks or in following up on patients involved in
20
outbreaks.
21
extent at the present time.
22
I’m sorry we don’t have a better answer at the moment for
23
you .
24
But it just hasnft really been done to any
MR. DANE BERNARD:
So, it~s a good issue, but
Follow-up, if I might?
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1
We/ve got data on those populations which seem to be more
2
at-risk -- this is outbreak data -- who gets Listeriosis
3
predominantly and who doesn’t.
4
not an immunologist.
5
presented, I think, to theorize what some of the
6
mechanisms of susceptibility might be in those
7
categories.
8
9
We know enough, I think--
We know enough basis, what you’ve
Have you thought into that scenario to see if
there’s any mileage there?
I mean, for example, the less
10
than one-year-old group.
11
still developing, immature, unchallenged, da, da, da, da.
12
Based on the mouse models that you’ve got, is there
13
anything that applies there?
14
spectrum, same thing.
15
We know the immune system is
At the other end of the
DR. RICHARD RAYBOURNE:
Rich Raybourne again.
16
I think in terms of doing those kinds of studies, we
17
should look at, for example, in levels of quantifiable
18
types of markers, like the Cytokines I mentioned,
19
these populous -- it’s theoretically possible to do that.
20
The problem with doing that -- at least my understanding
21
of it -- is in the absence of an ongoing infection
22
measuring levels of circulating Cytokines is not going to
23
be very worthwhile.
24
would want to do to get into sort of a more technical way
in
And at the very least, what you
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1
of approaching this, if I could, what you would want to
2
do is to somehow collect materials from these
3
individuals, stimulate them in-vitro and look at the
4
ability of the cells to respond.
5
huge and expensive task to do this kind of thing.
I mean, it would be a
There may be other simpler ways you can measure
6
7
this, looking at -- and non-invasive ways, too.
8
we’re currently trying to think of approaches to this in
9
terms of even to the point of doing serological-type
And
10
surveys, although this is problematic in Listeria because
11
there’s not a lot of evidence that I’m aware of that
12
serum antibody responses are important in resistance to
13
Listeria.
14
could answer it and come up with an approach to it.
15
we’ve certainly thought about it but have not done that
16
at this point.
17
So, I mean, it’s a great question.
MR. MORRIS POTTER:
Morris Potter.
I wish we
And
Rich, I
18
think what Dane is suggesting is that say, for instance,
19
in the geriatric literature, it’s known more or less
20
which subsets go first.
21
at susceptibilities of various mouse strains that are
22
absent, those things that go in 50-year-olds and then the
23
things that start to go when we hit 60 and so forth, that
24
we might be able to then model the human population
And, therefore, if we can look
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1
those age groups and suggest when people are going to
2
become more susceptible to infection, when they’re going
3
to become more susceptible to serious invasive disease
4
and that sort of thing.
5
MR. WILLIAM JAHNCKE:
Bob?
6
MR. ROBERT BUCHANAN:
Bob Buchanan, FDA.
Yeah,
7
I think I’d like to echo on what Morrie says.
8
wondering if you may be making this more complicated than
9
is warranted considering the huge range of -- and
I/m
10
certainly, you’re going to face with the rest of your
11
risk assessment.
12
presentation a bunch of years ago on trying to get some
13
estimates of increased risks associated with aging.
14
while certainly you’re gonna have to come up with some
15
kind of fudge factor to relate the increased
16
susceptibility,
17
age-related decreases in, for example, T-cell
18
proliferation.
19
related equations that we could develop for achlorhydria
20
in the aged.
21
off with trying a couple of fairly simple relationships
22
that have been gleaned from these broad population
23
studies, start simple.
24
more sophisticated.
Morrie and Jim Smith and I did a
And
it was not very difficult to find some
It was not difficult to come up with age-
So, I’m wondering if we couldn’t just start
And if it didn’t work, then get
.-.
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DR. RICHARD RAYBOURNE:
1
2
MR. MICHAEL JAHNCKE:
4
DR. WESLEY LONG:
6
7
8
9
___
I think thatls a good approach, yes.
3
5
Rich Raybourne again.
Yes?
I do want to make one point,
though .
MR. MICHAEL JAHNCKE:
Identify yourself,
please, Wes.
DR. WESLEY LONG:
Wes Long, FDA.
That it’s
consistent with some of our conversations yesterday that
10
what we’re doing is, you know, we don’t have all the data
11
now certainly, clearly.
12
framework at this stage and using that to figure out what
13
to do next.
14
risk assessments as more information becomes available.
15
so, I think this sort of thinking is important.
16
But what we’re doing is laying a
And we talked about how we can modify the
Rich sort of mixed up the data we’d like to get
17
from outbreaks, that sort of thing, which is future,
18
which we don’t have now.
19
thinking now, I’m hoping that we will sort of lay the
20
groundwork, even though we may not be able to utilize
21
some of the things that he’s talking about immediately.
But by doing this sort of
22
MR. MICHAEL JAHNCKE:
23
DR. ALISON O’BRIEN:
Yes?
This is Alison O’Brien.
0
24
Following up on what Bob Buchanan said about T-cell
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..-.
some kind of marker that suggests you
1
proliferation,
2
might be more susceptible to Listeria.
3
back to something Dr. Raybourne said during his talk.
4
Why aren’t a lot of AIDS patients infected with Listeria,
5
or are there?
6
subcategory.
7
portion, given that if we accept the paradigm that this
8
is an organism that uses protective immunity as related
9
to cell-mediated immunity, not pneumo-immunity.
10
The question goes
I mean, I know that I saw that as a
But to me, it seems a surprisingly small
DR. RICHARD RAYBOURNE:
Rich Raybourne again.
11
In terms of the AIDS question, I think part of the answer
12
-- and you’re right.
13
think it would be among AIDS patients.
14
of the sort of statements in their first papers that came
15
out when there were finally some Listeria AIDS cases.
16
And I think part of the reason for that may relate to the
17
observations with the effects of, for example, the
18
Interleukin 4 and the fact that it acts -- which in CD-4
19
deficient patients, is going to be lower.
20
mouse model, when you neutralize -- and this is not a
21
complete answer, but it’s sort of a clue -- that if you
22
neutralize IL-4, you actually ameliorate the Listeria
23
infection in the mouse model.
24
detrimental effect.
It’s not as common as you would
And this was one
And in the
So, it has kind of a
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Yes, go ahead.
1
MR. MICHAEL JAHNCKE:
2
DR. PATRICK McCARTHY:
This is Pat McCarthy.
3
It’s true that in AIDS patients, in some of the earlier
4
literature, researchers were saying that it’s not very
5
common in the AIDS patients.
6
’88, there was an estimate that AIDS patients have
7
Listeriosis about 150 times more often.
8
recent, I believe there was another estimate that AIDS
9
patients may have Listeriosis about 280 times as often.
10
But then about 186, ’87,
Then, more
so, it’s true that in the beginning, the
11
researchers were wondering why Listeriosis wasn’t showing
12
up in AIDS patients.
13
available, estimates started to increase.
But as more information became
14
MR. MICHAEL JAHNCKE:
Yes, Bob?
15
MR. ROBERT BUCHANAN:
Bob Buchanan, FDA.
My recollection was that
16
I just wanted to affirm that.
17
the approximate increase in risk associated with
18
Listeriosis and AIDS was about 300-fold.
19
there is a very substantial increase in risk.
20
MR. MICHAEL JAHNCKE:
21
MR. DANE BERNARD:
22
not an immunologist.
23
immunology.
24
Yeah,
Dane?
Thank you.
Still not.
So, I think
Dane Bernard,
But we’re not on
Another factor, I think, when you look at the
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1
data on incidence of Listeriosis in people with AIDS,
2
you’ve got to look at the interventions that go on there
3
as well.
4
dietary advice, is all provided once a person is
5
diagnosed in that category.
6
mitigation or risk management strategy there, I think,
7
that has a strong intervention that you’re seeing showing
8
up in health statistics.
_—
So, therers a risk
Other comments and
MR. MICHAEL JAHNCKE:
9
10
Prophylactic use of antibiotics, extensive
questions from the committee?
11
Yes, Bruce?
12
MR. BRUCE TOMPKIN:
r
rhis is Bruce Tompkin.
I’d
13
like to have a little clearer 1mderstanding
14
information is to be given to ithe risk assessment team.
15
If someone has data, do they just say, “Here, Dick
16
Whiting.
17
that you went through with a published announcement
18
the Federal Register, and so there’s probably a formal
19
mechanism.
20
will be used or considered and so on?
21
to what degree -- I know this process is one of the
22
processes we’re going through now.
This is a public
23
process.
So, I assume data
24
that’s provided will become public or available to the
Here it is”?
as to how
Or is there a mechanism -- I know
in
But how do we know that information provided
This is an open process.
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1
public.
2
Could you help me with that a little bit?
3
DR. RICHARD WHITING:
Richard Whiting.
Yeah.
4
There’s a paragraph or two in that Federal Register
5
Notice as a result of some of the discussions with us and
6
our lawyers and so on, that I think we’re probably
7
breaking some new ground for FDA here, as well.
8
9
The information that would be submitted, I
think you would have to expect that it would become
But we did say in there that we
10
public information.
11
would accept information that has been summarized or
12
blinded and various terminologies like this.
13
say, the meat industry, for example, through one of your
14
trade associations wanted to do a quick survey of
15
whatever Listeria your members might have, and the trade
16
association would just present a summary to us, that
17
would be the information that we would have.
18
So, if,
And as risk assessors, we would then try to
The more
19
evaluate that information as best we can.
20
information, the more details you could provide, the more
21
useful the information would be to us.
22
what is offered.
23
came in, we might have an indication of what methods were
24
used, what sensitivity -- if it was presence/absence
But we’ll accept
I would like to think that if some data
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1
data, what sensitivity might be there.
But, again, we will just accept to try to use
2
whatever people are willing to submit to us.
4
recognize this is sort of a new situation, I think, for
5
all of us.
6
scientific process and not a regulatory process, and I
7
guess we’ll have to see how it goes.
UI
<
-J
And werre gonna try to use this as a
This is Morris Potter.
8
MR. MORRIS POTTER:
9
I could amplify on that a little bit.
If
Part of the
10
rationale for using risk assessment is that it’s a
11
transparent process and that people who look at the risk
12
assessment ought to be able to repeat it using different
13
assumptions.
14
data sources available.
15
useful for the risk assessment but that might be felt
16
inappropriate to become public, they may still be useful
17
in terms of trying to validate things internally.
18
think that our preference is to use risk assessment to
19
help in making our decisions on risk more transparent,
20
more understandable to the broader audience.
21
u
u
And we
3
And that does create a need to make the
If there are data that could be
We wouldn~t want to turn our backs on data that
And if you have things that you’d like
22
could be useful.
23
to discuss, we can chat with you.
24
But I
Wes, did you have any clarification on that?
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DR. WESLEY LONG:
I do.
First of all -- This
I have the answer to this because it
2
is Wes Long, FDA.
3
was reported in Food Chemical News on the back cover page
4
there about six weeks ago that the Risk Assessment
5
Clearing House set up through the Food Safety Initiative
6
was going to be collecting the Listeria data.
7
I’m not sure what the source of that
But there is a Risk Assessment
8
information was.
9
Clearinghouse that is at the University of Maryland
10
thatls a part of FDA’s new Joint Institute for Food
11
Safety and Applied Nutrition.
12
of -- This clearinghouse is intended to be a repository
13
for data methods, models, anything to do with risk
14
assessment, initially focusing on microbial risk
15
assessment needs.
16
17
And we are in the process
Dave Lineback (phonetic) , who is the -- I~m not
sure of his title, the chair or the head --
18
MR. MICHAEL JAHNCKE:
19
DR. WESLEY LONG:
Director.
The Director, thank you.
20
Director of the Joint Institute for Food Safety and
21
Applied Nutrition will take responsibility
22
point, we’re not really set up, but we could be set up
23
very soon to take data.
24
to do sort of a secondary cleansing of data.
The
-- at this
He will take the responsibility
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I think you
163
1
would want to -- if you had to blind the data, you would
2
probably want to do that first.
3
mechanism to do that.
4
assurance, again, that -- of course, all of the
5
information that goes in the Clearinghouse does become
6
public.
7
opportunity to blind the data again and further assure
8
submitters of the confidentiality of that information.
And he would provide the
But that FDA would never -- this is an
So, Dave Lineback -- I could give you
9
o
But he would be a second
10
information about how to get in contact with him.
11
might be another way to get that information.
12
MR. MICHAEL JAHNCKE:
13
MR. MORRIS POTTER:
That
Morrie?
I guess if I could recap
14
where we are, Richard has suggested that there is
15
information in the Federal Register where you can send
16
it.
17
And, in fact, you could also send it to Richard or to me
18
or to Joe Levitt (phonetic) or to anybody else in the
19
building, and we will see that it gets to the right
20
place.
Wes has suggested that you could send it to Dave.
I_)
u
u
z
cd
21
MR. MICHAEL JAHNCKE:
Yes, Bob?
22
MR. ROBERT BUCHANAN:
And to answer the second
23
half of your question, Bruce, on how to tell whether or
24
not the data is being used similar to the document that
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1
you have in front of you that outlines the data sources
2
that are being considered, the risk assessment itself
3
will detail the data that was selected for use and the
4
criteria for using it.
5
you would know it by reading the final document.
MR. MICHAEL JAHNCKE:
6
7
8
9
So, if your data didn’t get used,
questions?
Other comments and
Yes, Dane?
MR. DANE BERNARD:
Thank you.
Dane Bernard.
Pat, you covered a number of things in your review of the
epidemiological
11
have watched outbreak information and epidemiological
12
studies for some years, occasionally run across things
13
that we don’t necessarily agree with, that maybe they
14
weren’t in fact quite as well-established
15
they might have been.
16
information.
Some of us, I think, who
10
as we thought
Is there any need to or will you be reviewing
17
any of the source information on past studies to see
18
whether it meets some kind of criteria of acceptability
19
in terms of whether we, in fact, have targeted all the
20
right foods or maybe have targeted one or two too many as
21
being implicated in outbreaks?
22
MR. MICHAEL JAHNCKE:
23
DR. PATRICK McCARTHY:
24
Please identify yourself.
Pat McCarthy.
Before I
refer some data over to Clark Barrington who’s going to
_—.
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1
be doing the modelling, I am going to look at it to make
2
sure that it seems reasonable to me that the cases are
3
well-described
4
there, including the rationale for implicating the
5
particular food.
and that it has the basic information in
I’m going to try to summarize the data a little
6
But
7
bit, in addition to giving them the raw data.
8
summarize the data a little bit to give them an
9
indication of how often a particular food or type of food
10
is being referred to in the studies that I refer to.
11
yes, I’m going to try to be critical in terms of which
12
studies are referred.
13
MR. MICHAEL JAHNCKE:
Bob?
14
MR. ROBERT BUCHANAN:
Bob Buchanan, FDA.
Sor
In
15
yesterday’s session on vibrio parahaemolyticus,
16
quite a long time on the dose-response area talking about
17
multiple biological end points and what would be
18
appropriate to model in the case of vibrio.
19
fairly classic enteric pathogen.
20
colonization of the intestinal tract as one biological
21
end point.
22
we spent
And thatls a
You deal with
Sepsis is a second biological end point.
23
Gastroenteritis
is an intermediate biological end point.
24
In your presentation, Pat, you gave several different
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potential biological end points.
2
a model for infection that would not be too dissimilar
3
from what we were discussing yesterday on vibrio.
Have you decided yet on what will be your
4
5
biological end points that you’re going to be modelling
6
or considering?
7
it going to be one for sepsis, one for meningitis,
8
for neonates?
m
Lu
+
Are you going to do multiple ones?
DR. PATRICK McCARTHY:
9
ol
And, Rich, you provided
1
Is
one
This is Pat McCarthy.
10
had planned to take a look at the studies and, again, to
11
put them together in terms of -- in a lot of different
12
ways.
13
different ways.
14
are two big end points.
15
modeler an estimate of how often those particular end
16
points come up in the literature that I reviewed.
17
also, since the more mild symptoms, there seems to be
18
several studies that refer to mild symptoms, I was also
19
going to give them an estimate of how often that seems to
20
show Up.
Organize the data for the model in a lot of
And, certainly, sepsis and meningitis
I was going to try to give the
And
cc
o
a
LL
a
I
21
In terms of headache or chills or abdominal
22
pain, I’m not there yet in terms of how I’m going to
23
group that data; but it might be -- I do have estimates
24
in different papers of how often subjects or cases had
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1
diarrhea
2
how
3
be open when
4
productive for him.
And
so, I haven’t
I’m going to give it to them,
I do and give
but
really
decided
I’m going to try to
it to him the way that’s most
5
MR. MICHAEL JAHNCKE:
Yes, Bob?
6
MR. ROBERT BUCHANAN:
Sort of a follow-up on
7
this, now directed towards Rich.
Rich, do we have any estimates on the
8
9
probability of colonization or attachment?
In presenting
10
your model of the infection, you just sort of said
11
llattachment,l!and you didn’t really deal with that.
Do we have any estimates on what it takes to
12
_-
or had chills.
13
get attachment, or are there different known attachment
14
mechanisms?
15
of attachment?
MR. MICHAEL JAHNCKE:
16
17
20
Identify yourself,
please.
DR. RICHARD RAYBOURNE:
18
19
Can you come up with any kind of probability
Yes.
Rich Raybourne,
FDA .
In the model I presented, I mentioned the
21
Internalin, which is essentially an attachment-type
22
virulence determinant.
23
with colonization, I’m not aware -- I don’t have that
24
information right now.
In terms of numbers associated
There may, in fact, be some
.-.
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1
because a number of oral infectivity studies have been
2
done.
3
or not, I’m aware of one study where they looked at
4
invasion in the intestinal wall and quantified organisms
5
invading the intestine of the mouse.
6
no, I don’t know of any.
And whether they used attachment as an end point
MR. MICHAEL JAHNCKE:
7
8
But beyond that,
Other questions and
comments?
Our next presenter, before we have it, on
9
10
behalf of the subcommittee, weld certainly like to
11
express our appreciation to all the presenters today and
12
all the hard work.
13
nicely.
14
The product is coming along quite
Thank you very much.
Our next presenter is Dr. Richard Whiting.
15
he is going to be giving a summary of what has been
16
presented and discussed, presented today.
17
DR. RICHARD WHITING:
And
I’m just going to be very
But maybe
18
brief in light of this good discussion we had.
19
we can start with Bruce’s question on this disputed
20
figure here.
21
did have some comments on the draft phase, but I guess we
22
didn’t get around to revising it.
23
to say here at the top, “Food consumption, food
24
contamination.”
This is the one Bruce is referring to.
We
But it’s just trying
These two go together to form your
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–.-=
And then this middle part, “Food Vehicle
1
exposure.
2
Virulence and Susceptibility” is the disease triangle
3
idea, the hazard assessment, and that leading on to
4
illness.
5
it.
6
and reworking of that to make it a little bit more clear.
It’s trying to give a little sense of flow to
I guess I can see we can do a little bit of editing
7
There’s kind of an old saying that risk
8
assessment people have had, “Let the data speak.”
9
guess that’s largely where we are at this point in the
You can see we’ve accumulated a lot of
10
risk assessment.
11
information.
12
would like to go with it.
13
And I
We~ve given you some ideas of where we
The next stage for the risk assessors is to try
14
to take all of this information and, really, just see
15
what we can do with it, see what the information can be
16
summarized as.
17
trying to combine the information on the presence of
18
Listeria in foods with the consumption.
19
And I think you’ve seen the problems with
That data base that Mary has -- I forgot.
She
20
had something like eight or ten different categories of
21
hamburgers.
22
cheeses, we have some good consumption information on
23
some of the Hispanic cheeses, for example.
24
these data bases don’t say anything about whether this
And then when you get to data like the
_-
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But then
170
And this is the
1
was pasteurized or unpasteurized cheese.
2
kind of information that we have to try now to pool
3
together and bring out of it the conclusions that we feel
4
are justified in bringing out.
5
will be quite a few areas where we will just say there is
6
not information available that we can go further.
7
part of the exercise of doing a risk assessment like this
8
is to highlight the data gaps.
And we may find there
And
I also think that this will be an iterative-
9
I think it will be occurring both
10
type of process.
11
within the next few months, and I can see us doing an
12
initial summary of the data, which will perhaps highlight
13
certain areas that we will then go back out and try to
14
find more detailed information on.
And I can see sort of this second round as a
15
16
point where we will probably try to get in contact with
17
various people in the industry who might have information
18
on specific consumption,
19
pasteurized versus unpasteurized in certain groups of
20
cheeses.
21
information on consumption patterns or food preparation
22
habits.
23
yet but might be very relevant for particular classes of
24
food .
you know, my question of
Or perhaps the industry might have some
Various questions like this which we don’t have
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so, I see this as an iterative-type process,
1
2
and it will probably continue beyond the September,
3
October date that we have set as a target for completion
4
of the first part of the risk assessment.
5
And we’ve also made quite a few references here
6
today to various research projects that are underway, the
7
primate pregnant monkey primate study, and various
8
studies like this -- which obviously won’t be ready by
9
September and October but yet, obviously, we want to take
10
that and look at the risk assessment again as soon as
11
that data becomes available.
I have been quite heartened today by, I think,
12
I was
13
the sense of participation here by the industry.
14
on the Salmonella enteritis and egg risk assessment team
15
that the USDA did a year or so ago.
And at that point,
16
we sort of approached the industry.
And I would say they
17
approached us back with quite a bit of trepidation.
18
we really did not get very much back that was helpful to
19
it.
20
the whole risk assessment process is about.
21
everyone is becoming a little bit more aware of just what
22
a risk assessment is and what it does and that people
23
will be a little more willing to participate
24
think for all of us, our goals are increased food safety.
And
I think there was a lot of apprehension about what
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in this.
I
172
1
And I really do put a plug out there and echo again the
2
conversation we did just have about the submission of
3
data and blinded data.
4
out to industry and everyone to become active and follow
5
it.
6
bring to us, that you do that.
9
And if you have specific information that you can
So, with that, Mr. Chairman, I thank you very
7
8
And I really do put an invitation
much.
MR. MICHAEL JAHNCKE:
Thank you very much.
10
Again, thanks to your entire group.
11
it and thank you.
Certainly appreciate
12
Morrie, 1’11 turn this over to you.
13
MR. MORRIS POTTER:
I’d like to add
That was
14
congratulations to the risk assessment team.
15
very nicely done.
16
like once more to invite participants today who are not
17
members of the committee to come to the mike, identify
18
yourself and make whatever statements you’d like to about
19
the risk assessment model that was presented today, the
20
direction the team is taking or other comments on the
21
risk of foodborne Listeriosis.
22
And on behalf of FDA and FSIS, I would
Perhaps while people are thinking about that,
23
I’d like to direct a question to Wally.
24
arose earlier about colonization.
The question
And I wondered if you
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1
had any information on either transient or long-term
2
colonization from your clinical experience.
3
MR. WALLY SCHLECH:
Thanks, Morrie.
Wally
I don’t have any information
4
Schlech from Delhausen.
5
other than to say we did some carriage studies during the
6
now-ancient maritime outbreak in family members,
7
primarily, and did find some carriage.
8
probably because they were eating the same items in the
9
menu and during the time we were sampling which, in fact,
We assume that’s
10
was often 30 -- probably several months after the case,
11
were able to find some Listeria.
12
new items or leftover from the previous, I don’t know.
But whether these were
13
I think there are some Dutch studies -- I
14
believe in Europe, some old studies of longitudinal
15
carriage, as I recall.
16
would suggest that carriage is transient, that it may
17
remain in the bowel flora for a period of time.
18
not certain.
19
I think, although most people
So, I’m
I think I wanted to raise a question about the
I think the febrile
20
biological endpoints.
21
gastroenteritis
22
And the thing that wasn’t talked about today is the
23
extraordinarily high attack rates within the exposed
24
group for that particular syndrome, whereas mostly the
syndrome is very much a distinct entity.
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1
Listeriosis you see, even in the outbreak situation, the
2
attack rates in the overall population are quite low.
I think there is some evidence that that may be
3
4
more related to a huge dose and possibly even local.
So,
5
maybe the hemolysin acts as a local cytotoxin in the gut
6
for a period or something.
I don’t know.
I’ve done some
7
But I think there is some data.
8
work in gastrointestinal carriage in mice and rats.
9
we can see carriage persist for a couple of weeks in the
And
But we haven’t really gone beyond that at
10
droppings.
11
this point in time.
And there certainly doesn’t seem to be any
12
The Internalin protein, I
13
specific attachment factors.
14
think, is an interesting protein.
15
things we think about, pili and other sort of typical
16
attachment factors, Listeria doesn’t exhibit them.
17
we really don’t have any information there.
MR. MORRIS POTTER:
18
But in terms of the
Thanks, Wally.
And
Other
In that case, I think we can wrap this up.
19
comments?
20
Tomorrow morning we start again at 8:00 for the plenary
21
session of the National Food Advisory Committee.
a
UJ
V2
<
-J
22
(Whereupon, the hearing in this
23
matter was concluded at 3:20 p.m.)
24
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day of
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