Philip Morris
Do Rodent Studies Predict Human Cancers?
Fields
- Author
- Wildavsky, A.
- Type
- SCRT, REPORT, SCIENTIFIC
- FOOT, FOOTNOTES
- Site
- E12
- Document File
- 2502145956/2502146352/Thresholds 4
- Master ID
- 2502146051/6295
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- Litigation
- Fali/Produced
- Named Person
- Ames, B.
- Anderson
- Armitage
- Chu
- Cohen
- Columbus
- Crisp, P.F.
- Doll
- Doull, J.
- Ellwein
- Fears
- Freedman
- Gladwell, M.
- Gold, L.
- Gough, M.
- Griesemer, R.A.
- Harris, R.
- Krewski, D.
- Lave, L.
- Levenson, L.
- Markov
- Perera
- Peto, R.
- Salzburg
- Swenberg
- Train, R.
- Weibull
- Zeisel
- Anderson
- Named Organization
- British Toxicological Society
- Congress
- Division of Toxicological Research + Tes
- Epa, Environmental Protection Agency
- Executive Office of the President
- FDA, Food and Drug Administration
- Food Safety Council
- Interagency Comm
- Nas, Natl Academy of Sciences
- Natl Inst of Environmental Health
- Natl Public Radio
- Office of Technology Assessment
- Univ of Ks
- Wa Post
- Congress
- Area
- DEMPSEY,RUTH/OFFICE
- Date Loaded
- 21 Mar 2000
- UCSF Legacy ID
- zpp22d00
Document Images
11-
way of analogy, if you drop a bottle from 10 feet off the
ground, it's pretty obvious what's going to happen.
(Sound of glass shattering)
Harris: This large drop is equivalent to a large dose of a
chemical, and it can be deadly. But what if, instead of taking
one bottle and dropping it from 10 feet, you take 10 bottles
and drop them from one foot? It's like giving many people a
smaller dose of that toxic chemical_ Here's what the EPA
assumes will happen.
(Sound of several bottles hitting the ground and one of them
shattering)
Harris: They figure one of the 10 bottles will break. The
reasoning is that one-tenth the dose, or one-tenth the drop
distance, will do one-tenth the damage. In reality, though, this
is what happens-
(Sound of several bottles hitting the ground)
Harris: There is, in fact, a safe height you can drop a bottle
from without breaking it, and John Doull from the University of
Kansas says the same idea holds for toxic chemicals.

Doull: It is the dose, not the compound, that determines its
adverse effects . . . .
Harris: So, recently, researchers like Swenberg have started to
dig deeper and ask why some chemicals trigger cancer in some
animals. It's as though they're trying to understand the
difference between turntables and CD players. And Swenberg
says one especially interesting example is unleaded gasoline.
You may have been the sticker at the pump warning that
gasoline causes cancer in laboratory animals. Well, here's the
story with gasoline.
Swenberg: It causes kidney cancer in male rats only, not in
female rates and not in mice.
Harris: So what's going on? Swenberg decided to find out by
studying those animals, and he discovered that a chemical in
gasoline binds to a naturally-occuring protein that's only found
in the kidneys of male rats.
Swenberg: And this results in a build-up of the protein and
ultimately leads to the development of cancer. And since
humans do not synthesize this protein, this is not likely to be a
-- a mechanism important to humans.
Harris: Swenberg says dozens of other chemicals besides
gasoline cause this specific kidney cancer in male rats,

13
including copy machine toner, a bathroom deodorizer and even
a natural chemical called D-limonene.
Swenberg: It turns out that about two glasses of orange juice
contains a carcinogenic amount of D-limonene for the male rat,
but it has absolutely no effect on mice or on female rats, and
I'm sure it has no effect on humans.
Harris: As a result of this research, the Environmental
Protection Agency recently decided that if a chemical like
gasoline only triggers this kind of kidney tumor in male rats
and it doesn't do anything else bad, it's probably not going to
cause cancer in people. So far there are just a handful of
stories like this where scientists have actually figured out why
a compound is causing tumors in certain animals. But there are
a lot more studies in the works, including reassessments of
dioxin, formaldehyde and certain PCBs?t
Knowledge of mechanisms yields far greater discriminatory power.
With such knowledge scientists can determine whether there is a
threshold below which there is no damage or whether harm occurs
proportionate to the dose, however low that dose is. No mechanism,
no dose-response relationship.
The War over the Dose-Response Threshold N
O
tV
i
A
OI
~
i
N

There is disagreement over whether there is a dose-response
threshold, so that below a certain level no harm occurs, or whether
the damage is linear, such that harm from a chemical increases or
decreases as a proportion of the dose. It is important, to start with,
to ask why such an apparently technical matter has occasioned so
much dispute.
Because the field of toxicology is built on the principle that the
poison is in the dose, the opposing linear (or proportional) principle--
there is no threshold dose below which damage cannot occur--is a
challenge to toxicological science.
A common statement about dose response levels is that no one
really understands what happens when people are exposed to very
low levels of chemicals.22 There is no difficulty in finding
substances, such as the heart medicine digitalis, that are helpful at
low doses but can be fatal at large doses. But that does not answer
the question of whether there are substances for which no threshold
exists23 Given there is a considerable range of sensitivity among,
human beings, it can always be said that some hypersensitive people
might be adversely affected. The traditional response has been to
use a margin of safety to take care of the supersusceptible. Given
also that chemicals may interact with each other to create cancers
that neither substance would alone, it cannot be said definitively that
either is safe. By the same token, however, one chemical may render
another harmless or less harmful.24
The regulatory response is that the dose-response relationship
is linear. The rationale is that this provides a margin of safety for
the public. The question is whether this assumption is true.

15
Going further into the "furious battle [that] rages around the
threshold controversy,"'25 it will be instructive to read a semiofficial
account by high-ranking Environmental Protection Agency officials
published in a major journal, Risk Anal,ysis. The models EPA uses
attempt to establish an upper-bound, nearly the worst that could
happen, on the basis of a no-threshold linear response_ Anderson et
al. are quite open in saying that "This recognition that the lower
bound may __. be indistinguishable from zero stems from the
uncertainties associated with mechanisms of carcinogenesis including
the possibility of detoxification and repair mechanisms, metabolic
pathways, and the role of the agent in the cancer process."26 In
short, for all EPA knows, there may be no damage at low doses.
Furthermore, Anderson et al. continue, "Most often there is no
biological justification to support the choice of any one model to
describe actual risk."27 While this task would be easy if there were
data on actual environmental exposures to human beings, in which
case an appropriate model could be fitted to the data, the EPA article
continues, "In the absence of such data a variety of models can be
used to fit the data in the observed range, but these models differ
sharply (in the danger estimates they produce] at low doses."ZS If
the choice of model determines the results, because they "differ
sharply at low doses," why bother with the experiment? Exactly.
Employing the justification that nevertheless these models are the
best available, Anderson et al. state that "It should be clear from the
preceding discussion that the linear non-threshold model has been
used by the EPA to place plausible upper bounds on risk, not to
establish actual risk."29 This is a significant admission.

1
My question is "best for what"? Use of the upper bound
misleads people into thinking it is an actual estimate of hazard by an
authoritative government agency when it is not. Use of "worst case"
scenarios makes no sense, moreover, when there is reason why the
outcome may be zero and there is no biological sense in anticipatory
epidemic consequences.
Now we know that everything depends on which of the
available statistical models are used and whether whichever one is
chosen in the absence of biological indications, tells us what we need
to know. Does it?
EPA claims that the linear, no-dose-response model best fits
knowledge about cancer causation. But its officials could not know
this without knowledge of the mechanisms at work, in which case
they would be able to choose one they knew fit the causal
relationship. At other times, they acknowledge the real basis for
their choice of model, the desire to choose the most conservative
estimate so as to, as the saying goes, act on the side of safety. But.
are they so acting?
If it is true, as Anderson et al. say in their appendix, that
"There is no really solid scientific basis for any mathematical
extrapolation model relating carcinogen exposure to cancer risks at
the extremely low levels of concentration that must be dealt, with in
evaluating environmental hazards,"30 then why make one? The
answer must be that with going from rodents to people most
regulation of chemicals would lack a rationale that could be called
scientific. No science, no regulation; no man-mouse extrapolation, no
science, no regulation. The models that make this extrapolation

plausible are the important thing. Extrapolations from animals dosed
at very high levels to people exposed to far smaller levels make
sense only in the context of the models of cancer causation into
which they are meant to fit.
Multistage Models
Is this chemical guilty and to what degree at which dose and to
whom? Interpretation of cancer causation depends on models, which
we can think of as symbolic representations of theories, with
numbers attached, that give meaning to the data. No model, no
interpretation, no meaning, no result. Actually, there have to be two
models in one; first, a model of the biology underlying cancer
causation and, second, the statistical approximation of that model.
Getting accurate results depends both on the predictive power of the
biological model of cancer causation and on whether the statistical
approximation captures the causal structure of the model. If the _
model does not well describe cancer causation in human beings, and
if, on top of that, the statistical approximation does not well describe
the model, the errors in both models multiply to give unsatisfactory
results. The task is a daunting one.
We can take the Armitage-Doll model as representative of
those used by governmental agencies in regulation. It seeks to
describe the relationship between exposures to chemicals and the
incidence of cancer at various ages for men and women.31 The
biological version portrays human cells as going through a number of
stages that ultimately result in cancer. The hypothesis is that one or
17

I
more cells receives an insult and then goes through several changes
that turn them into malignant cells after which they proliferate. The
times and the different stages are not specified. All these stages are
probabilistic in that some cells under the same exposure will become
cancerous and others will not. "Put another way, with multistage
models," Richard Peto tells us, "when all the predisposing factors
have been allowed for, luck has an essential role in determining who
gets cancer and who does not."32 Thus the stages in the models are
essentially probabilities without the users knowing whether human
cancer proceeds in those stages or according to those odds.33 In the
field of economics, these would be called Markov chain models,
which means essentially that every present stage depends on results
of previous stages. The time spent in the various stages is assumed
to be proportionate to the exposure of the affected individual.
The basic difficulty with multistage models, as the reader
might imagine, is that there is little reason to believe they actually
capture the biological process of cancer formation. At the same time,
the statistical manipulations are very far from the causal
requirements of the model, so that one has no idea what one has got
when the result is cranked out.34 Which brings us to the statistical
interpretation of animal cancer studies, the most critical and least
understood part of modeling cancer causation.
The existence of twelve different test groups tells us that
statistical inference is the essence of the matter: after all,
conclusions are to be drawn observing differences between the
control group and other animals and between sexual and dose

19
groups. This is not something that can be done by counting on the
fingers of one hand. It requires methods based on statistical theory.
Biological Interpretation of Animal Cancer Tests
Fears at al. are wise in concluding that "There is danger in
relying solely on the finding of statistical significance without
incorporating biological knowledge and corraborative evidence such
as the presence of a dose-response relationship for experimentally
consistent results in different species or sexes."35 But what if there
is little or no biological knowledge?
In order to get accurate estimates of the probability that
chemicals that cause cancer in animals also cause cancer in human
beings, Salzburg recommends applying "the bioassay to a number of
innocuous substances. There have to be some compounds that are
not human carcinogens, or the whole exercise of looking for
carcinogens makes no sense." Yet, after examining the literature,, he
finds that "this was never done for the [rodentj lifetime feeding
study ...."36 His argument needs to be heard in full:
Thus, it would appear that no attempt has ever been made
to determine how well society can identify human carcinogens
by feeding groups of 50 rats and mice, each, the suspect
substance at maximum tolerated doses for their entire lives.
Common scientific prudence would suggest that this assay be
tried on a group of known human carcinogens and on a group
of supposedly innocuous substances (such as sucrose or amino

2(
acids) before we either (1) believe that it provides some
protection for society (sensitivity) or (2) believe it identifies
mainly harmful substances (specificity). There is no substitute
for such proper validation on any new bioassay.37
He believes "that we are confusing the effects of biological activity
upon the old-age legions of rodents with the thing we fear, cancer."38
There is also the claim that cancers found in rate autopsies are
induced by test procedures that feed them at the MTD_
Mitogenesis. or Is Cancer Caused bv the Test
and Not by the Chemicals?
The charge, if true, that the tumors observed in animal cancer
tests may be due to the huge doses delivered at the MTD would be
fatal to the no-threshold idea. For then the animal cancer tests
themselves would be taking out only what they put in: cancer in,
cancer out. Bruce Ames and Lois Gold, among others, claim that the
chronic wounding induced by delivering heavy doses of a chemical
promotes cancer by inducing cell division, a process called
mitogensis. As the animal is effectively wounded or poisoned, it
grows replacement cells, a process known to increase chances of
mutation and hence of cancer.
The theory was prompted by findings that while cancer is
thought to be accompanied by mutation, alteration, or damage of
DNA, a large proportion of the chemicals that cause cancers in animal
tests do not in fact damage genes in other tests. There are, as a
