The 1986 EPA Cancer Risk Assessment Guidelines
Having been written on the heels of the influential 1983 NRC
report, the EPA (1986) guidelines closely follow their recommendations. Compared to later revisions, it is very
brief. However, it did confront the
issue of model uncertainty:
Different extrapolation models,
however, may fit the observed data reasonably well but may lead to large
differences in the projected risk at low doses.
As the solution to the problem, the 1986 guidelines offered
this:
The Agency will review each
assessment as to the evidence on carcinogenesis mechanisms and other biological
or statistical evidence that indicates the suitability of a particular
extrapolation model. Goodness-of-fit to the experimental observations is not an
effective means of discriminating among models (OSTP, 1985). A rationale will
be included to justify the use of the chosen model. In the absence of adequate
information to the contrary, the linearized multistage procedure will be
employed. Where appropriate, the results of using various extrapolation models
maybe useful for comparison with the linearized multistage procedure.
This short paragraph makes three important statements. First, it recognizes that goodness-if-fit
(i.e statistical evidence) and biological evidence (i.e. a biological
rationale) are both important in selecting a suitable model for
extrapolation. Second, it introduces the
linearized multistage model as the default option that will be used unless
there is “adequate information to the contrary”. Third, it is suggested that, at least under
some circumstances, it may be desirable to make risk estimates using
alternative models as well. The second
and third statements are further elaborated in the next paragraph:
It should be emphasized that the
linearized multistage procedure leads to a plausible upper limit to the risk
that is consistent with some proposed mechanisms of carcinogenesis. Such an
estimate, however, does not necessarily give a realistic prediction of the
risk. The true value of the risk is unknown, and maybe as low as zero. The
range of risks, defined by the upper limit given by the chosen model and the
lower limit which may be as low as zero, should be explicitly stated. An
established procedure does not yet exist for making “most likely" or
"best" estimates of risk within the range of uncertainty defined by the
upper and lower limit estimates. If data and procedures become available, the
Agency will also provide "most likely" or "best" estimates
of risk. This will be most feasible when human data are available and when
exposures are in the dose range of the data.
As the plausible worst case option, the justification for
the default option is the same as the de
minimus application used by the USFDA.
It is also acknowledged that lower estimates are also plausible. In particular, it is suggested that the risk
may be as low as zero. It is also
acknowledges that, even though there is no established procedure for doing so,
providing a best estimate would also be desirable.
Adequate Evidence to the Contrary
The 1986 guidelines did not attempt to define what evidence
would be considered sufficient to overturn the default option. In the following decade, many chemical
industry studies were sponsored to provide the necessary evidence, usually by
showing, or attempting to show, that a nongenotoxic mechanism is responsible
for the development of tumors at high doses.
But, as it turned out, no scientific argument fraught with uncertainty
was ever found to be sufficient to overturn the bright and shiny default option
that exhibited no uncertainty whatsoever.
Another NRC (1994) committee that took up this issue, a gave
a discussion of the matter in one of the appendices. The EPA (1999) guidelines summarized this
discussion:
Appendix N of the report contains
two presentations of alternative views held by some committee members on this
issue. One view, known as
"plausible conservatism," suggested that departures from defaults
should not be made unless new information improves the understanding of a
biological process to the point that relevant experts reach consensus that the
protective default assumption concerning that process is no longer plausible. The same criterion was recommended where the
underlying scientific mechanism is well understood, but where a default is used
to address missing data. In this case,
the default should not be replaced with case-specific data unless it is the
consensus of relevant experts that the proffered data make the default
assumption no longer plausible. Another
view, known as the "maximum use of scientific information" approach,
acknowledged that the initial choice of defaults should be protective, but
argued that conservatism should not be a factor in determining whether to
depart from the default in favor of an alternate biological theory or alternate
data. According to this view, it should
not be necessary to reach expert consensus that the default assumption had been
rendered implausible; it should be sufficient that risk assessors find the
alternate approach more plausible than the default.
The thing is, both these “views” are reasonable
for some applications. If the regulatory
statute is intended to be conservative (e.g. the Delaney clause or a premarket
approval process), then using the default as long as it remains plausible is
sensible. On the other hand, justifying
a regulation with a cost-benefit analysis with a less-likely default option
makes no sense at all; money will be spent to avoid health outcomes that
probably won’t happen.
The 1996 Proposed and 1999 EPA Interim Guidelines for Carcinogen Risk Assessment
Although these guidelines were never finalized, they exhibit
the evolution that took place over the next 10 years. With regard to model uncertainty, the key development
was the division of the dose-response relationship into two zones that are
separated by a “Point of Departure”. The
high-dose zone is defined by “the empirical data in the range of observation”. As another “default option” the point of
departure is to be defined by the LED10, which corresponds to the
lower confidence limit of the estimated dose where 10% of the population
exhibits the effect. When used for
effects other than cancer the Effective Dose (ED) is also known as the
benchmark dose (BMD), which is roughly equivalent to the No Observed Adverse
Effect Level. The use of the LED was
expressly motivated by a desire to harmonize methodologies used for cancer and
non-cancer endpoints; “the LED10 can be regarded as an improved and
harmonized estimate of the NOAEL”.
However, genotoxic carcinogens, the guidelines suggest that linear
extrapolation from the POD is appropriate:
The use of straight line
extrapolation for a linear default is a change from the 1986 guidelines which
used the "linearized multistage" (LMS) procedure. This change is made because the former
modeling procedure gave an appearance of specific knowledge and sophistication
unwarranted for a default.
This is the shell game, of course. The linear model is no longer justified as a
plausible worst-case scenario. It is
simply justified by agency policy. It also
seems rather clear that guideline authors wanted to restrict the choices
presented to agency managers, who will by and large fail to notice that the
scientific rug has been pulled from underneath the risk estimates. When considering the possibility of
characterizing model uncertainty associated with using different plausible
models to estimate:
Discussion of the confidence in the
extrapolation is appropriately done qualitatively or by showing results for
alternatives that are equally plausible. It is not useful, for example, to
conduct quantitative uncertainty analysis running multiple forms of linear
models. This would obviate the function of the policy default.
Why, oh why, would obviating the function of the policy
default be a bad idea? As God and the
1983 NRC report intended, agency policy can always be applied AFTER the risk
assessment is completed. But, if you are
playing the shell game, it isn’t. This
time, the shell game victims are the scientists who are trying to provide a
theoretical basis for estimating risks. Since
inductive reasoning can’t be reliably controlled, keeping control of the decision
process dictates that it be excluded.
The 90’s guidelines do promote the use of biological models
or “mode-of-action” analyses that may influence the way the assessment
proceeds. If it can be shown that a
carcinogen is nongenotoxic, then instead of a fake risk estimate, there will be
no risk estimate.
The 2005 Cancer Risk Assessment Guidelines
While the Weight of the Evidence discussion is much
improved, there are no substantial procedural differences between the 2005
guidelines and the 1999 Interim guidelines with regard to dose-response
modeling. However, the shell game was
ratcheted up another gear, presumably to put cancer risk assessment on the same
footing as the ersatz noncancer variety.
Most notably, the procedure for “nonlinear extrapolation” is the same methodology
used for the reference dose, which involves no extrapolation whatsoever. The most vigorous shell game is played in the
section on the “POD narrative”. The
problem is this:
As a single-point summary of a
single dose-response curve, the POD alone does not convey all the critical
information present in the data from which it is derived. To convey a measure of uncertainty, the POD
should be presented as a central estimate with upper and lower bounds. A POD
narrative summarizes other important features of the database and the POD that
are important to account for in low-dose extrapolations or other analyses.
It is not at all clear who the narrative is to be directed
to. Is the risk assessor writing the
narrative for a risk manager who stands upon the POD gazing out across the
vast, or not so vast, expanse of the Margin of Exposure towards the region
where the actual exposures occur? Or, is
it some secondary risk assessor who is expected to pick up the pieces of this
mess? The most ironic directive is this
one:
(d) Slope of the dose-response curve at the POD. How does response
change as dose is reduced below the POD?
A steep slope indicates that risk decreases rapidly as dose decreases.
On the other hand, a steep slope also indicates that errors in an exposure
assessment can lead to large errors in estimating risk. Both aspects of the slope are important. The slope also indicates whether
dose-response curves for different effects are likely to cross below the POD.
This narrative seems to instruct the reader to ignore the
POD. What a great idea; maybe we should
actually do a risk assessment that, you know, actually provides risk estimates.
Really, the 1986 guidelines were pretty good. It needed some tweaking and appendix N of the
1994 NRC report provided a pretty good start for doing just that. But instead, we got the science-policy shell
game designed to make the default option the only option. Where the choice was between uncertain theory
or nothing, we got the latter.
References
USEPA (1999). Guidelines for
Carcinogen Risk Assessment, Review Draft, CEAF-0644,
Office of Research and Development.
Office of Research and Development.
Official Post Soundtrack
Post Notes
Thesis post #26. Second in the shell game series. A longer than normal essay, but I think it all needs to be there.
Soundtrack: Not Australia; the fatal shore is the POD.
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