Last week we discussed the general topic of low-dose extrapolation for
the purpose of setting Occupational Exposure Limits (OELs). This week we will get more specific; namely,
how do we go from high risk rat data to low risk extrapolated estimates for
humans?
As we established in previous blogs, in most cases the data ends at an effect level in
the animals at around 10% but we want an OEL in humans at a level of effect much
lower than this value. Theoretically and conceptually, we want to protect “nearly all”
who might be exposed. Low-dose
extrapolation is designed to inform us as to what “nearly all” might mean in
operational terms.
A basic problem exists that many
models will fit the actual rat data quite well but give VERY different
predictions when extrapolated to low risk at low dose. A slide that I have used in teaching for many
years is pasted below:
Please note that the normal range of available toxicological data
occurs all the way to the right of these curves and at high dose. All FOUR of the very different models on this graph can do
a perfectly good job of describing the available data but all are quite
different in their predictions of response/risk at low dose.
Consider the curve labeled “False” Threshold (supralinear). Like all the curves it starts at zero dose
with a background level of the toxicological effect under consideration. Let us for sack of this example, assume it
is cancer which has a relatively strong background level in humans and rats. As soon as the dose come up
from zero the putative risk predicted from this model rises rapidly until it
reaches a local peak. Then it declines
to very close to background (i.e., the "false" threshold) and finally, proceeds upward into the normal range
of toxicological response. This may seem
somewhat fanciful; however, this “false” threshold curve has been proposed by
some to describe what may be happening with endocrine disruptors.
Let us now look at the point labeled “threshold”. Here the putative
effect of dose reaches the background line at a relatively high dose. Below this dose it is assumed that there is
NO harmful effect from exposure for anyone or at least for the vast majority of the
population. Indeed, much of the conventional wisdom in
toxicological circles today is that this situations exists for a majority of
chemicals especially those considered to be non-cancer causing agents.
Now let’s examine, the “No threshold (sublinear)” line and model. This is where the conventional wisdom currently
puts carcinogenic (especially genotoxic carcinogenic) risk assessment. The assumption being that even a single
molecule can mutate DNA and cause cancer and that 2 molecules presents twice the
risk.
My personal favorite model and line on this slide is labeled “Hormesis”. Here there is actually a LOWER risk
predicted versus background as the dose comes up from zero. It eventually, climbs up the curve into the
normal range of toxicological data; however, I think you can see what a
dramatic effect this curve might have on risk assessment if it were generally
true. I am going to devote an entire
blog to the subject of hormesis but I wanted to include it here just to show
the comparison with the others.
I have studied this dilemma for a long time and in my opinion we are
not in position today to scientifically prove that any of these curves are true
representations of reality for most chemicals under consideration. ALL of these models/curves/predictions are in effect, arguments without data.
I have heard it said that “There are many questions that cannot be
answered but that must be decided.” I believe that it is up to the best science available
to inform these political decisions as to which model(s) we use and where we
draw the line in setting OELs. Even
after a model is chosen, the uncertainty around the predictions of that model
needs to be disclosed so that those viewing and using the OELs understand
exactly where they came from.
The next blog is designed to open your mind relative to possible and seemingly strange reality of hormesis and offer my ideas on want needs to happen to
determine just what is occurring at low doses in human tissue.
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