Chemistry Reference
In-Depth Information
of a design is fi rst of all determined by the total number
of animals used. Distributing them over more dose
groups does not result in a poorer performance of the
study, despite the smaller number of animals per dose
group. Dose placement is another crucial factor, and to
minimize the risk of inadequate dose placement, the
use of multiple dose studies is favorable. As a concom-
itant advantage, the use of multiple doses mitigates
the disturbing effect of potential systematic errors in
single dose groups. However, for endpoints with large
residual variation (CV
For example, reproductive and developmental stud-
ies having generational nested study designs often
have greater sensitivity, and for such studies a BMR
of 5% has typically been used; similarly, epidemiology
studies often have greater sensitivities, and a BMR of
1% has typically been used for quantal human data.
For continuous data with a minimal level of change in
the endpoint that is generally considered to be biologi-
cally signifi cant (for example, a change in average adult
body weight of 10%, or the doubling of average level for
some liver enzyme), that amount of change can be used
to defi ne the BMR. The BMD and the benchmark dose
level [BMDL] corresponding to a change in the mean
response equal to one control standard deviation from
the control mean should also be presented for compari-
son purposes; if individual data are available and a deci-
sion can be made about which individual levels can be
reasonably considered adverse (perhaps on the basis of a
quantile of the control distribution, for example), the data
can be “dichotomized” on the basis of that cutoff value,
and the BMR can be set as previously for quantal data.
In the absence of any other idea of what level of
response to consider adverse, a change in the mean
equal to one control standard deviation from the con-
trol mean can be used. The control standard deviation
can be computed including historical control data,
but the control mean must be from data concurrent
with the treatments being considered (Crump, 1995).
Crump (1995) found that this gives an excess risk of
approximately 10% for the proportion of individuals
below the 2nd percentile or above the 98th percentile
of controls for normally distributed effects.
18%), there is a substantial
probability of not detecting the overall dose response,
and this probability increases in designs with increas-
ing number of dose groups. In such situations, six dose
groups may be used as a compromise. Designs with
high dose levels (i.e., associated with relatively high
effects) are helpful in estimating doses with smaller
effects (such as the BMD), and it seems bad practice
to omit higher dose groups to improve the fi t at lower
doses. The typical 28-days study design of four dose
groups with fi ve animals (per sex) may not be ade-
quate to assess endpoints with large residual variation
(CV
≥
18%), both in assessing a benchmark dose and in
assessing a NOAEL (Bokkers
et al.
, 2005).
≥
5.3 Data Types and Benchmark Dose
Although software for several continuous models is
available (USEPA, 2005), there may be occasions when
it is advantageous to convert continuous data to quan-
tal data, for example, before applying a BMD analysis
(an alternative to the NOAEL approach for assess-
ing noncancer risks associated with hazardous com-
pounds). In some cases, converting continuous data
into quantal data may more directly address a specifi c
defi nition of adverse response. For example, body
weight measurements for individual animals could be
converted to the incidence of animals that have more
than 10% lowering of body weight, if this is the crite-
rion for a signifi cant response. Rendering data quantal
may also facilitate comparisons among data sets if the
majorities are in quantal form. A major disadvantage
of continuous to quantal conversion is the loss of infor-
mation about the magnitude of response.
For quantal data, an excess risk of 10% is the default
BMR, because the 10% response is at or near the limit
of sensitivity in most cancer bioassays and in some
noncancer bioassays as well. If a study has greater than
usual sensitivity, a lower BMR can be used, although
the ED10 (the dose corresponding to a 10% increase in
an adverse effect, relative to the control response) and
LED10 (the 95% lower confi dence limit of the dose of
a chemical needed to produce an adverse effect in 10%
of those exposed to the chemical, relative to control)
should always be presented for comparison purposes.
6.0 DOSE-RESPONSE IN AN ERA
OF -OMICS
Dose response and dose effect are fundamental
descriptors of events occurring after an exposure.
Although the fi eld of toxicology continues to explode
with the development of new techniques, models, and
“-omics” areas of study, these underlying concepts
remain invaluable and are the common threads that
link these areas together. Newer terms including “bio-
logical monitoring” and “biomarkers,” which have
become more common in recent years, incorporate the
responses to exposures and include information on
dose response and effect. An in-depth discussion of
these terms is found in Chapter 4 (Fowler, 2005).
References
Albert, R. E., and Altshuller, B. (1973).
In
“Radionuclides Carcino-
genesis.” (J. E. Ballon, Ed.), pp. 233-253. AEC Symposium Series
CONT-72050. NIlS, Springfi eld, VA.
