technical guidance documents - Institute for Health and Consumer ...

EFFECTS ASSESSMENT
Multiple values for the same endpoint with the same species should be investigated on a case-bycase
basis, looking for reasons for differences between the results. For equivalent data on the
same end-point and species, the geometric mean should be used as the input value for the
calculation. If this is not possible, perhaps because valid results are considered to be too variable,
then grouping and combining the values, e.g. by pH ranges, and using reduced numbers of
values should be considered. The effects that these different treatments have on the derived value
(and on the resulting risk characterisation) should be investigated and discussed.
Where it is considered that the results are limited to certain conditions (e.g. not appropriate for
low pH conditions) then these limitations should be explained. The values derived from different
treatments of the data may be useful to indicate sensitive regions.
Fit to a distribution
Different distributions like e.g. log-logistic, log-normal or others may be used (Aldenberg and
Jaworska, 2000, Aldenberg and Slob, 1993). The log-normal distribution is a pragmatic choice
from the possible families of distributions because of the available description of its
mathematical properties (methods exist that allow for most in depth analyses of various
uncertainties).
The Anderson–Darling goodness of fit test can be used in addition to the Kolmogorov-Smirnovtest,
as a criterion for the choice of a parametric distribution for comprehensive data sets,
because it gives more weight to the tails of the distribution. A lack of fit may be caused by very
different factors. One common factor seems to be the inclusion of several NOECs for species
tested in a single laboratory, where the same test concentrations were used for all species. The
statistical determination of the NOEC can lead to the same value being obtained for several
species, showing up as a vertical row of NOECs in the cumulative distribution plots. Another
reason for lack of fit is a possible bimodality of the SSD, due to a specific mode of action of the
tested substance towards only some taxonomic groups of species.
Whatever the fit to a distribution, results should be discussed in regards to the graphical
representation of the species distribution and the different p values that were obtained with each
test. Finally, any choice of a specific distribution function should be clearly explained.
If the data do not fit any distribution, the left tail of the distribution (the lowest effect
concentrations) should be analysed more carefully. If a subgroup of species can be identified as
particularly sensitive and if the number of data on this subgroup is sufficient, the distribution can
be fit to this subgroup. In case of lack of fit, the SSD method should not be used.
Estimated parameter
For pragmatic reasons it has been decided that the concentration corresponding with the point in
the SSD profile below which 5% of the species occur should be derived as an intermediate value
in the determination of a PNEC. A 50% confidence interval (c.i.) associated with this
concentration should also be derived.
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