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@ARTICLE{Jiang:126790,
author = {X. Jiang$^*$ and A. Kopp-Schneider$^*$},
title = {{S}tatistical strategies for averaging {EC}50 from multiple
dose-response experiments.},
journal = {Archives of toxicology},
volume = {89},
number = {11},
issn = {1432-0738},
address = {Berlin},
publisher = {Springer},
reportid = {DKFZ-2017-02818},
pages = {2119 - 2127},
year = {2015},
abstract = {In most dose-response studies, repeated experiments are
conducted to determine the EC50 value for a chemical,
requiring averaging EC50 estimates from a series of
experiments. Two statistical strategies, the mixed-effect
modeling and the meta-analysis approach, can be applied to
estimate average behavior of EC50 values over all
experiments by considering the variabilities within and
among experiments. We investigated these two strategies in
two common cases of multiple dose-response experiments in
(a) complete and explicit dose-response relationships are
observed in all experiments and in (b) only in a subset of
experiments. In case (a), the meta-analysis strategy is a
simple and robust method to average EC50 estimates. In case
(b), all experimental data sets can be first screened using
the dose-response screening plot, which allows visualization
and comparison of multiple dose-response experimental
results. As long as more than three experiments provide
information about complete dose-response relationships, the
experiments that cover incomplete relationships can be
excluded from the meta-analysis strategy of averaging EC50
estimates. If there are only two experiments containing
complete dose-response information, the mixed-effects model
approach is suggested. We subsequently provided a web
application for non-statisticians to implement the proposed
meta-analysis strategy of averaging EC50 estimates from
multiple dose-response experiments.},
keywords = {Valproic Acid (NLM Chemicals)},
cin = {C060},
ddc = {610},
cid = {I:(DE-He78)C060-20160331},
pnm = {313 - Cancer risk factors and prevention (POF3-313)},
pid = {G:(DE-HGF)POF3-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:25294322},
doi = {10.1007/s00204-014-1350-3},
url = {https://inrepo02.dkfz.de/record/126790},
}