Journal Article

DKFZ-2019-02868

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Modeling dose-response functions for combination treatments with log-logistic or Weibull functions.

Holland-Letz, T. (First author)DKFZ* ; Leibner, A.DKFZ* ; Kopp-Schneider, A. (Last author)DKFZ*

2020
Springer Heidelberg

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Please use a persistent id in citations: doi:10.1007/s00204-019-02631-2

Abstract: Dose-response curves of new substances in toxicology and related areas are commonly fitted using log-logistic functions. In more advanced studies, an additional interest is often how these substances will behave when applied in combination with a second substance. Here, an essential question for both design and analysis of these combination experiments is whether the resulting dose-response function will still be a member of the class of log-logistic functions, and, if so, what function parameters will result for the combined substances. Different scenarios might be considered in regard to whether a true interaction between the substances is expected, or whether the combination will simply be additive. In this paper, it is shown that the resulting function will in general not be a log-logistic function, but can be approximated very closely with one. Parameters for this approximation can be predicted from the parameters of both ingredients. Furthermore, some simple interaction structures can still be represented with a single log-logistic function. The approach can also be applied to Weibull-type dose-response functions, and similar results are obtained. Finally, the results were applied to a real data set obtained from cell culture experiments involving two cancer treatments, and the dose-response curve of a combination treatment was predicted from the properties of the singular substances.

Note: #EA:C060#LA:C060# 2020 Jan;94(1):197-204

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Contributing Institute(s):

1. C060 Biostatistik (C060)
2. KKE Pädiatrische Onkologie (B310)

Research Program(s):

1. 313 - Cancer risk factors and prevention (POF3-313) (POF3-313)

Appears in the scientific report 2020

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Database coverage:
; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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