Statistical analyses for in vitro cytogenetic assays using Chinese hamster ovary cells.
It is a widely held view that objective statistical criteria are needed for the evaluation of genetic toxicity assays. This paper presents statistical methods for the analysis of data from in vitro sister chromatid exchange (SCE) and chromosome aberration tests that use Chinese hamster ovary cells. For SCEs, an extensive study of solvent control results demonstrated that there is a substantial interday component of variability in the data, and that a Poisson sampling model is applicable to data generated via the protocol of Galloway et al [1985]. Consequently, a trend test for evidence of a dose response is proposed for such SCE data. As an illustration of this statistical method, analysis of data previously considered to be negative [Gulati et al, 1985] indicates that di(2-ethyl-hexyl) phthalate induces a weak, but reproducible, SCE dose response in CHO cells. Monte Carlo methods are used to show that the trend test is more sensitive than four other statistical procedures considered for the analysis of Poisson-distributed SCEs. A similar trend test for dose response in proportions is proposed for chromosome aberration data, where the percent of cells with chromosome aberrations is the response of interest. Sensitivity (or power) studies indicate that three doses and a control with 50 cells/dose point is a reasonable design for an in vitro SCE study that uses the Galloway et al protocol. For in vitro chromosome aberrations, however, three doses and a control with 100 cells/dose point appears to produce too insensitive an assay; an increase to 200 cells/dose point in the Galloway et al protocol seems worthy of serious consideration.
Margolin
B H
BH
Resnick
M A
MA
Rimpo
J Y
JY
Archer
P
P
Galloway
S M
SM
Bloom
A D
AD
Zeiger
E
E
D000818:Animals; D002869:Chromosome Aberrations; D006224:Cricetinae; D005260:Female; D009152:Mutagenicity Tests / Q000592:standards*; D010053:Ovary; D012107:Research Design; D012854:Sister Chromatid Exchange; D013223:Statistics as Topic