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Analysis of graded lesions in long-term carcinogenicity studies

Authors Fry JS, Lee PN, Hamling JS

Received 1 February 2013

Accepted for publication 15 March 2013

Published 14 May 2013 Volume 2013:3 Pages 11—37

DOI https://doi.org/10.2147/OAMS.S43535

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John S Fry, Peter N Lee, Jan S Hamling

PN Lee Statistics and Computing, Sutton, UK

Abstract: In long-term carcinogenicity studies, the Peto test is the standard method for analyzing lesions that are not observable in life, taking into account differential between-group mortality. This method requires knowledge for each animal in each group of when the animal died, whether a lesion was seen postmortem, and the context of observation (ie, whether the lesion was fatal [considered to have contributed to its death] or whether it was incidental [seen in an animal dying for an unrelated reason]). The Peto test was not designed to take severity of the lesion into account. Age-adjusted analysis taking severity into account can be carried out using a stratified version of the Kruskal–Wallis one-way analysis of variance by ranks, but this does not take context of observation into account. Here, we describe an extended version of the stratified Kruskal–Wallis test that both allows analysis of lesions graded on severity and takes fatality of the lesion into account. This includes both a test for between-group heterogeneity and a test for dose-related trend, and provides a powerful method for analyzing such data. The Peto and Kruskal–Wallis tests may be considered special cases of this more general test. The test may be applied not only to nonneoplastic lesions (such as chronic progressive nephropathy), where pathologists often grade severity on a 5-point scale, but also to preneoplastic and neoplastic lesions, carrying out a single analysis of focal hyperplasia, benign tumor, and malignant tumor of a specific histological type, regarding these as successive stages of a progressive condition.

Keywords: carcinogenicity tests, survival analysis, heterogeneity, trend, stratified analysis

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